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Sample records for hierarchical method based

  1. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

    PubMed Central

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

  2. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

    PubMed

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

  3. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

    PubMed

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

  4. 3D CAD model retrieval method based on hierarchical multi-features

    NASA Astrophysics Data System (ADS)

    An, Ran; Wang, Qingwen

    2015-12-01

    The classical "Shape Distribution D2" algorithm takes the distance between two random points on a surface of CAD model as statistical features, and based on that it generates a feature vector to calculate the dissimilarity and achieve the retrieval goal. This algorithm has a simple principle, high computational efficiency and can get a better retrieval results for the simple shape models. Based on the analysis of D2 algorithm's shape distribution curve, this paper enhances the algorithm's descriptive ability for a model's overall shape through the statistics of the angle between two random points' normal vectors, especially for the distinctions between the model's plane features and curved surface features; meanwhile, introduce the ratio that a line between two random points cut off by the model's surface to enhance the algorithm's descriptive ability for a model's detailed features; finally, integrating the two shape describing methods with the original D2 algorithm, this paper proposes a new method based the hierarchical multi-features. Experimental results showed that this method has bigger improvements and could get a better retrieval results compared with the traditional 3D CAD model retrieval method.

  5. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  6. A Bayesian hierarchical method to account for random effects in cytogenetic dosimetry based on calibration curves.

    PubMed

    Mano, Shuhei; Suto, Yumiko

    2014-11-01

    The dicentric chromosome assay (DCA) is one of the most sensitive and reliable methods of inferring doses of radiation exposure in patients. In DCA, one calibration curve is prepared in advance by in vitro irradiation to blood samples from one or sometimes multiple healthy donors in considering possible inter-individual variability. Although the standard method has been demonstrated to be quite accurate for actual dose estimates, it cannot account for random effects, which come from such as the blood donor used to prepare the calibration curve, the radiation-exposed patient, and the examiners. To date, it is unknown how these random effects impact on the standard method of dose estimation. We propose a novel Bayesian hierarchical method that incorporates random effects into the dose estimation. To demonstrate dose estimation by the proposed method and to assess the impact of inter-individual variability in samples from multiple donors on the estimation, peripheral blood samples from 13 occupationally non-exposed, non-smoking, healthy individuals were collected and irradiated with gamma rays. The results clearly showed significant inter-individual variability and the standard method using a sample from a single donor gave anti-conservative confidence interval of the irradiated dose. In contrast, the Bayesian credible interval for irradiated dose calculated by the proposed method using samples from multiple donors properly covered the actual doses. Although the classical confidence interval of calibration curve with accounting inter-individual variability in samples from multiple donors was roughly coincident with the Bayesian credible interval, the proposed method has better reasoning and potential for extensions.

  7. Hierarchical design of an electro-hydraulic actuator based on robust LPV methods

    NASA Astrophysics Data System (ADS)

    Németh, Balázs; Varga, Balázs; Gáspár, Péter

    2015-08-01

    The paper proposes a hierarchical control design of an electro-hydraulic actuator, which is used to improve the roll stability of vehicles. The purpose of the control system is to generate a reference torque, which is required by the vehicle dynamic control. The control-oriented model of the actuator is formulated in two subsystems. The high-level hydromotor is described in a linear form, while the low-level spool valve is a polynomial system. These subsystems require different control strategies. At the high level, a linear parameter-varying control is used to guarantee performance specifications. At the low level, a control Lyapunov-function-based algorithm, which creates discrete control input values of the valve, is proposed. The interaction between the two subsystems is guaranteed by the spool displacement, which is control input at the high level and must be tracked at the low-level control. The spool displacement has physical constraints, which must also be incorporated into the control design. The robust design of the high-level control incorporates the imprecision of the low-level control as an uncertainty of the system.

  8. MtHc: a motif-based hierarchical method for clustering massive 16S rRNA sequences into OTUs.

    PubMed

    Wei, Ze-Gang; Zhang, Shao-Wu

    2015-07-01

    The recent sequencing revolution driven by high-throughput technologies has led to rapid accumulation of 16S rRNA sequences for microbial communities. Clustering short sequences into operational taxonomic units (OTUs) is an initial crucial process in analyzing metagenomic data. Although many methods have been proposed for OTU inferences, a major challenge is the balance between inference accuracy and computational efficiency. To address these challenges, we present a novel motif-based hierarchical method (namely MtHc) for clustering massive 16S rRNA sequences into OTUs with high clustering accuracy and low memory usage. Suppose all the 16S rRNA sequences can be used to construct a complete weighted network, where sequences are viewed as nodes, each pair of sequences is connected by an imaginary edge, and the distance of a pair of sequences represents the weight of the edge. MtHc consists of three main phrases. First, heuristically search the motif that is defined as n-node sub-graph (in the present study, n = 3, 4, 5), in which the distance between any two nodes is less than a threshold. Second, use the motif as a seed to form candidate clusters by computing the distances of other sequences with the motif. Finally, hierarchically merge the candidate clusters to generate the OTUs by only calculating the distances of motifs between two clusters. Compared with the existing methods on several simulated and real-life metagenomic datasets, we demonstrate that MtHc has higher clustering performance, less memory usage and robustness for setting parameters, and that it is more effective to handle the large-scale metagenomic datasets. The MtHC software can be freely download from for academic users.

  9. MtHc: a motif-based hierarchical method for clustering massive 16S rRNA sequences into OTUs.

    PubMed

    Wei, Ze-Gang; Zhang, Shao-Wu

    2015-07-01

    The recent sequencing revolution driven by high-throughput technologies has led to rapid accumulation of 16S rRNA sequences for microbial communities. Clustering short sequences into operational taxonomic units (OTUs) is an initial crucial process in analyzing metagenomic data. Although many methods have been proposed for OTU inferences, a major challenge is the balance between inference accuracy and computational efficiency. To address these challenges, we present a novel motif-based hierarchical method (namely MtHc) for clustering massive 16S rRNA sequences into OTUs with high clustering accuracy and low memory usage. Suppose all the 16S rRNA sequences can be used to construct a complete weighted network, where sequences are viewed as nodes, each pair of sequences is connected by an imaginary edge, and the distance of a pair of sequences represents the weight of the edge. MtHc consists of three main phrases. First, heuristically search the motif that is defined as n-node sub-graph (in the present study, n = 3, 4, 5), in which the distance between any two nodes is less than a threshold. Second, use the motif as a seed to form candidate clusters by computing the distances of other sequences with the motif. Finally, hierarchically merge the candidate clusters to generate the OTUs by only calculating the distances of motifs between two clusters. Compared with the existing methods on several simulated and real-life metagenomic datasets, we demonstrate that MtHc has higher clustering performance, less memory usage and robustness for setting parameters, and that it is more effective to handle the large-scale metagenomic datasets. The MtHC software can be freely download from for academic users. PMID:25912934

  10. Arbitrary Order Hierarchical Bases for Computational Electromagnetics

    SciTech Connect

    Rieben, R N; White, D; Rodrigue, G

    2002-12-20

    We present a clear and general method for constructing hierarchical vector bases of arbitrary polynomial degree for use in the finite element solution of Maxwell's equations. Hierarchical bases enable p-refinement methods, where elements in a mesh can have different degrees of approximation, to be easily implemented. This can prove to be quite useful as sections of a computational domain can be selectively refined in order to achieve a greater error tolerance without the cost of refining the entire domain. While there are hierarchical formulations of vector finite elements in publication (e.g. [1]), they are defined for tetrahedral elements only, and are not generalized for arbitrary polynomial degree. Recently, Hiptmair, motivated by the theory of exterior algebra and differential forms presented a unified mathematical framework for the construction of conforming finite element spaces [2]. In [2], both 1-form (also called H(curl)) and 2-form (also called H(div)) conforming finite element spaces and the definition of their degrees of freedom are presented. These degrees of freedom are weighted integrals where the weighting function determines the character of the bases, i.e. interpolatory, hierarchical, etc.

  11. Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?. -based on different credit correlations using hierarchical methods

    NASA Astrophysics Data System (ADS)

    He, Fang; Chen, Xi

    2016-11-01

    The accelerating accumulation and risk concentration of Chinese local financing platforms debts have attracted wide attention throughout the world. Due to the network of financial exposures among institutions, the failure of several platforms or regions of systemic importance will probably trigger systemic risk and destabilize the financial system. However, the complex network of credit relationships in Chinese local financing platforms at the state level remains unknown. To fill this gap, we presented the first complex networks and hierarchical cluster analysis of the credit market of Chinese local financing platforms using the "bottom up" method from firm-level data. Based on balance-sheet channel, we analyzed the topology and taxonomy by applying the analysis paradigm of subdominant ultra-metric space to an empirical data in 2013. It is remarked that we chose to extract the network of co-financed financing platforms in order to evaluate the effect of risk contagion from platforms to bank system. We used the new credit similarity measure by combining the factor of connectivity and size, to extract minimal spanning trees (MSTs) and hierarchical trees (HTs). We found that: (1) the degree distributions of credit correlation backbone structure of Chinese local financing platforms are fat tailed, and the structure is unstable with respect to targeted failures; (2) the backbone is highly hierarchical, and largely explained by the geographic region; (3) the credit correlation backbone structure based on connectivity and size is significantly heterogeneous; (4) key platforms and regions of systemic importance, and contagion path of systemic risk are obtained, which are contributed to preventing systemic risk and regional risk of Chinese local financing platforms and preserving financial stability under the framework of macro prudential supervision. Our approach of credit similarity measure provides a means of recognizing "systemically important" institutions and regions

  12. Hierarchical bilateral filtering based disparity estimation for view synthesis

    NASA Astrophysics Data System (ADS)

    Shin, Hong-Chang; Lee, Gwangsoon; Cheong, Won-Sik; Hur, Namho

    2016-06-01

    In this paper, we introduce a high efficient and practical disparity estimation using hierarchical bilateral filtering for real-time view synthesis. The proposed method is based on hierarchical stereo matching with hardware-efficient bilateral filtering. Hardware-efficient bilateral filtering is different from the exact bilateral filter. The purpose of the method is to design an edge-preserving filter that can be efficiently parallelized on hardware. The proposed hierarchical bilateral filtering based disparity estimation is essentially a coarse-to-fine use of stereo matching with bilateral filtering. It works as follows: firstly, the hierarchical image pyramid are constructed; the multi-scale algorithm then starts by applying a local stereo matching to the downsampled images at the coarsest level of the hierarchy. After the local stereo matching, the estimated disparity map is refined with the bilateral filtering. And then the refined disparity map will be adaptively upsampled to the next finer level. The upsampled disparity map used as a prior of the corresponding local stereo matching at the next level, and filtered and so on. The method we propose is essentially a combination of hierarchical stereo matching and hardware-efficient bilateral filtering. As a result, visual comparison using real-world stereoscopic video clips shows that the method gives better results than one of state-of-art methods in terms of robustness and computation time.

  13. A hierarchical classification method for finger knuckle print recognition

    NASA Astrophysics Data System (ADS)

    Kong, Tao; Yang, Gongping; Yang, Lu

    2014-12-01

    Finger knuckle print has recently been seen as an effective biometric technique. In this paper, we propose a hierarchical classification method for finger knuckle print recognition, which is rooted in traditional score-level fusion methods. In the proposed method, we firstly take Gabor feature as the basic feature for finger knuckle print recognition and then a new decision rule is defined based on the predefined threshold. Finally, the minor feature speeded-up robust feature is conducted for these users, who cannot be recognized by the basic feature. Extensive experiments are performed to evaluate the proposed method, and experimental results show that it can achieve a promising performance.

  14. A hierarchical method for molecular docking using cloud computing.

    PubMed

    Kang, Ling; Guo, Quan; Wang, Xicheng

    2012-11-01

    Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein-ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs.

  15. A hierarchical method for molecular docking using cloud computing.

    PubMed

    Kang, Ling; Guo, Quan; Wang, Xicheng

    2012-11-01

    Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein-ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs. PMID:23017886

  16. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    EPA Science Inventory

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  17. Constructing storyboards based on hierarchical clustering analysis

    NASA Astrophysics Data System (ADS)

    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.

  18. Parallel iterative solvers and preconditioners using approximate hierarchical methods

    SciTech Connect

    Grama, A.; Kumar, V.; Sameh, A.

    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.

  19. Multigrid hierarchical simulated annealing method for reconstructing heterogeneous media

    NASA Astrophysics Data System (ADS)

    Pant, Lalit M.; Mitra, Sushanta K.; Secanell, Marc

    2015-12-01

    A reconstruction methodology based on different-phase-neighbor (DPN) pixel swapping and multigrid hierarchical annealing is presented. The method performs reconstructions by starting at a coarse image and successively refining it. The DPN information is used at each refinement stage to freeze interior pixels of preformed structures. This preserves the large-scale structures in refined images and also reduces the number of pixels to be swapped, thereby resulting in a decrease in the necessary computational time to reach a solution. Compared to conventional single-grid simulated annealing, this method was found to reduce the required computation time to achieve a reconstruction by around a factor of 70-90, with the potential of even higher speedups for larger reconstructions. The method is able to perform medium sized (up to 3003 voxels) three-dimensional reconstructions with multiple correlation functions in 36-47 h.

  20. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation.

    PubMed

    Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

    2016-08-16

    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.

  1. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    PubMed Central

    Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

    2016-01-01

    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. PMID:27537888

  2. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation.

    PubMed

    Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

    2016-01-01

    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. PMID:27537888

  3. Carbon composition with hierarchical porosity, and methods of preparation

    SciTech Connect

    Mayes, Richard T; Dai, Sheng

    2014-10-21

    A method for fabricating a porous carbon material possessing a hierarchical porosity, the method comprising subjecting a precursor composition to a curing step followed by a carbonization step, the precursor composition comprising: (i) a templating component comprised of a block copolymer, (ii) a phenolic component, (iii) a dione component in which carbonyl groups are adjacent, and (iv) an acidic component, wherein said carbonization step comprises heating the precursor composition at a carbonizing temperature for sufficient time to convert the precursor composition to a carbon material possessing a hierarchical porosity comprised of mesopores and macropores. Also described are the resulting hierarchical porous carbon material, a capacitive deionization device in which the porous carbon material is incorporated, as well as methods for desalinating water by use of said capacitive deionization device.

  4. Low energy isomers of (H2O)25 from a hierarchical method based on Monte Carlo temperature basin paving and molecular tailoring approaches benchmarked by MP2 calculations.

    PubMed

    Sahu, Nityananda; Gadre, Shridhar R; Rakshit, Avijit; Bandyopadhyay, Pradipta; Miliordos, Evangelos; Xantheas, Sotiris S

    2014-10-28

    We report new global minimum candidate structures for the (H2O)25 cluster that are lower in energy than the ones reported previously and correspond to hydrogen bonded networks with 42 hydrogen bonds and an interior, fully coordinated water molecule. These were obtained as a result of a hierarchical approach based on initial Monte Carlo Temperature Basin Paving sampling of the cluster's Potential Energy Surface with the Effective Fragment Potential, subsequent geometry optimization using the Molecular Tailoring Approach with the fragments treated at the second order Møller-Plesset (MP2) perturbation (MTA-MP2) and final refinement of the entire cluster at the MP2 level of theory. The MTA-MP2 optimized cluster geometries, constructed from the fragments, were found to be within <0.5 kcal/mol from the minimum geometries obtained from the MP2 optimization of the entire (H2O)25 cluster. In addition, the grafting of the MTA-MP2 energies yields electronic energies that are within <0.3 kcal/mol from the MP2 energies of the entire cluster while preserving their energy rank order. Finally, the MTA-MP2 approach was found to reproduce the MP2 harmonic vibrational frequencies, constructed from the fragments, quite accurately when compared to the MP2 ones of the entire cluster in both the HOH bending and the OH stretching regions of the spectra.

  5. Comparison of the incremental and hierarchical methods for crystalline neon.

    PubMed

    Nolan, S J; Bygrave, P J; Allan, N L; Manby, F R

    2010-02-24

    We present a critical comparison of the incremental and hierarchical methods for the evaluation of the static cohesive energy of crystalline neon. Both of these schemes make it possible to apply the methods of molecular electronic structure theory to crystalline solids, offering a systematically improvable alternative to density functional theory. Results from both methods are compared with previous theoretical and experimental studies of solid neon and potential sources of error are discussed. We explore the similarities of the two methods and demonstrate how they may be used in tandem to study crystalline solids.

  6. Method for implementation of recursive hierarchical segmentation on parallel computers

    NASA Technical Reports Server (NTRS)

    Tilton, James C. (Inventor)

    2005-01-01

    A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.

  7. Model-based hierarchical reinforcement learning and human action control.

    PubMed

    Botvinick, Matthew; Weinstein, Ari

    2014-11-01

    Recent work has reawakened interest in goal-directed or 'model-based' choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour.

  8. Model-based hierarchical reinforcement learning and human action control

    PubMed Central

    Botvinick, Matthew; Weinstein, Ari

    2014-01-01

    Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822

  9. [A medical image semantic modeling based on hierarchical Bayesian networks].

    PubMed

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  10. Cascade process modeling with mechanism-based hierarchical neural networks.

    PubMed

    Cong, Qiumei; Yu, Wen; Chai, Tianyou

    2010-02-01

    Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

  11. Hierarchical cobalt-based hydroxide microspheres for water oxidation.

    PubMed

    Zhang, Ye; Cui, Bai; Derr, Olivia; Yao, Zhibo; Qin, Zhaotong; Deng, Xiangyun; Li, Jianbao; Lin, Hong

    2014-03-21

    3D hierarchical cobalt hydroxide carbonate hydrate (Co(CO3)0.5(OH)·0.11H2O) has been synthesized featuring a hollow urchin-like structure by a one-step hydrothermal method at modest temperature on FTO glass substrates. The functionalities of precursor surfactants were isolated and analyzed. A plausible formation mechanism of the spherical urchin-like microclusters has been furnished through time-dependent investigations. Introduction of other transitional metal doping (Cu, Ni) would give rise to a substantial morphological change associated with a surface area drop. The directly grown cobalt-based hydroxide composite electrodes were found to be capable of catalyzing oxygen evolution reaction (OER) under both neutral pH and alkaline conditions. The favorable 3D dendritic morphology and porous structure provide large surface areas and possible defect sites that are likely responsible for their robust electrochemical activity.

  12. Hierarchic plate and shell models based on p-extension

    NASA Technical Reports Server (NTRS)

    Szabo, Barna A.; Sahrmann, Glenn J.

    1988-01-01

    Formulations of finite element models for beams, arches, plates and shells based on the principle of virtual work was studied. The focus is on computer implementation of hierarchic sequences of finite element models suitable for numerical solution of a large variety of practical problems which may concurrently contain thin and thick plates and shells, stiffeners, and regions where three dimensional representation is required. The approximate solutions corresponding to the hierarchic sequence of models converge to the exact solution of the fully three dimensional model. The stopping criterion is based on: (1) estimation of the relative error in energy norm; (2) equilibrium tests, and (3) observation of the convergence of quantities of interest.

  13. Auction-based resource allocation game under a hierarchical structure

    NASA Astrophysics Data System (ADS)

    Cui, Yingying; Zou, Suli; Ma, Zhongjing

    2016-01-01

    This paper studies a class of auction-based resource allocation games under a hierarchical structure, such that each supplier is assigned a certain amount of resource from a single provider and allocates it to its buyers with auction mechanisms. To implement the efficient allocations for the underlying hierarchical system, we first design an auction mechanism, for each local system composed of a supplier and its buyers, which inherits the advantages of the progressive second price mechanism. By employing a dynamic algorithm, each local system converges to its own efficient Nash equilibrium, at which the efficient resource allocation is achieved and the bidding prices of all the buyers in this local system are identical with each other. After the local systems reach their own equilibria respectively, the resources assigned to suppliers are readjusted via a dynamic hierarchical algorithm with respect to the bidding prices associated with the implemented equilibria of local systems. By applying the proposed hierarchical process, the formulated hierarchical system can converge to the efficient allocation under certain mild conditions. The developed results in this work are demonstrated with simulations.

  14. Iris Image Classification Based on Hierarchical Visual Codebook.

    PubMed

    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.

  15. Iris Image Classification Based on Hierarchical Visual Codebook.

    PubMed

    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. PMID:26353275

  16. A new artefacts resistant method for automatic lineament extraction using Multi-Hillshade Hierarchic Clustering (MHHC)

    NASA Astrophysics Data System (ADS)

    Šilhavý, Jakub; Minár, Jozef; Mentlík, Pavel; Sládek, Ján

    2016-07-01

    This paper presents a new method of automatic lineament extraction which includes the removal of the 'artefacts effect' which is associated with the process of raster based analysis. The core of the proposed Multi-Hillshade Hierarchic Clustering (MHHC) method incorporates a set of variously illuminated and rotated hillshades in combination with hierarchic clustering of derived 'protolineaments'. The algorithm also includes classification into positive and negative lineaments. MHHC was tested in two different territories in Bohemian Forest and Central Western Carpathians. The original vector-based algorithm was developed for comparison of the individual lineaments proximity. Its use confirms the compatibility of manual and automatic extraction and their similar relationships to structural data in the study areas.

  17. Asymmetric capacitors using lignin-based hierarchical porous carbons

    NASA Astrophysics Data System (ADS)

    Salinas-Torres, David; Ruiz-Rosas, Ramiro; Valero-Romero, María José; Rodríguez-Mirasol, José; Cordero, Tomás; Morallón, Emilia; Cazorla-Amorós, Diego

    2016-09-01

    Hierarchical porous carbons (HPC) were fabricated from lignin by hard template method using Beta and Y zeolites as templates. Textural properties were dictated by the hard template, obtaining a bi-modal pore size distribution with similar micropore sizes but different mesopore sizes. These HPCs provide a well-connected and developed porosity that show capacitance values near to 140 F g-1 in 1 M H2SO4 at 1 A g-1 and a capacitance retention of ca. 50% and 40% when the specific current is increased from 1 to 64 A g-1 for the Y and the Beta-based carbons, respectively. A symmetric capacitor working at 1.2 V with energy densities of 4.2 Wh kg-1 at 1.3 kW kg-1 has been obtained using the Beta-based HPC. Asymmetric in mass design allowed to operate the capacitor safely at 1.4 V, yielding an energy density of 6.3 Wh kg-1 at 1.3 kW kg-1, an increase of 50% with respect to the symmetric configuration, while keeping a maximum power near to 50 kW kg-1. This capacitor has an energy density comparable to that of a symmetric supercapacitor built using a commercial activated carbon of much higher porosity development, outperforming it in terms of energy, coulombic efficiencies and maximum power.

  18. Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

    NASA Astrophysics Data System (ADS)

    Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

    2012-11-01

    This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

  19. Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

    2011-01-01

    The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

  20. P2MP MPLS-Based Hierarchical Service Management System

    NASA Astrophysics Data System (ADS)

    Kumaki, Kenji; Nakagawa, Ikuo; Nagami, Kenichi; Ogishi, Tomohiko; Ano, Shigehiro

    This paper proposes a point-to-multipoint (P2MP) Multi-Protocol Label Switching (MPLS) based hierarchical service management system. Traditionally, general management systems deployed in some service providers control MPLS Label Switched Paths (LSPs) (e.g., RSVP-TE and LDP) and services (e.g., L2VPN, L3VPN and IP) separately. In order for dedicated management systems for MPLS LSPs and services to cooperate with each other automatically, a hierarchical service management system has been proposed with the main focus on point-to-point (P2P) TE LSPs in MPLS path management. In the case where P2MP TE LSPs and services are deployed in MPLS networks, the dedicated management systems for P2MP TE LSPs and services must work together automatically. Therefore, this paper proposes a new algorithm that uses a correlation between P2MP TE LSPs and multicast VPN services based on a P2MP MPLS-based hierarchical service management architecture. Also, the capacity and performance of the proposed algorithm are evaluated by simulations, which are actually based on certain real MPLS production networks, and are compared to that of the algorithm for P2P TE LSPs. Results show this system is very scalable within real MPLS production networks. This system, with the automatic correlation, appears to be deployable in real MPLS production networks.

  1. Hierarchical clustering method for improved prostate cancer imaging in diffuse optical tomography

    NASA Astrophysics Data System (ADS)

    Kavuri, Venkaiah C.; Liu, Hanli

    2013-03-01

    We investigate the feasibility of trans-rectal near infrared (NIR) based diffuse optical tomography (DOT) for early detection of prostate cancer using a transrectal ultrasound (TRUS) compatible imaging probe. For this purpose, we designed a TRUS-compatible, NIR-based image system (780nm), in which the photo diodes were placed on the trans-rectal probe. DC signals were recorded and used for estimating the absorption coefficient. We validated the system using laboratory phantoms. For further improvement, we also developed a hierarchical clustering method (HCM) to improve the accuracy of image reconstruction with limited prior information. We demonstrated the method using computer simulations laboratory phantom experiments.

  2. Recent global methane trends: an investigation using hierarchical Bayesian methods

    NASA Astrophysics Data System (ADS)

    Rigby, M. L.; Stavert, A.; Ganesan, A.; Lunt, M. F.

    2014-12-01

    Following a decade with little growth, methane concentrations began to increase across the globe in 2007, and have continued to rise ever since. The reasons for this renewed growth are currently the subject of much debate. Here, we discuss the recent observed trends, and highlight some of the strengths and weaknesses in current "inverse" methods for quantifying fluxes using observations. In particular, we focus on the outstanding problems of accurately quantifying uncertainties in inverse frameworks. We examine to what extent the recent methane changes can be explained by the current generation of flux models and inventories. We examine the major modes of variability in wetland models along with the Global Fire Emissions Database (GFED) and the Emissions Database for Global Atmospheric Research (EDGAR). Using the Model for Ozone and Related Tracers (MOZART), we determine whether the spatial and temporal atmospheric trends predicted using these emissions can be brought into consistency with in situ atmospheric observations. We use a novel hierarchical Bayesian methodology in which scaling factors applied to the principal components of the flux fields are estimated simultaneously with the uncertainties associated with the a priori fluxes and with model representations of the observations. Using this method, we examine the predictive power of methane flux models for explaining recent fluctuations.

  3. Hierarchical photocatalysts.

    PubMed

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

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

  4. Automated control of hierarchical systems using value-driven methods

    NASA Technical Reports Server (NTRS)

    Pugh, George E.; Burke, Thomas E.

    1990-01-01

    An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

  5. Facile Method toward Hierarchical Fullerene Architectures with Enhanced Hydrophobicity and Photoluminescence.

    PubMed

    Zheng, Shushu; Xu, Meilin; Lu, Xing

    2015-09-16

    A two-step self-assembly strategy has been developed for the preparation of fullerene hierarchical architectures. Typically, the precipitation method is utilized to synthesize the initial fullerene microstructures, and subsequently a drop-drying process is employed to facilitate the fullerene microstructures to self-assemble into the final hierarchical structures. Overall, this methodology is quite simple and feasible, which can be applied to prepare fullerene hierarchical structures with different morphological features, simply by choosing proper solvent. Moreover, the as-obtained C70 hierarchical structures have many superior properties over the original C70 microrods such as superhydrophobicity and unique photoluminescence behaviors, promising their applications as waterproof optoelectronics. PMID:26320882

  6. Hierarchical Methods for the Generation, Publication and Visualization of Huge Astronomical Data Cube Surveys

    NASA Astrophysics Data System (ADS)

    Fernique, P.; Allen, M.; Boch, T.; Bonnarel, F.; Oberto, A.

    2015-09-01

    The CDS has developed and validated new methods to generate, publish and display huge astronomical image data cubes based on the Hierarchical Progressive Survey (HiPS) framework. Data cubes with two spatial dimensions and an additional spectral or temporal dimension can be mapped onto HEALPix grids at different resolutions, which supports zooming and panning of the data across the sky with the ability to explore the third dimension of the cube. These methods are successfully applied to different sorts of cube data, and surveys of cube data.

  7. Hierarchical approaches to estimate energy expenditure using phone-based accelerometers.

    PubMed

    Vathsangam, Harshvardhan; Schroeder, E Todd; Sukhatme, Gaurav S

    2014-07-01

    Physical inactivity is linked with increase in risk of cancer, heart disease, stroke, and diabetes. Walking is an easily available activity to reduce sedentary time. Objective methods to accurately assess energy expenditure from walking that is normalized to an individual would allow tailored interventions. Current techniques rely on normalization by weight scaling or fitting a polynomial function of weight and speed. Using the example of steady-state treadmill walking, we present a set of algorithms that extend previous work to include an arbitrary number of anthropometric descriptors. We specifically focus on predicting energy expenditure using movement measured by mobile phone-based accelerometers. The models tested include nearest neighbor models, weight-scaled models, a set of hierarchical linear models, multivariate models, and speed-based approaches. These are compared for prediction accuracy as measured by normalized average root mean-squared error across all participants. Nearest neighbor models showed highest errors. Feature combinations corresponding to sedentary energy expenditure, sedentary heart rate, and sex alone resulted in errors that were higher than speed-based models and nearest-neighbor models. Size-based features such as BMI, weight, and height produced lower errors. Hierarchical models performed better than multivariate models when size-based features were used. We used the hierarchical linear model to determine the best individual feature to describe a person. Weight was the best individual descriptor followed by height. We also test models for their ability to predict energy expenditure with limited training data. Hierarchical models outperformed personal models when a low amount of training data were available. Speed-based models showed poor interpolation capability, whereas hierarchical models showed uniform interpolation capabilities across speeds. PMID:25014933

  8. Hierarchical colorant-based direct binary search halftoning.

    PubMed

    He, Zhen

    2010-07-01

    Colorant-based direct binary search (CB-DBS) halftoning proposed in provides an image quality benchmark for dispersed-dot halftoning algorithms. The objective of this paper is to further push the image quality limit. An algorithm called hierarchical colorant-based direct binary search (HCB-DBS) is developed in this paper. By appropriately integrating yellow colorant into dot-overlapping and dot-positioning controls, it is demonstrated that HCB-DBS can achieve better halftone texture of both individual and joint dot-color planes, without compromising the dot distribution of more visible halftone of cyan and magenta colorants. The input color specification is first converted from colorant space to dot-color space with minimum brightness variation principle for full dot-overlapping control. The dot-colors are then split into groups based upon dot visibility. Hierarchical monochrome DBS halftoning is applied to make dot-positioning decision for each group, constrained on the already generated halftone of the groups with higher priority. And dot-coloring is decided recursively with joint monochrome DBS halftoning constrained on the related total dot distribution. Experiments show HCB-DBS improves halftone texture for both individual and joint dot-color planes. And it reduces the halftone graininess and free of color mottle artifacts, comparing to CB-DBS.

  9. Hierarchical polypyrrole based composites for high performance asymmetric supercapacitors

    NASA Astrophysics Data System (ADS)

    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.

  10. Efficiently dense hierarchical graphene based aerogel electrode for supercapacitors

    NASA Astrophysics Data System (ADS)

    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.

  11. Efficiently dense hierarchical graphene based aerogel electrode for supercapacitors

    NASA Astrophysics Data System (ADS)

    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.

  12. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    PubMed

    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. PMID:19336318

  13. Facial animation on an anatomy-based hierarchical face model

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Prakash, Edmond C.; Sung, Eric

    2003-04-01

    In this paper we propose a new hierarchical 3D facial model based on anatomical knowledge that provides high fidelity for realistic facial expression animation. Like real human face, the facial model has a hierarchical biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. The deformable skin model has multi-layer structure to approximate different types of soft tissue. It takes into account the nonlinear stress-strain relationship of the skin and the fact that soft tissue is almost incompressible. Different types of muscle models have been developed to simulate distribution of the muscle force on the skin due to muscle contraction. By the presence of the skull model, our facial model takes advantage of both more accurate facial deformation and the consideration of facial anatomy during the interactive definition of facial muscles. Under the muscular force, the deformation of the facial skin is evaluated using numerical integration of the governing dynamic equations. The dynamic facial animation algorithm runs at interactive rate with flexible and realistic facial expressions to be generated.

  14. Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

    PubMed

    Jankovic, Marko; Ogawa, Hidemitsu

    2004-10-01

    Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

  15. Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

    PubMed

    Jankovic, Marko; Ogawa, Hidemitsu

    2004-10-01

    Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method. PMID:15593379

  16. Superhydrophobic Surface Based on a Coral-Like Hierarchical Structure of ZnO

    PubMed Central

    Wu, Jun; Xia, Jun; Lei, Wei; Wang, Baoping

    2010-01-01

    Background 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. Methodology 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. Results 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. PMID:21209931

  17. Growth of hierarchical based ZnO micro/nanostructured films and their tunable wettability behavior

    NASA Astrophysics Data System (ADS)

    Suresh Kumar, P.; Dhayal Raj, A.; Mangalaraj, D.; Nataraj, D.; Ponpandian, N.; Li, Lin; Chabrol, G.

    2011-05-01

    Hierarchical zinc oxide (ZnO) micro/nanostructured thin films were grown onto as-prepared and different annealed ZnO seed layer films by a simple two step chemical process. A cost effective successive ionic layer adsorption and reaction (SILAR) method was employed to grow the seed layer films at optimal temperature (80 °C) and secondly, different hierarchical based ZnO structured thin films were deposited over the seed layered films by chemical bath deposition (CBD). The influence of seed layer on the structural, surface morphological, optical and wettability behavior of the ZnO thin films were systematically investigated. The XRD analysis confirms the high crystalline nature of both the seed layer and corresponding ZnO micro/nanostructured films with a perfect hexagonal structure oriented along (0 0 2) direction. The surface morphology revels a complex and orientated hierarchical based ZnO structured films with diverse shapes from plates to hexagonal rod-like crystal to tube-like structure and even much more complex needle-like shapes during secondary nucleation, by changing the seed layer conditions. The water contact angle (WCA) measurements on hierarchical ZnO structured films are completely examined to study its surface wettability behavior for its suitability in future self-cleaning application. Photoluminescence (PL) spectra of the ZnO structured film exhibit UV and visible emissions in the range of 420-500 nm. The present approach demonstrates its potential for low-temperature, large-scale, controlled synthesis of crystalline hierarchical ZnO nanostructures films.

  18. Knowledge-based environment for hierarchical modeling and simulation

    SciTech Connect

    Kim, Taggon.

    1988-01-01

    This dissertation develops a knowledge-based environment for hierarchical modeling and simulation of discrete-event systems as the major part of a longer, ongoing research project in artificial intelligence and distributed simulation. In developing the environment, a knowledge representation framework for modeling and simulation, which unifies structural and behavioral knowledge of simulation models, is proposed by incorporating knowledge-representation schemes in artificial intelligence within simulation models. The knowledge base created using the framework is composed of a structural knowledge base called entity structure base and a behavioral knowledge base called model base. The DEVS-Scheme, a realization of DEVS (Discrete Event System Specifiation) formalism in a LISP-based, object-oriented environment, is extended to facilitate the specification of behavioral knowledge of models, especially for kernel models that are suited to model massively parallel computer architectures. The ESP Scheme, a realization of entity structure formalism in a frame-theoretic representation, is extended to represent structural knowledge of models and to manage it in the structural knowledge base.

  19. Model-based hand tracking using a hierarchical Bayesian filter.

    PubMed

    Stenger, Björn; Thayananthan, Arasanathan; Torr, Philip H S; Cipolla, Roberto

    2006-09-01

    This paper sets out a tracking framework, which is applied to the recovery of three-dimensional hand motion from an image sequence. The method handles the issues of initialization, tracking, and recovery in a unified way. In a single input image with no prior information of the hand pose, the algorithm is equivalent to a hierarchical detection scheme, where unlikely pose candidates are rapidly discarded. In image sequences, a dynamic model is used to guide the search and approximate the optimal filtering equations. A dynamic model is given by transition probabilities between regions in parameter space and is learned from training data obtained by capturing articulated motion. The algorithm is evaluated on a number of image sequences, which include hand motion with self-occlusion in front of a cluttered background.

  20. Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

    PubMed Central

    Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

    2012-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

  1. WSNs data acquisition by combining hierarchical routing method and compressive sensing.

    PubMed

    Zou, Zhiqiang; Hu, Cunchen; Zhang, Fei; Zhao, Hao; Shen, Shu

    2014-09-09

    We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs.

  2. Interframe hierarchical vector quantization using hashing-based reorganized codebook

    NASA Astrophysics Data System (ADS)

    Choo, Chang Y.; Cheng, Che H.; Nasrabadi, Nasser M.

    1995-12-01

    Real-time multimedia communication over PSTN (Public Switched Telephone Network) or wireless channel requires video signals to be encoded at the bit rate well below 64 kbits/second. Most of the current works on such very low bit rate video coding are based on H.261 or H.263 scheme. The H.263 encoding scheme, for example, consists mainly of motion estimation and compensation, discrete cosine transform, and run and variable/fixed length coding. Vector quantization (VQ) is an efficient and alternative scheme for coding at very low bit rate. One such VQ code applied to video coding is interframe hierarchical vector quantization (IHVQ). One problem of IHVQ, and VQ in general, is the computational complexity due to codebook search. A number of techniques have been proposed to reduce the search time which include tree-structured VQ, finite-state VQ, cache VQ, and hashing based codebook reorganization. In this paper, we present an IHVQ code with a hashing based scheme to reorganize the codebook so that codebook search time, and thus encoding time, can be significantly reduced. We applied the algorithm to the same test environment as in H.263 and evaluated coding performance. It turned out that the performance of the proposed scheme is significantly better than that of IHVQ without hashed codebook. Also, the performance of the proposed scheme was comparable to and often better than that of the H.263, due mainly to hashing based reorganized codebook.

  3. Spam Detection Based on a Hierarchical Self-Organizing Map

    NASA Astrophysics Data System (ADS)

    Palomo, Esteban José; Domínguez, Enrique; Luque, Rafael Marcos; Muñoz, José

    The GHSOM is an artificial neural network that has been widely used for data clustering. The hierarchical architecture of the GHSOM is more flexible than a single SOM since it is adapted to input data, mirroring inherent hierarchical relations among them. The adaptation process of the GHSOM architecture is controlled by two parameters. However, these parameters have to be established in advance and this task is not always easy. In this paper, a new hierarchical self-organizing model that has just one parameter is proposed. The performance of this model has been evaluated by building a spam detector. Experimental results confirm the goodness of this approach.

  4. ESTIMATION OF FAILURE RATES OF DIGITAL COMPONENTS USING A HIERARCHICAL BAYESIAN METHOD.

    SciTech Connect

    YUE, M.; CHU, T.L.

    2006-01-30

    One of the greatest challenges in evaluating reliability of digital I&C systems is how to obtain better failure rate estimates of digital components. A common practice of the digital component failure rate estimation is attempting to use empirical formulae to capture the impacts of various factors on the failure rates. The applicability of an empirical formula is questionable because it is not based on laws of physics and requires good data, which is scarce in general. In this study, the concept of population variability of the Hierarchical Bayesian Method (HBM) is applied to estimating the failure rate of a digital component using available data. Markov Chain Monte Carlo (MCMC) simulation is used to implement the HBM. Results are analyzed and compared by selecting different distribution types and priors distributions. Inspired by the sensitivity calculations and based on review of analytic derivations, it seems reasonable to suggest avoiding the use of gamma distribution in two-stage Bayesian analysis and HBM analysis.

  5. Hierarchical scheduling method of UAV resources for emergency surveying

    NASA Astrophysics Data System (ADS)

    Zhang, Junxiao; Zhu, Qing; Shen, Fuqiang; Miao, Shuangxi; Cao, Zhenyu; Weng, Qiqiang

    2015-12-01

    Traditional mission scheduling methods are unable to meet the timeliness requirements of emergency surveying. Different size and overlaps of different missions lead to inefficient scheduling and poor mission returns. Especially for UAVs, based on their agile and flexible ability, the scheduling result becomes diversiform; as affected by environment and unmanned aerial vehicle performance, different scheduling will lead to different time costs and mission payoffs. An effective scheduling solution is to arrange the UAVs reasonably to complete as many as missions possible with better quality and satisfaction of different demands. This paper proposes a method for mission decomposition or aggregation to generate a mission unit for specific UAVs based on the spatio-temporal constraints of different missions and UAV observation ability demands. In this way, the problems of lack or redundancy of resource scheduling, which can be caused by mission overload, various information demands and spatial overlapping will be effectively reduced. Furthermore, the global efficiency evaluation function is built by considering typical scheduling objectives, such as mission returns, priority and load balancing of resources. Then, an improved ant colony algorithm is designed to acquire an optimal scheduling scheme and the dynamic adjustment strategy is employed. Finally, the correctness and validity are demonstrated by the simulation experiment.

  6. A Biological Hierarchical Model Based Underwater Moving Object Detection

    PubMed Central

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

  7. OBIA based hierarchical image classification for industrial lake water.

    PubMed

    Uca Avci, Z D; Karaman, M; Ozelkan, E; Kumral, M; Budakoglu, M

    2014-07-15

    Water management is very important in water mining regions for the sustainability of the natural environment and for industrial activities. This study focused on Acigol Lake, which is an important wetland for sodium sulphate (Na2SO4) production, a significant natural protection area and habitat for local bird species and endemic species of this saline environment, and a stopover for migrating flamingos. By a hierarchical classification method, ponds representing the industrial part were classified according to in-situ measured Baumé values, and lake water representing the natural part was classified according to in-situ measurements of water depth. The latter is directly related to the water level, which should not exceed a critical level determined by the regulatory authorities. The resulting data, produced at an accuracy of around 80%, illustrates the status in two main regions for a single date. The output of the analysis may be meaningful for firms and environmental researchers, and authorizations can provide a good perspective for decision making for sustainable resource management in the region which has uncommon and specific ecological characteristics.

  8. A biological hierarchical model based underwater moving object detection.

    PubMed

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results.

  9. A biological hierarchical model based underwater moving object detection.

    PubMed

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

  10. The Common Prescription Patterns Based on the Hierarchical Clustering of Herb-Pairs Efficacies.

    PubMed

    Cao, Jia

    2016-01-01

    Prescription patterns are rules or regularities used to generate, recognize, or judge a prescription. Most of existing studies focused on the specific prescription patterns for diverse diseases or syndromes, while little attention was paid to the common patterns, which reflect the global view of the regularities of prescriptions. In this paper, we designed a method CPPM to find the common prescription patterns. The CPPM is based on the hierarchical clustering of herb-pair efficacies (HPEs). Firstly, HPEs were hierarchically clustered; secondly, the individual herbs are labeled by the HPEC (the clusters of HPEs); and then the prescription patterns were extracted from the combinations of HPEC; finally the common patterns are recognized statistically. The results showed that HPEs have hierarchical clustering structure. When the clustering level is 2 and the HPEs were classified into two clusters, the common prescription patterns are obvious. Among 332 candidate prescriptions, 319 prescriptions follow the common patterns. The description of the patterns is that if a prescription contains the herbs of the cluster (C 1), it is very likely to have other herbs of another cluster (C 2); while a prescription has the herbs of C 2, it may have no herbs of C 1. Finally, we discussed that the common patterns are mathematically coincident with the Blood-Qi theory.

  11. Hierarchical structure of the countries based on electricity consumption and economic growth

    NASA Astrophysics Data System (ADS)

    Kantar, Ersin; Aslan, Alper; Deviren, Bayram; Keskin, Mustafa

    2016-07-01

    We investigate the hierarchical structures of countries based on electricity consumption and economic growth by using the real amounts of their consumption over a certain time period. We use electricity consumption data to detect the topological properties of 64 countries from 1971 to 2008. These countries are divided into three clusters: low income group, middle income group and high income group countries. Firstly, a relationship between electricity consumption and economic growth is investigated by using the concept of hierarchical structure methods (minimal spanning tree (MST) and hierarchical tree (HT)). Secondly, we perform bootstrap techniques to investigate a value of the statistical reliability to the links of the MST. Finally, we use a clustering linkage procedure in order to observe the cluster structure more clearly. The results of the structural topologies of these trees are as follows: (i) we identified different clusters of countries according to their geographical location and economic growth, (ii) we found a strong relation between energy consumption and economic growth for all the income groups considered in this study and (iii) the results are in good agreement with the causal relationship between electricity consumption and economic growth.

  12. Virtual Screening and Molecular Design Based on Hierarchical Qsar Technology

    NASA Astrophysics Data System (ADS)

    Kuz'min, Victor E.; Artemenko, A. G.; Muratov, Eugene N.; Polischuk, P. G.; Ognichenko, L. N.; Liahovsky, A. V.; Hromov, A. I.; Varlamova, E. V.

    This chapter is devoted to the hierarchical QSAR technology (HiT QSAR) based on simplex representation of molecular structure (SiRMS) and its application to different QSAR/QSPR tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) of the QSAR paradigm by a series of enhanced models based on molecular structure description (in a specific order from 1D to 4D). Actually, it's a system of permanently improved solutions. Different approaches for domain applicability estimation are implemented in HiT QSAR. In the SiRMS approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality, and symmetry). The level of simplex descriptors detailed increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach presented are an ability to solve QSAR/QSPR tasks for mixtures of compounds, the absence of the "molecular alignment" problem, consideration of different physical-chemical properties of atoms (e.g., charge, lipophilicity), and the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of HiT QSAR was demonstrated by its comparison with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as the predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic, biological, etc. experiments. The HiT QSAR is realized as the suite of computer programs termed the "HiT QSAR" software that so includes powerful statistical capabilities and a number of useful utilities.

  13. A novel 3D constellation-masked method for physical security in hierarchical OFDMA system.

    PubMed

    Zhang, Lijia; Liu, Bo; Xin, Xiangjun; Liu, Deming

    2013-07-01

    This paper proposes a novel 3D constellation-masked method to ensure the physical security in hierarchical optical orthogonal frequency division multiplexing access (OFDMA) system. The 3D constellation masking is executed on the two levels of hierarchical modulation and among different OFDM subcarriers, which is realized by the masking vectors. The Lorenz chaotic model is adopted for the generation of masking vectors in the proposed scheme. A 9.85 Gb/s encrypted hierarchical QAM OFDM signal is successfully demonstrated in the experiment. The performance of illegal optical network unit (ONU) with different masking vectors is also investigated. The proposed method is demonstrated to be secure and efficient against the commonly known attacks in the experiment.

  14. Shape controlled synthesis of hierarchical nickel sulfide by the hydrothermal method.

    PubMed

    Karthikeyan, R; Navaneethan, M; Archana, J; Thangaraju, D; Arivanandhan, M; Hayakawa, Y

    2014-12-14

    Hierarchical structures of nickel sulfide have been grown by the hydrothermal method. Nickel nitrate hexahydrate and thiourea were used as precursor materials to synthesize nickel sulfide. Ethylenediaminetetraacetic acid was used as a capping agent to achieve monodispersity. The different phases of nickel sulfide and its dependency on the precursor concentration were analyzed by X-ray diffractometry. Transmission electron microscopy analysis was used to confirm the phase changes and morphological behavior of the synthesized material. The morphological evolution of the hierarchical structure formation was studied systematically by scanning electron microscopy. In this study, we explore a novel method to control the synthesis of nickel sulfide hierarchical structures by varying the precursor concentration. The two mixed phases enhanced the catalytic activity in the 4-nitro phenol reduction reaction. PMID:25338309

  15. Vehicle detection based on visual saliency and deep sparse convolution hierarchical model

    NASA Astrophysics Data System (ADS)

    Cai, Yingfeng; Wang, Hai; Chen, Xiaobo; Gao, Li; Chen, Long

    2016-07-01

    Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification. These types of methods generally have high processing times and low vehicle detection performance. To address this issue, a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed. A visual saliency calculation is firstly used to generate a small vehicle candidate area. The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection. The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group, which outperforms the existing state-of-the-art algorithms. More importantly, high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

  16. Vehicle detection based on visual saliency and deep sparse convolution hierarchical model

    NASA Astrophysics Data System (ADS)

    Cai, Yingfeng; Wang, Hai; Chen, Xiaobo; Gao, Li; Chen, Long

    2016-06-01

    Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification. These types of methods generally have high processing times and low vehicle detection performance. To address this issue, a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed. A visual saliency calculation is firstly used to generate a small vehicle candidate area. The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection. The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group, which outperforms the existing state-of-the-art algorithms. More importantly, high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

  17. Hierarchical Grid-based Multi-People Tracking-by-Detection With Global Optimization.

    PubMed

    Chen, Lili; Wang, Wei; Panin, Giorgio; Knoll, Alois

    2015-11-01

    We present a hierarchical grid-based, globally optimal tracking-by-detection approach to track an unknown number of targets in complex and dense scenarios, particularly addressing the challenges of complex interaction and mutual occlusion. Frame-by-frame detection is performed by hierarchical likelihood grids, matching shape templates through a fast oriented distance transform. To allow recovery from misdetections, common heuristics such as nonmaxima suppression within observations is eschewed. Within a discretized state-space, the data association problem is formulated as a grid-based network flow model, resulting in a convex problem casted into an integer linear programming form, giving a global optimal solution. In addition, we show how a behavior cue (body orientation) can be integrated into our association affinity model, providing valuable hints for resolving ambiguities between crossing trajectories. Unlike traditional motion-based approaches, we estimate body orientation by a hybrid methodology, which combines the merits of motion-based and 3D appearance-based orientation estimation, thus being capable of dealing also with still-standing or slowly moving targets. The performance of our method is demonstrated through experiments on a large variety of benchmark video sequences, including both indoor and outdoor scenarios.

  18. Gaussian Process Regression-Based Video Anomaly Detection and Localization With Hierarchical Feature Representation.

    PubMed

    Cheng, Kai-Wen; Chen, Yie-Tarng; Fang, Wen-Hsien

    2015-12-01

    This paper presents a hierarchical framework for detecting local and global anomalies via hierarchical feature representation and Gaussian process regression (GPR) which is fully non-parametric and robust to the noisy training data, and supports sparse features. While most research on anomaly detection has focused more on detecting local anomalies, we are more interested in global anomalies that involve multiple normal events interacting in an unusual manner, such as car accidents. To simultaneously detect local and global anomalies, we cast the extraction of normal interactions from the training videos as a problem of finding the frequent geometric relations of the nearby sparse spatio-temporal interest points (STIPs). A codebook of interaction templates is then constructed and modeled using the GPR, based on which a novel inference method for computing the likelihood of an observed interaction is also developed. Thereafter, these local likelihood scores are integrated into globally consistent anomaly masks, from which anomalies can be succinctly identified. To the best of our knowledge, it is the first time GPR is employed to model the relationship of the nearby STIPs for anomaly detection. Simulations based on four widespread datasets show that the new method outperforms the main state-of-the-art methods with lower computational burden. PMID:26394423

  19. Hierarchically structured carbon-based composites: Design, synthesis and their application in electrochemical capacitors.

    PubMed

    Yuan, C Z; Gao, B; Shen, L F; Yang, S D; Hao, L; Lu, X J; Zhang, F; Zhang, L J; Zhang, X G

    2011-02-01

    This feature article provides an overview of the recent research progress on the hierarchically structured carbon-based composites for electrochemical capacitors. The basic principles of electrochemical capacitors, and the design, construction and performance of hierarchically structured carbon-based composites electrode materials with good ions and electron transportation and large specific surface area are discussed. The trend of future development of high-power and large-energy electrochemical capacitors is proposed.

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

    NASA Astrophysics Data System (ADS)

    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.

  1. Protein structure prediction using a docking-based hierarchical folding scheme.

    PubMed

    Kifer, Ilona; Nussinov, Ruth; Wolfson, Haim J

    2011-06-01

    The pathways by which proteins fold into their specific native structure are still an unsolved mystery. Currently, many methods for protein structure prediction are available, and most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations toward each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method's abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the template-based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for template-based structure prediction, and in particular, the docking-basedranking technique presented here can be incorporated into any profile-profile comparison based method. PMID:21445943

  2. Hierarchical Vision-based Algorithm for Vehicle Model Type Recognition from Time-sequence Road Images

    NASA Astrophysics Data System (ADS)

    Zheng, Mingxie; Gotoh, Toshiyuki; Shiohara, Morito

    This paper describes a vision-based algorithm for recognizing the vehicle model type from time-sequence road images. Many types of vehicle models are offered commercially, and some of them are resemble in shape. This prevents us to discriminate their model types from the others easily. To solve these problems, we proposes a hierarchical recognition method with training process, in which the resemble model groups are firstly generated and the effective features to discriminate the models in the each group are then selected using the subspace method in training. In the recognition process, a front area is firstly detected from each frame of the input time-sequence images, then a hierarchical recognition which consists of a group and a category discrimination is performed. Finally, the results of frame recognition are integrated to realize stable recognition. The experimental results using time-sequence road images show the proposed method is effective: the recognition rate for the registered model types is more than 99%, and the rejection rate for unregistered vehicle type is more than 92%.

  3. Calculation of correlated initial state in the hierarchical equations of motion method using an imaginary time path integral approach

    SciTech Connect

    Song, Linze; Shi, Qiang

    2015-11-21

    Based on recent findings in the hierarchical equations of motion (HEOM) for correlated initial state [Y. Tanimura, J. Chem. Phys. 141, 044114 (2014)], we propose a new stochastic method to obtain the initial conditions for the real time HEOM propagation, which can be used further to calculate the equilibrium correlation functions and symmetrized correlation functions. The new method is derived through stochastic unraveling of the imaginary time influence functional, where a set of stochastic imaginary time HEOM are obtained. The validity of the new method is demonstrated using numerical examples including the spin-Boson model, and the Holstein model with undamped harmonic oscillator modes.

  4. Calculation of correlated initial state in the hierarchical equations of motion method using an imaginary time path integral approach.

    PubMed

    Song, Linze; Shi, Qiang

    2015-11-21

    Based on recent findings in the hierarchical equations of motion (HEOM) for correlated initial state [Y. Tanimura, J. Chem. Phys. 141, 044114 (2014)], we propose a new stochastic method to obtain the initial conditions for the real time HEOM propagation, which can be used further to calculate the equilibrium correlation functions and symmetrized correlation functions. The new method is derived through stochastic unraveling of the imaginary time influence functional, where a set of stochastic imaginary time HEOM are obtained. The validity of the new method is demonstrated using numerical examples including the spin-Boson model, and the Holstein model with undamped harmonic oscillator modes. PMID:26590526

  5. Protein Structure Prediction using a Docking-based Hierarchical Folding scheme

    PubMed Central

    Kifer, Ilona; Nussinov, Ruth; Wolfson, Haim J.

    2011-01-01

    The pathways by which proteins fold into their specific native structure is still an unsolved mystery. Currently many methods for protein structure prediction are available, most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently-folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations towards each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method’s abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the Template-Based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for Template-Based structure prediction, and in particular, the docking-based ranking technique presented here can be incorporated into any profile-profile comparison based method. PMID:21445943

  6. A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning

    NASA Astrophysics Data System (ADS)

    Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei

    2013-03-01

    In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.

  7. A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning

    NASA Astrophysics Data System (ADS)

    Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei

    2012-04-01

    In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.

  8. Replanning Using Hierarchical Task Network and Operator-Based Planning

    NASA Technical Reports Server (NTRS)

    Wang, X.; Chien, S.

    1997-01-01

    In order to scale-up to real-world problems, planning systems must be able to replan in order to deal with changes in problem context. In this paper we describe hierarchical task network and operatorbased re-planning techniques which allow adaptation of a previous plan to account for problems associated with executing plans in real-world domains with uncertainty, concurrency, changing objectives.

  9. Low energy isomers of (H{sub 2}O){sub 25} from a hierarchical method based on Monte Carlo temperature basin paving and molecular tailoring approaches benchmarked by MP2 calculations

    SciTech Connect

    Sahu, Nityananda; Gadre, Shridhar R. E-mail: sotiris.xantheas@pnnl.gov; Rakshit, Avijit; Bandyopadhyay, Pradipta; Miliordos, Evangelos; Xantheas, Sotiris S. E-mail: sotiris.xantheas@pnnl.gov

    2014-10-28

    We report new global minimum candidate structures for the (H{sub 2}O){sub 25} cluster that are lower in energy than the ones reported previously and correspond to hydrogen bonded networks with 42 hydrogen bonds and an interior, fully coordinated water molecule. These were obtained as a result of a hierarchical approach based on initial Monte Carlo Temperature Basin Paving sampling of the cluster's Potential Energy Surface with the Effective Fragment Potential, subsequent geometry optimization using the Molecular Tailoring Approach with the fragments treated at the second order Møller-Plesset (MP2) perturbation (MTA-MP2) and final refinement of the entire cluster at the MP2 level of theory. The MTA-MP2 optimized cluster geometries, constructed from the fragments, were found to be within <0.5 kcal/mol from the minimum geometries obtained from the MP2 optimization of the entire (H{sub 2}O){sub 25} cluster. In addition, the grafting of the MTA-MP2 energies yields electronic energies that are within <0.3 kcal/mol from the MP2 energies of the entire cluster while preserving their energy rank order. Finally, the MTA-MP2 approach was found to reproduce the MP2 harmonic vibrational frequencies, constructed from the fragments, quite accurately when compared to the MP2 ones of the entire cluster in both the HOH bending and the OH stretching regions of the spectra.

  10. Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Tilton, James C.

    2012-01-01

    A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

  11. An ontology-based hierarchical semantic modeling approach to clinical pathway workflows.

    PubMed

    Ye, Yan; Jiang, Zhibin; Diao, Xiaodi; Yang, Dong; Du, Gang

    2009-08-01

    This paper proposes an ontology-based approach of modeling clinical pathway workflows at the semantic level for facilitating computerized clinical pathway implementation and efficient delivery of high-quality healthcare services. A clinical pathway ontology (CPO) is formally defined in OWL web ontology language (OWL) to provide common semantic foundation for meaningful representation and exchange of pathway-related knowledge. A CPO-based semantic modeling method is then presented to describe clinical pathways as interconnected hierarchical models including the top-level outcome flow and intervention workflow level along a care timeline. Furthermore, relevant temporal knowledge can be fully represented by combing temporal entities in CPO and temporal rules based on semantic web rule language (SWRL). An illustrative example about a clinical pathway for cesarean section shows the applicability of the proposed methodology in enabling structured semantic descriptions of any real clinical pathway.

  12. Spectral/HP Element Method With Hierarchical Reconstruction for Solving Hyperbolic Conservation Laws

    SciTech Connect

    Xu, Zhiliang; Lin, Guang

    2009-12-01

    Hierarchical reconstruction (HR) has been successfully applied to prevent oscillations in solutions computed by finite volume, discontinuous Galerkin, spectral volume schemes when solving hyperbolic conservation laws. In this paper, we demonstrate that HR can also be combined with spectral/hp element methods for solving hyperbolic conservation laws. We show that HR preserves the order of accuracy of spectral/hp element methods for smooth solutions and generate essentially non-oscillatory solution profiles for shock wave problems.

  13. Validity of the t-plot method to assess microporosity in hierarchical micro/mesoporous materials.

    PubMed

    Galarneau, Anne; Villemot, François; Rodriguez, Jeremy; Fajula, François; Coasne, Benoit

    2014-11-11

    The t-plot method is a well-known technique which allows determining the micro- and/or mesoporous volumes and the specific surface area of a sample by comparison with a reference adsorption isotherm of a nonporous material having the same surface chemistry. In this paper, the validity of the t-plot method is discussed in the case of hierarchical porous materials exhibiting both micro- and mesoporosities. Different hierarchical zeolites with MCM-41 type ordered mesoporosity are prepared using pseudomorphic transformation. For comparison, we also consider simple mechanical mixtures of microporous and mesoporous materials. We first show an intrinsic failure of the t-plot method; this method does not describe the fact that, for a given surface chemistry and pressure, the thickness of the film adsorbed in micropores or small mesopores (< 10σ, σ being the diameter of the adsorbate) increases with decreasing the pore size (curvature effect). We further show that such an effect, which arises from the fact that the surface area and, hence, the free energy of the curved gas/liquid interface decreases with increasing the film thickness, is captured using the simple thermodynamical model by Derjaguin. The effect of such a drawback on the ability of the t-plot method to estimate the micro- and mesoporous volumes of hierarchical samples is then discussed, and an abacus is given to correct the underestimated microporous volume by the t-plot method.

  14. Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization

    NASA Astrophysics Data System (ADS)

    Hui, Zhenyang; Hu, Youjian; Jin, Shuanggen; Yevenyo, Yao Ziggah

    2016-08-01

    Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract a road point cloud. Moreover, these existing methods are deficient in removing the interference of narrow roads and several attached areas (e.g., parking lot and bare ground) to main roads extraction, thereby imparting low completeness and correctness to the city road network extraction result. Aiming at resolving the key technical issues of road extraction from airborne LiDAR point clouds, this paper proposes a novel method to extract road centerlines from airborne LiDAR point clouds. The proposed approach is mainly composed of three key algorithms, namely, Skewness balancing, Rotating neighborhood, and Hierarchical fusion and optimization (SRH). The skewness balancing algorithm used for the filtering was adopted as a new method for obtaining an optimal intensity threshold such that the "pure" road point cloud can be obtained. The rotating neighborhood algorithm on the other hand was developed to remove narrow roads (corridors leading to parking lots or sidewalks), which are not the main roads to be extracted. The proposed hierarchical fusion and optimization algorithm caused the road centerlines to be unaffected by certain attached areas and ensured the road integrity as much as possible. The proposed method was tested using the Vaihingen dataset. The results demonstrated that the proposed method can effectively extract road centerlines in a complex urban environment with 91.4% correctness and 80.4% completeness.

  15. Inheritance rules for Hierarchical Metadata Based on ISO 19115

    NASA Astrophysics Data System (ADS)

    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

  16. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    PubMed

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression.

  17. Hierarchical image-based rendering using texture mapping hardware

    SciTech Connect

    Max, N

    1999-01-15

    Multi-layered depth images containing color and normal information for subobjects in a hierarchical scene model are precomputed with standard z-buffer hardware for six orthogonal views. These are adaptively selected according to the proximity of the viewpoint, and combined using hardware texture mapping to create ''reprojected'' output images for new viewpoints. (If a subobject is too close to the viewpoint, the polygons in the original model are rendered.) Specific z-ranges are selected from the textures with the hardware alpha test to give accurate 3D reprojection. The OpenGL color matrix is used to transform the precomputed normals into their orientations in the final view, for hardware shading.

  18. Hierarchical Coloured Petrinet Based Healthcare Infrastructure Interdependency Model

    NASA Astrophysics Data System (ADS)

    Nivedita, N.; Durbha, S.

    2014-11-01

    To ensure a resilient Healthcare Critical Infrastructure, understanding the vulnerabilities and analysing the interdependency on other critical infrastructures is important. To model this critical infrastructure and its dependencies, Hierarchal Coloured petri net modelling approach for simulating the vulnerability of Healthcare Critical infrastructure in a disaster situation is studied.. The model enables to analyse and understand various state changes, which occur when there is a disruption or damage to any of the Critical Infrastructure, and its cascading nature. It also enables to explore optimal paths for evacuation during the disaster. The simulation environment can be used to understand and highlight various vulnerabilities of Healthcare Critical Infrastructure during a flood disaster scenario; minimize consequences; and enable timely, efficient response.

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

    NASA Astrophysics Data System (ADS)

    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.

  20. An Investigation of Possible Hierarchical Dependency of Four Piaget-Type Tasks under Two Methods of Presentation to Third-, Fifth-, and Seventh-Grade Children.

    ERIC Educational Resources Information Center

    Phillips, Darrell Gordon

    The purpose of this study was to investigate a proposed model for the acquisition of the concept of displacement volume and to compare two methods of conservation task presentation. A 12-stage hierarchical model for the acquisition of the concept was proposed, based on four primary assumptions: (1) concept attainment can be measured by…

  1. Loss Function Based Ranking in Two-Stage, Hierarchical Models

    PubMed Central

    Lin, Rongheng; Louis, Thomas A.; Paddock, Susan M.; Ridgeway, Greg

    2009-01-01

    Performance evaluations of health services providers burgeons. Similarly, analyzing spatially related health information, ranking teachers and schools, and identification of differentially expressed genes are increasing in prevalence and importance. Goals include valid and efficient ranking of units for profiling and league tables, identification of excellent and poor performers, the most differentially expressed genes, and determining “exceedances” (how many and which unit-specific true parameters exceed a threshold). These data and inferential goals require a hierarchical, Bayesian model that accounts for nesting relations and identifies both population values and random effects for unit-specific parameters. Furthermore, the Bayesian approach coupled with optimizing a loss function provides a framework for computing non-standard inferences such as ranks and histograms. Estimated ranks that minimize Squared Error Loss (SEL) between the true and estimated ranks have been investigated. The posterior mean ranks minimize SEL and are “general purpose,” relevant to a broad spectrum of ranking goals. However, other loss functions and optimizing ranks that are tuned to application-specific goals require identification and evaluation. For example, when the goal is to identify the relatively good (e.g., in the upper 10%) or relatively poor performers, a loss function that penalizes classification errors produces estimates that minimize the error rate. We construct loss functions that address this and other goals, developing a unified framework that facilitates generating candidate estimates, comparing approaches and producing data analytic performance summaries. We compare performance for a fully parametric, hierarchical model with Gaussian sampling distribution under Gaussian and a mixture of Gaussians prior distributions. We illustrate approaches via analysis of standardized mortality ratio data from the United States Renal Data System. Results show that SEL

  2. Highly Transparent Water-Repelling Surfaces based on Biomimetic Hierarchical Structure

    NASA Astrophysics Data System (ADS)

    Wooh, Sanghyuk; Koh, Jai; Yoon, Hyunsik; Char, Kookheon

    2013-03-01

    Nature is a great source of inspiration for creating unique structures with special functions. The representative examples of water-repelling surfaces in nature, such as lotus leaves, rose petals, and insect wings, consist of an array of bumps (or long hairs) and nanoscale surface features with different dimension scales. Herein, we introduced a method of realizing multi-dimensional hierarchical structures and water-repellancy of the surfaces with different drop impact scenarios. The multi-dimensional hierarchical structures were fabricated by soft imprinting method with TiO2 nanoparticle pastes. In order to achieve the enhanced hydrophobicity, fluorinated moieties were attached to the etched surfaces to lower the surface energy. As a result, super-hydrophobic surfaces with high transparency were realized (over 176° water contact angle), and for further investigation, these hierarchical surfaces with different drop impact scenarios were characterized by varying the impact speed, drop size, and the geometry of the surfaces.

  3. Investigation of major international and Turkish companies via hierarchical methods and bootstrap approach

    NASA Astrophysics Data System (ADS)

    Kantar, E.; Deviren, B.; Keskin, M.

    2011-11-01

    We present a study, within the scope of econophysics, of the hierarchical structure of 98 among the largest international companies including 18 among the largest Turkish companies, namely Banks, Automobile, Software-hardware, Telecommunication Services, Energy and the Oil-Gas sectors, viewed as a network of interacting companies. We analyze the daily time series data of the Boerse-Frankfurt and Istanbul Stock Exchange. We examine the topological properties among the companies over the period 2006-2010 by using the concept of hierarchical structure methods (the minimal spanning tree (MST) and the hierarchical tree (HT)). The period is divided into three subperiods, namely 2006-2007, 2008 which was the year of global economic crisis, and 2009-2010, in order to test various time-windows and observe temporal evolution. We carry out bootstrap analyses to associate the value of statistical reliability to the links of the MSTs and HTs. We also use average linkage clustering analysis (ALCA) in order to better observe the cluster structure. From these studies, we find that the interactions among the Banks/Energy sectors and the other sectors were reduced after the global economic crisis; hence the effects of the Banks and Energy sectors on the correlations of all companies were decreased. Telecommunication Services were also greatly affected by the crisis. We also observed that the Automobile and Banks sectors, including Turkish companies as well as some companies from the USA, Japan and Germany were strongly correlated with each other in all periods.

  4. Superomniphobic, transparent, and antireflection surfaces based on hierarchical nanostructures.

    PubMed

    Mazumder, Prantik; Jiang, Yongdong; Baker, David; Carrilero, Albert; Tulli, Domenico; Infante, Daniel; Hunt, Andrew T; Pruneri, Valerio

    2014-08-13

    Optical surfaces that can repel both water and oil have much potential for applications in a diverse array of technologies including self-cleaning solar panels, anti-icing windows and windshields for automobiles and aircrafts, low-drag surfaces, and antismudge touch screens. By exploiting a hierarchical geometry made of two-tier nanostructures, primary nanopillars of length scale ∼ 100-200 nm superposed with secondary branching nanostructures made of nanoparticles of length scale ∼ 10-30 nm, we have achieved static contact angles of more than 170° and 160° for water and oil, respectively, while the sliding angles were lower than 4°. At the same time, with respect to the initial flat bare glass, the nanotextured surface presented significantly reduced reflection (<0.5%), increased transmission (93.8% average over the 400 to 700 nm wavelength range), and very low scattering values (about 1% haze). To the authors' knowledge, these are the highest optical performances in conjunction with superomniphobicity reported to date in the literature. The primary nanopillars are monolithically integrated in the glass surface using lithography-free metal dewetting followed by reactive ion etching,1 while the smaller and higher surface area branching structure made of secondary nanoparticles are deposited by the NanoSpray2 combustion chemical vapor deposition (CCVD).

  5. Superomniphobic, transparent, and antireflection surfaces based on hierarchical nanostructures.

    PubMed

    Mazumder, Prantik; Jiang, Yongdong; Baker, David; Carrilero, Albert; Tulli, Domenico; Infante, Daniel; Hunt, Andrew T; Pruneri, Valerio

    2014-08-13

    Optical surfaces that can repel both water and oil have much potential for applications in a diverse array of technologies including self-cleaning solar panels, anti-icing windows and windshields for automobiles and aircrafts, low-drag surfaces, and antismudge touch screens. By exploiting a hierarchical geometry made of two-tier nanostructures, primary nanopillars of length scale ∼ 100-200 nm superposed with secondary branching nanostructures made of nanoparticles of length scale ∼ 10-30 nm, we have achieved static contact angles of more than 170° and 160° for water and oil, respectively, while the sliding angles were lower than 4°. At the same time, with respect to the initial flat bare glass, the nanotextured surface presented significantly reduced reflection (<0.5%), increased transmission (93.8% average over the 400 to 700 nm wavelength range), and very low scattering values (about 1% haze). To the authors' knowledge, these are the highest optical performances in conjunction with superomniphobicity reported to date in the literature. The primary nanopillars are monolithically integrated in the glass surface using lithography-free metal dewetting followed by reactive ion etching,1 while the smaller and higher surface area branching structure made of secondary nanoparticles are deposited by the NanoSpray2 combustion chemical vapor deposition (CCVD). PMID:24988148

  6. A Hierarchical Control Architecture for a PEBB-Based ILC Marx Modulator

    SciTech Connect

    Macken, K.; Burkhart, C.; Larsen, R.; Nguyen, M.N.; Olsen, J.; /SLAC

    2011-12-15

    The idea of building power conversion systems around Power Electronic Building Blocks (PEBBs) was initiated by the U.S. Office of Naval Research in the mid 1990s. A PEBB-based design approach is advantageous in terms of power density, modularity, reliability, and serviceability. It is obvious that this approach has much appeal for pulsed power conversion including the International Linear Collider (ILC) klystron modulator application. A hierarchical control architecture has the inherent capability to support the integration of PEBBs. This has already been successfully demonstrated in a number of industrial applications in the recent past. This paper outlines the underlying concepts of a hierarchical control architecture for a PEBB-based Marx-topology ILC klystron modulator. The control in PEBB-based power conversion systems can be functionally partitioned into (three) hierarchical layers; system layer, application layer, and PEBB layer. This has been adopted here. Based on such a hierarchical partition, the interfaces are clearly identified and defined and, consequently, are easily characterised. A conceptual design of the hardware manager, executing low-level hardware oriented tasks, is detailed. In addition, the idea of prognostics is briefly discussed.

  7. Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection.

    PubMed

    Li, Zhifeng; Gong, Dihong; Li, Xuelong; Tao, Dacheng

    2016-05-01

    Aging face recognition refers to matching the same person's faces across different ages, e.g., matching a person's older face to his (or her) younger one, which has many important practical applications, such as finding missing children. The major challenge of this task is that facial appearance is subject to significant change during the aging process. In this paper, we propose to solve the problem with a hierarchical model based on two-level learning. At the first level, effective features are learned from low-level microstructures, based on our new feature descriptor called local pattern selection (LPS). The proposed LPS descriptor greedily selects low-level discriminant patterns in a way, such that intra-user dissimilarity is minimized. At the second level, higher level visual information is further refined based on the output from the first level. To evaluate the performance of our new method, we conduct extensive experiments on the MORPH data set (the largest face aging data set available in the public domain), which show a significant improvement in accuracy over the state-of-the-art methods. PMID:26930681

  8. Hierarchical flight control system synthesis for rotorcraft-based unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Shim, Hyunchul

    The Berkeley Unmanned Aerial Vehicle (UAV) research aims to design, implement, and analyze a group of autonomous intelligent UAVs and UGVs (Unmanned Ground Vehicles). The goal of this dissertation is to provide a comprehensive procedural methodology to design, implement, and test rotorcraft-based unmanned aerial vehicles (RUAVs). We choose the rotorcraft as the base platform for our aerial agents because it offers ideal maneuverability for our target scenarios such as the pursuit-evasion game. Aided by many enabling technologies such as lightweight and powerful computers, high-accuracy navigation sensors and communication devices, it is now possible to construct RUAVs capable of precise navigation and intelligent behavior by the decentralized onboard control system. Building a fully functioning RUAV requires a deep understanding of aeronautics, control theory and computer science as well as a tremendous effort for implementation. These two aspects are often inseparable and therefore equally highlighted throughout this research. The problem of multiple vehicle coordination is approached through the notion of a hierarchical system. The idea behind the proposed architecture is to build a hierarchical multiple-layer system that gradually decomposes the abstract mission objectives into the physical quantities of control input. Each RUAV incorporated into this system performs the given tasks and reports the results through the hierarchical communication channel back to the higher-level coordinator. In our research, we provide a theoretical and practical approach to build a number of RUAVs based on commercially available navigation sensors, computer systems, and radio-controlled helicopters. For the controller design, the dynamic model of the helicopter is first built. The helicopter exhibits a very complicated multi-input multi-output, nonlinear, time-varying and coupled dynamics, which is exposed to severe exogenous disturbances. This poses considerable difficulties for

  9. Photocatalytic properties of hierarchical ZnO flowers synthesized by a sucrose-assisted hydrothermal method

    NASA Astrophysics Data System (ADS)

    Lv, Wei; Wei, Bo; Xu, Lingling; Zhao, Yan; Gao, Hong; Liu, Jia

    2012-10-01

    In this work, hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. The thermogravimetric analysis/differential thermal analysis (TGA-DTA) and Fourier transform infrared spectra (FTIR) showed that sucrose acted as a complexing agent in the synthesis process and assisted combustion during annealing. Photocatalytic activity was evaluated using the degradation of organic dye methyl orange. The sucrose added ZnO flowers showed improved activity, which was mainly attributed to the better crystallinity as confirmed by X-ray photoelectron spectroscopy (XPS) analysis. The effect of sucrose amount on photocatalytic activity was also studied.

  10. Content-based audio authentication using a hierarchical patchwork watermark embedding

    NASA Astrophysics Data System (ADS)

    Gulbis, Michael; Müller, Erika

    2010-05-01

    of the watermark method to overcome the limitations given by the feature extraction. The approach is a recursive application of the patchwork algorithm onto its own patches, with a modified patch selection to ensure a better signal to noise ratio for the watermark embedding. The robustness evaluation was done by compression (mp3, ogg, aac), normalization, and several attacks of the stirmark benchmark for audio suite. Compared on the base of same payload and transparency the hierarchical approach shows improved robustness.

  11. Low crosstalk optical hierarchical authentication with a fixed random phase lock based on two beams interference

    NASA Astrophysics Data System (ADS)

    Lu, Dajiang; He, Wenqi; Peng, Xiang

    2015-09-01

    We propose a novel method to achieve the purpose of hierarchical authentication based on two beams interference. In this method, different target images indicating different authentication levels are analytically encoded into corresponding phase-only masks (phase keys) and amplitude-only masks (amplitude keys) with the help of a random phase mask, which is created in advance and acts as the fixed lock of this authentication system. For the authentication process, a legal user can obtain a specified target image at the output plane if his/her phase key, and amplitude key, which should be settled close against the fixed internal phase lock, are respectively illuminated by two coherent beams. By comparing the target image with all the standard certification images in the database, the system can thus verify the user's identity. In simple terms, this system can not only confirm the legality of a user but also distinguish his/her identity level. Moreover, in despite of the internal phase lock of this system being fixed, the crosstalk between different pairs of keys hold by different users is low. Theoretical analysis and numerical simulation are both provided to demonstrate the validity of this method.

  12. Facile one-step photolithographic method for engineering hierarchically nano/microstructured transparent superamphiphobic surfaces.

    PubMed

    Li, Tingjie; Paliy, Maxim; Wang, Xiaolong; Kobe, Brad; Lau, Woon-Ming; Yang, Jun

    2015-05-27

    It is of great value to develop a simple, controllable, and scalable method of making superamphiphobic surfaces. Here we present a facile one-step photolithographic method to engineer superamphiphobic surfaces consisting of photoresist micropillars decorated with nanoparticles of the same photoresist. The surface or coating is optically transparent and versatile, and can be fabricated on a broad range of substrates including stretchable elastomers. During the development of the micropillar array, photoresist nanoparticles are spontaneously grown on the micropillars by a well-controlled emulsification process of the un-cross-linked residual photoresist. This creates a hierarchical structure with a re-entrant and convex morphology which is the key for superoleophobicity. The chemical bonding between the nanoparticles and the micropillars is strong producing a robust and durable coating. This facile method is scalable and industry-applicable for a variety of applications such as self-cleaning, antifouling, and deicing/antifrosting.

  13. A functional network estimation method of resting-state fMRI using a hierarchical Markov random field.

    PubMed

    Liu, Wei; Awate, Suyash P; Anderson, Jeffrey S; Fletcher, P Thomas

    2014-10-15

    We propose a hierarchical Markov random field model for estimating both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show that our proposed model is able to identify both group and subject functional networks with higher accuracy on synthetic data, more robustness, and inter-session consistency on the real data.

  14. A Functional Networks Estimation Method of Resting-State fMRI Using a Hierarchical Markov Random Field

    PubMed Central

    Liu, Wei; Awate, Suyash P.; Anderson, Jeffrey S.; Fletcher, P. Thomas

    2014-01-01

    We propose a hierarchical Markov random field model that estimates both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show our proposed model is able to identify both group and subject functional networks with higher accuracy, more robustness, and inter-session consistency. PMID:24954282

  15. Hierarchical model-based tracking of cervical vertebrae from dynamic biplane radiographs.

    PubMed

    Haque, Md Abedul; Anderst, William; Tashman, Scott; Marai, G Elisabeta

    2013-07-01

    We present a novel approach for automatically, accurately and reliably determining the 3D motion of the cervical spine from a series of stereo or biplane radiographic images. These images could be acquired through a variety of different imaging hardware configurations. We follow a hierarchical, anatomically-aware, multi-bone approach that takes into account the complex structure of cervical vertebrae and inter-vertebrae overlapping, as well as the temporal coherence in the imaging series. These significant innovations improve the speed, accuracy, reliability and flexibility of the tracking process. Evaluation on cervical data shows that the approach is as accurate (average precision 0.3 mm and 1°) as the expert human-operator driven method that was previously state of the art. However, unlike the previously used method, the hierarchical approach is automatic and robust; even in the presence of implanted hardware. Therefore, the method has solid potential for clinical use to evaluate the effectiveness of surgical interventions.

  16. Chelating agent-free, vapor-assisted crystallization method to synthesize hierarchical microporous/mesoporous MIL-125 (Ti).

    PubMed

    McNamara, Nicholas D; Hicks, Jason C

    2015-03-11

    Titanium-based microporous heterogeneous catalysts are widely studied but are often limited by the accessibility of reactants to active sites. Metal-organic frameworks (MOFs), such as MIL-125 (Ti), exhibit enhanced surface areas due to their high intrinsic microporosity, but the pore diameters of most microporous MOFs are often too small to allow for the diffusion of larger reactants (>7 Å) relevant to petroleum and biomass upgrading. In this work, hierarchical microporous MIL-125 exhibiting significantly enhanced interparticle mesoporosity was synthesized using a chelating-free, vapor-assisted crystallization method. The resulting hierarchical MOF was examined as an active catalyst for the oxidation of dibenzothiophene (DBT) with tert-butyl hydroperoxide and outperformed the solely microporous analogue. This was attributed to greater access of the substrate to surface active sites, as the pores in the microporous analogues were of inadequate size to accommodate DBT. Moreover, thiophene adsorption studies suggested the mesoporous MOF contained larger amounts of unsaturated metal sites that could enhance the observed catalytic activity. PMID:25695286

  17. Facile method for preparing superoleophobic surfaces with hierarchical microcubic/nanowire structures

    NASA Astrophysics Data System (ADS)

    Kwak, Wonshik; Hwang, Woonbong

    2016-02-01

    To facilitate the fabrication of superoleophobic surfaces having hierarchical microcubic/nanowire structures (HMNS), even for low surface tension liquids including octane (surface tension = 21.1 mN m-1), and to understand the influences of surface structures on the oleophobicity, we developed a convenient method to achieve superoleophobic surfaces on aluminum substrates using chemical acid etching, anodization and fluorination treatment. The liquid repellency of the structured surface was validated through observable experimental results the contact and sliding angle measurements. The etching condition required to ensure high surface roughness was established, and an optimal anodizing condition was determined, as a critical parameter in building the superoleophobicity. The microcubic structures formed by acid etching are essential for achieving the formation of the hierarchical structure, and therefore, the nanowire structures formed by anodization lead to an enhancement of the superoleophobicity for low surface tension liquids. Under optimized morphology by microcubic/nanowire structures with fluorination treatment, the contact angle over 150° and the sliding angle less than 10° are achieved even for octane.

  18. Analysis of the effects of the global financial crisis on the Turkish economy, using hierarchical methods

    NASA Astrophysics Data System (ADS)

    Kantar, Ersin; Keskin, Mustafa; Deviren, Bayram

    2012-04-01

    We have analyzed the topology of 50 important Turkish companies for the period 2006-2010 using the concept of hierarchical methods (the minimal spanning tree (MST) and hierarchical tree (HT)). We investigated the statistical reliability of links between companies in the MST by using the bootstrap technique. We also used the average linkage cluster analysis (ALCA) technique to observe the cluster structures much better. The MST and HT are known as useful tools to perceive and detect global structure, taxonomy, and hierarchy in financial data. We obtained four clusters of companies according to their proximity. We also observed that the Banks and Holdings cluster always forms in the centre of the MSTs for the periods 2006-2007, 2008, and 2009-2010. The clusters match nicely with their common production activities or their strong interrelationship. The effects of the Automobile sector increased after the global financial crisis due to the temporary incentives provided by the Turkish government. We find that Turkish companies were not very affected by the global financial crisis.

  19. Hierarchical decomposition of burn body diagram based on cutaneous functional units and its utility.

    PubMed

    Richard, Reg; Jones, John A; Parshley, Philip

    2015-01-01

    A burn body diagram (BBD) is a common feature used in the delivery of burn care for estimating the TBSA burn as well as calculating fluid resuscitation and nutritional requirements, wound healing, and rehabilitation intervention. However, little change has occurred for over seven decades in the configuration of the BBD. The purpose of this project was to develop a computerized model using hierarchical decomposition (HD) to more precisely determine the percentage burn within a BBD based on cutaneous functional units (CFUs). HD is a process by which a system is degraded into smaller parts that are more precise in their use. CFUs were previously identified fields of the skin involved in the range of motion. A standard Lund/Browder (LB) BBD template was used as the starting point to apply the CFU segments. LB body divisions were parceled down into smaller body area divisions through a HD process based on the CFU concept. A numerical pattern schema was used to label the various segments in a cephalo/caudal, anterior/posterior, medial/lateral manner. Hand/fingers were divided based on anatomical landmarks and known cutaneokinematic function. The face was considered using aesthetic units. Computer code was written to apply the numeric hierarchical schema to CFUs and applied within the context of the surface area graphic evaluation BBD program. Each segmented CFU was coded to express 100% of itself. The CFU/HD method refined the standard LB diagram from 13 body segments and 33 subdivisions into 182 isolated CFUs. Associated CFUs were reconstituted into 219 various surface area combinations totaling 401 possible surface segments. The CFU/HD schema of the body surface mapping is applicable to measuring and calculating percent wound healing in a more precise manner. It eliminates subjective assessment of the percentage wound healing and the need for additional devices such as planimetry. The development of CFU/HD body mapping schema has rendered a technologically advanced

  20. 3D Pharmacophore, hierarchical methods, and 5-HT4 receptor binding data.

    PubMed

    Varin, Thibault; Saettel, Nicolas; Villain, Jonathan; Lesnard, Aurelien; Dauphin, François; Bureau, Ronan; Rault, Sylvain

    2008-10-01

    5-Hydroxytryptamine subtype-4 (5-HT(4)) receptors have stimulated considerable interest amongst scientists and clinicians owing to their importance in neurophysiology and potential as therapeutic targets. A comparative analysis of hierarchical methods applied to data from one thousand 5-HT(4) receptor-ligand binding interactions was carried out. The chemical structures were described as chemical and pharmacophore fingerprints. The definitions of indices, related to the quality of the hierarchies in being able to distinguish between active and inactive compounds, revealed two interesting hierarchies with the Unity (1 active cluster) and pharmacophore fingerprints (4 active clusters). The results of this study also showed the importance of correct choice of metrics as well as the effectiveness of a new alternative of the Ward clustering algorithm named Energy (Minimum E-Distance method). In parallel, the relationship between these classifications and a previously defined 3D 5-HT(4) antagonist pharmacophore was established.

  1. Synthesis of peroxo-titanium decorated H-titanate-nanotube-based hierarchical microspheres with enhanced visible-light photocatalytic activity in degradation of Rhodamine B.

    PubMed

    Qiu, Yong; Li, Xinjun

    2014-10-21

    Peroxo-titanium decorated H-titanate-nanotube-based hierarchical microspheres (PTHM) with a large surface area (368 m(2) g(-1)) and mesoporous structure were prepared by an alkaline hydrothermal method in the presence of H2O2 followed by acid wash, and they exhibited improved activity in degradation of Rhodamine B under visible light irradiation.

  2. Inferring a District-Based Hierarchical Structure of Social Contacts from Census Data

    PubMed Central

    Yu, Zhiwen; Liu, Jiming; Zhu, Xianjun

    2015-01-01

    Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual’s social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model. PMID:25679787

  3. Cryptanalysis of Chatterjee-Sarkar Hierarchical Identity-Based Encryption Scheme at PKC 06

    NASA Astrophysics Data System (ADS)

    Park, Jong Hwan; Lee, Dong Hoon

    In 2006, Chatterjee and Sarkar proposed a hierarchical identity-based encryption (HIBE) scheme which can support an unbounded number of identity levels. This property is particularly useful in providing forward secrecy by embedding time components within hierarchical identities. In this paper we show that their scheme does not provide the claimed property. Our analysis shows that if the number of identity levels becomes larger than the value of a fixed public parameter, an unintended receiver can reconstruct a new valid ciphertext and decrypt the ciphertext using his or her own private key. The analysis is similarly applied to a multi-receiver identity-based encryption scheme presented as an application of Chatterjee and Sarkar's HIBE scheme.

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

    USGS Publications Warehouse

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

    2011-01-01

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

  5. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    NASA Astrophysics Data System (ADS)

    Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

    2015-11-01

    In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of

  6. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    NASA Astrophysics Data System (ADS)

    Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

    2015-07-01

    In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor

  7. A Medical Cloud-Based Platform for Respiration Rate Measurement and Hierarchical Classification of Breath Disorders

    PubMed Central

    Fekr, Atena Roshan; Janidarmian, Majid; Radecka, Katarzyna; Zilic, Zeljko

    2014-01-01

    The measurement of human respiratory signals is crucial in cyberbiological systems. A disordered breathing pattern can be the first symptom of different physiological, mechanical, or psychological dysfunctions. Therefore, a real-time monitoring of the respiration patterns, as well as respiration rate is a critical need in medical applications. There are several methods for respiration rate measurement. However, despite their accuracy, these methods are expensive and could not be integrated in a body sensor network. In this work, we present a real-time cloud-based platform for both monitoring the respiration rate and breath pattern classification, remotely. The proposed system is designed particularly for patients with breathing problems (e.g., respiratory complications after surgery) or sleep disorders. Our system includes calibrated accelerometer sensor, Bluetooth Low Energy (BLE) and cloud-computing model. We also suggest a procedure to improve the accuracy of respiration rate for patients at rest positions. The overall error in the respiration rate calculation is obtained 0.53% considering SPR-BTA spirometer as the reference. Five types of respiration disorders, Bradapnea, Tachypnea, Cheyn-stokes, Kaussmal, and Biot's breathing are classified based on hierarchical Support Vector Machine (SVM) with seven different features. We have evaluated the performance of the proposed classification while it is individualized to every subject (case 1) as well as considering all subjects (case 2). Since the selection of kernel function is a key factor to decide SVM's performance, in this paper three different kernel functions are evaluated. The experiments are conducted with 11 subjects and the average accuracy of 94.52% for case 1 and the accuracy of 81.29% for case 2 are achieved based on Radial Basis Function (RBF). Finally, a performance evaluation has been done for normal and impaired subjects considering sensitivity, specificity and G-mean parameters of different kernel

  8. A medical cloud-based platform for respiration rate measurement and hierarchical classification of breath disorders.

    PubMed

    Fekr, Atena Roshan; Janidarmian, Majid; Radecka, Katarzyna; Zilic, Zeljko

    2014-06-24

    The measurement of human respiratory signals is crucial in cyberbiological systems. A disordered breathing pattern can be the first symptom of different physiological, mechanical, or psychological dysfunctions. Therefore, a real-time monitoring of the respiration patterns, as well as respiration rate is a critical need in medical applications. There are several methods for respiration rate measurement. However, despite their accuracy, these methods are expensive and could not be integrated in a body sensor network. In this work, we present a real-time cloud-based platform for both monitoring the respiration rate and breath pattern classification, remotely. The proposed system is designed particularly for patients with breathing problems (e.g., respiratory complications after surgery) or sleep disorders. Our system includes calibrated accelerometer sensor, Bluetooth Low Energy (BLE) and cloud-computing model. We also suggest a procedure to improve the accuracy of respiration rate for patients at rest positions. The overall error in the respiration rate calculation is obtained 0.53% considering SPR-BTA spirometer as the reference. Five types of respiration disorders, Bradapnea, Tachypnea, Cheyn-stokes, Kaussmal, and Biot's breathing are classified based on hierarchical Support Vector Machine (SVM) with seven different features. We have evaluated the performance of the proposed classification while it is individualized to every subject (case 1) as well as considering all subjects (case 2). Since the selection of kernel function is a key factor to decide SVM's performance, in this paper three different kernel functions are evaluated. The experiments are conducted with 11 subjects and the average accuracy of 94.52% for case 1 and the accuracy of 81.29% for case 2 are achieved based on Radial Basis Function (RBF). Finally, a performance evaluation has been done for normal and impaired subjects considering sensitivity, specificity and G-mean parameters of different kernel

  9. A nanotectonics approach to produce hierarchically organized bioactive glass nanoparticles-based macrospheres.

    PubMed

    Luz, Gisela M; Mano, João F

    2012-10-21

    Bioactive particles have been widely used in a series of biomedical applications due to their ability to promote bone-bonding and elicit favorable biological responses in therapies associated with the replacement and regeneration of mineralized tissues. In this work hierarchical architectures are prepared by an innovative methodology using SiO(2)-CaO sol-gel based nanoparticles. Inspired by colloidal crystals, spherical aggregates were formed on biomimetic superhydrophobic surfaces using bioactive glass nanoparticles (BG-NPs) able to promote bone regeneration. A highly ordered organization, a common feature of mineralized structures in Nature, was achieved at both nano- and microlevels, being the crystallization degree of the structures controlled by the evaporation rates taking place at room temperature (RT) or at 4 °C. The crystallization degree of the structures influenced the Ca/P ratio of the apatitic film formed at their surface, after 7 days of immersion in SBF. This allows the regulation of bioactive properties and the ability to release potential additives that could be also incorporated in such particles with a high efficiency. Such a versatile method to produce bioactive particles with controlled size and internal structure could open new possibilities in designing new spherical devices for orthopaedic applications, including tissue engineering.

  10. A nanotectonics approach to produce hierarchically organized bioactive glass nanoparticles-based macrospheres

    NASA Astrophysics Data System (ADS)

    Luz, Gisela M.; Mano, João F.

    2012-09-01

    Bioactive particles have been widely used in a series of biomedical applications due to their ability to promote bone-bonding and elicit favorable biological responses in therapies associated with the replacement and regeneration of mineralized tissues. In this work hierarchical architectures are prepared by an innovative methodology using SiO2-CaO sol-gel based nanoparticles. Inspired by colloidal crystals, spherical aggregates were formed on biomimetic superhydrophobic surfaces using bioactive glass nanoparticles (BG-NPs) able to promote bone regeneration. A highly ordered organization, a common feature of mineralized structures in Nature, was achieved at both nano- and microlevels, being the crystallization degree of the structures controlled by the evaporation rates taking place at room temperature (RT) or at 4 °C. The crystallization degree of the structures influenced the Ca/P ratio of the apatitic film formed at their surface, after 7 days of immersion in SBF. This allows the regulation of bioactive properties and the ability to release potential additives that could be also incorporated in such particles with a high efficiency. Such a versatile method to produce bioactive particles with controlled size and internal structure could open new possibilities in designing new spherical devices for orthopaedic applications, including tissue engineering.

  11. GDS-based Mask Data Preparation Flow: Data Volume Containment by Hierarchical Data Processing

    NASA Astrophysics Data System (ADS)

    Schulze, Steffen F.; LaCour, Pat; Buck, Peter D.

    2002-12-01

    As the industry enters the development of the 65nm node the pressure on the data path and tapeout flow is growing. Design complexity and increased deployment of resolution enhancement techniques (RET) result in rapidly growing file sizes, which turns what used to be the relatively simple task of mask data preparation into a real bottleneck. This discussion introduces the data preparation scheme in the mask house and analyzes its evolution. Mask data preparation (MDP) has evolved from a flow that only needed to support a single mask lithography tool data format (MEBES) with minimal data alteration steps to one which requires the support of many mask lithography tool data formats and at the same time requires significant data alteration to support the increased precision necessary for today"s advanced masks.. However, the MDP flow developed around the MEBES format and it"s derivatives still exists. The design community has migrated towards the use of hierarchical data formats and processes to control file size and processing time. MDP, which from a file size and process complexity point of view is beginning to look more and more like the advanced RET operations performed on the data prior to mask manufacturing, is still standardized on a flat data format that is poorly optimized for a growing number of mask lithography tools. Based on examples it will be shown how this complicates the data handling further. An alternate data preparation flow accommodating the larger files and re-gaining flexibility for turnaround time (TAT) and throughput management is suggested. This flow utilizes the hierarchical GDS-II format as the exchange format for mask data preparation. It complements the existing flow for the most complex designs. The introduction of a hierarchical exchange format enables the transfer of a number of necessary data preparation steps into the hierarchical domain. Data processing strategies are discussed. The paper illustrates the benefit of hierarchical

  12. A facile method to fabricate porous Co{sub 3}O{sub 4} hierarchical microspheres

    SciTech Connect

    Cheng, J.P. Chen, X.; Ma, R.; Liu, F.; Zhang, X.B.

    2011-08-15

    Flower-like Co{sub 3}O{sub 4} hierarchical microspheres composed of self-assembled porous nanoplates have been prepared by a two-step method without employing templates. The first step involves the synthesis of flower-like Co(OH){sub 2} microspheres by a solution route at low temperatures. The second step includes the calcination of the as-prepared Co(OH){sub 2} microspheres at 200 deg. C for 1 h, causing their decomposition to form porous Co{sub 3}O{sub 4} microspheres without destruction of their original morphology. The samples were characterized by scanning electron microscope, transmission electron microscope, X-ray diffractormeter and Fourier transform infrared spectroscope. Some experimental factors including solution temperature and surfactant on the morphologies of the final products have been investigated. The magnetic properties of Co{sub 3}O{sub 4} microspheres were also investigated. - Graphical Abstract: Flower-like Co{sub 3}O{sub 4} microspheres are composed of self-assembled nanoplates and these nanoplates appear to be closely packed in the microspheres. These nanoplates consist of a large number of nanocrystallites less than 5 nm in size with a porous structure, in which the connection between nanocrystallites is random. Research Highlights: {yields} Flower-like Co{sub 3}O{sub 4} hierarchical microspheres composed of self-assembled porous nanoplates have been prepared by a two-step method without employing templates. {yields} Layered Co(OH){sub 2} microspheres were prepared with an appropriate approach under low temperatures for 1 h reaction. {yields} Calcination caused Co(OH){sub 2} decomposition to form porous Co{sub 3}O{sub 4} microspheres without destruction of their original morphology.

  13. A method of spherical harmonic analysis in the geosciences via hierarchical Bayesian inference

    NASA Astrophysics Data System (ADS)

    Muir, J. B.; Tkalčić, H.

    2015-11-01

    The problem of decomposing irregular data on the sphere into a set of spherical harmonics is common in many fields of geosciences where it is necessary to build a quantitative understanding of a globally varying field. For example, in global seismology, a compressional or shear wave speed that emerges from tomographic images is used to interpret current state and composition of the mantle, and in geomagnetism, secular variation of magnetic field intensity measured at the surface is studied to better understand the changes in the Earth's core. Optimization methods are widely used for spherical harmonic analysis of irregular data, but they typically do not treat the dependence of the uncertainty estimates on the imposed regularization. This can cause significant difficulties in interpretation, especially when the best-fit model requires more variables as a result of underestimating data noise. Here, with the above limitations in mind, the problem of spherical harmonic expansion of irregular data is treated within the hierarchical Bayesian framework. The hierarchical approach significantly simplifies the problem by removing the need for regularization terms and user-supplied noise estimates. The use of the corrected Akaike Information Criterion for picking the optimal maximum degree of spherical harmonic expansion and the resulting spherical harmonic analyses are first illustrated on a noisy synthetic data set. Subsequently, the method is applied to two global data sets sensitive to the Earth's inner core and lowermost mantle, consisting of PKPab-df and PcP-P differential traveltime residuals relative to a spherically symmetric Earth model. The posterior probability distributions for each spherical harmonic coefficient are calculated via Markov Chain Monte Carlo sampling; the uncertainty obtained for the coefficients thus reflects the noise present in the real data and the imperfections in the spherical harmonic expansion.

  14. Excellent Humidity Sensor Based on LiCl Loaded Hierarchically Porous Polymeric Microspheres.

    PubMed

    Jiang, Kai; Zhao, Hongran; Dai, Jianxun; Kuang, Da; Fei, Teng; Zhang, Tong

    2016-09-28

    A catalyst-free Friedel-Crafts alkylation reaction has been developed to synthesize hierarchically porous polymeric microspheres (HPPMs) with phloroglucin and dimethoxymethane. HPPMs with uniform size were obtained and the size can be tuned by the concentration of raw materials. The chemical structure and hierarchical porous characteristic of HPPMs were characterized in detail. HPPMs were then loaded with humidity sensitive material LiCl to construct composites for humidity sensor. The optimum sensor based on 3 wt % LiCl-loaded HPPMs shows high sensitivity at the relative humidity (RH) atmosphere of 11-95%, small hysteresis, enhanced durability and rapid response. The sensitive mechanism was discussed through the investigation of complex impedance plots. PMID:27598319

  15. Integrated photonic reservoir computing based on hierarchical time-multiplexing structure.

    PubMed

    Zhang, Hong; Feng, Xue; Li, Boxun; Wang, Yu; Cui, Kaiyu; Liu, Fang; Dou, Weibei; Huang, Yidong

    2014-12-15

    An integrated photonic reservoir computing (RC) based on hierarchical time-multiplexing structure is proposed by numerical simulations. A micro-ring array (MRA) is employed as a typical time delay implementation of RC. At the output port of the MRA, a secondary time-multiplexing is achieved by multi-mode interference (MMI) splitter and delay line array. This hierarchical time-multiplexing structure can ensure a large reservoir size with fast processing speed. Simulation results indicate that the proposed RC system yields better performance than previously reported ones. The achieved normalized mean square error between the system output and target sequence are 0.5% and 2.7% for signal classification and chaotic time series prediction, respectively, while the sample rate is as high as 1.3 Gbps.

  16. A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

    NASA Technical Reports Server (NTRS)

    Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

    2012-01-01

    The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

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

    NASA Astrophysics Data System (ADS)

    Brely, Lucas; Bosia, Federico; Pugno, Nicola

    2015-07-01

    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.

  18. Hierarchical graphs for better annotations of rule-based models of biochemical systems

    SciTech Connect

    Hu, Bin; Hlavacek, William

    2009-01-01

    In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of a molecular component. A set of rules comprises a mathematical/computational model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Here, for purposes of model annotation, we propose an extension of BNGL that involves the use of hierarchical graphs to represent (1) relationships among components and subcomponents of molecules and (2) relationships among classes of reactions defined by rules. 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)/CD3 complex. Likewise, we illustrate how hierarchical graphs can be used to document the similarity of two related rules for kinase-catalyzed phosphorylation of a protein substrate. We also demonstrate how a hierarchical graph representing a protein can be encoded in an XML-based format.

  19. A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

    PubMed Central

    Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

    2013-01-01

    Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy

  20. A Subspace Pursuit-based Iterative Greedy Hierarchical solution to the neuromagnetic inverse problem.

    PubMed

    Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S; Brown, Emery N; Purdon, Patrick L

    2014-02-15

    Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy

  1. The relationship between carbon dioxide emission and economic growth: Hierarchical structure methods

    NASA Astrophysics Data System (ADS)

    Deviren, Seyma Akkaya; Deviren, Bayram

    2016-06-01

    Carbon dioxide (CO2) emission has an essential role in the current debate on sustainable development and environmental protection. CO2 emission is also directly linked with use of energy which plays a focal role both for production and consumption in the world economy. Therefore the relationship between the CO2 emission and economic growth has a significant implication for the environmental and economical policies. In this study, within the scope of sociophysics, the topology, taxonomy and relationships among the 33 countries, which have almost the high CO2 emission and economic growth values, are investigated by using the hierarchical structure methods, such as the minimal spanning tree (MST) and hierarchical tree (HT), over the period of 1970-2010. The average linkage cluster analysis (ALCA) is also used to examine the cluster structure more clearly in HTs. According to their proximity, economic ties and economic growth, different clusters of countries are identified from the structural topologies of these trees. We have found that the high income & OECD countries are closely connected to each other and are isolated from the upper middle and lower middle income countries from the MSTs, which are obtained both for the CO2 emission and economic growth. Moreover, the high income & OECD clusters are homogeneous with respect to the economic activities and economic ties of the countries. It is also mentioned that the Group of Seven (G7) countries (CAN, ENG, FRA, GER, ITA, JPN, USA) are connected to each other and these countries are located at the center of the MST for the results of CO2 emission. The same analysis may also successfully apply to the other environmental sources and different countries.

  2. A hierarchical hybrid design for high performance tin based Li-ion battery anodes.

    PubMed

    Song, Xuefeng

    2013-05-24

    Novel hierarchical hybrids, tin dioxide@carbon hollow spheres with encapsulated tin nanoparticles (SnO₂@HCS@Sn), were fabricated by combining solution and vapor phase techniques. The phase composition, morphological evolution and porosity of the hierarchical hybrids were characterized by x-ray diffraction, energy dispersive x-ray spectroscopy, scanning and transmission electron microscopy, and N₂ adsorption-desorption analysis. The significantly improved electrochemical performance of this functional material is attributed to its heterogeneous architecture which unifies hollow carbon spheres with tin nanoparticles with a diameter of less than 20 nm, which are further conformally covered by ultra-small tin dioxide nanoplates. The ultrathin SnO₂ nanoplates grown on the carbon spheres effectively increase the charge-transfer properties and shorten the transport lengths for both electrons and lithium ions. The mesoporous carbon spheres offer excellent conductivity and abundant void space to buffer the large volume change during cycling. High initial capacity (∼1766 mAh g⁻¹ at 0.1 Ag⁻¹), high initial Coulombic efficiency (56.4%), and long cycle life (100 cycles with ∼710 mAh g⁻¹) have been realized in the hierarchical hybrid tin-based anodes.

  3. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    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.

  4. Hierarchical development of three direct-design methods for two-dimensional axial-turbomachinery cascades

    SciTech Connect

    Korakianitis, T. )

    1993-04-01

    The direct and inverse blade-design iterations for the selection of isolated airfoils and gas turbine blade cascades are enormously reduced if the initial blade shape has performance characteristics near the desirable ones. This paper presents the hierarchical development of three direct blade-design methods of increasing utility for generating two-dimensional blade shapes. The methods can be used to generate inputs to the direct- or inverse-blade-design sequences for subsonic or supersonic airfoils for compressors and turbines, or isolated airfoils. The first method specifies the airfoil shapes with analytical polynomials. It shows that continuous curvature and continuous slope of curvature are necessary conditions to minimize the possibility of flow separation, and to lead to improved blade designs. The second method specifies the airfoil shapes with parametric fourth-order polynomials, which result in continuous-slope-of-curvature airfoils, with smooth Mach number and pressure distributions. This method is time consuming. The third method specifies the airfoil shapes by using a mixture of analytical polynomials and mapping the airfoil surfaces from a desirable curvature distribution. The third method provides blade surfaces with desirable performance in very few direct-design iterations. In all methods the geometry near the leading edge is specified by a thickness distribution added to a construction line, which eliminates the leading edge overspeed and laminar-separation regions. The blade-design methods presented in this paper can be used to improve the aerodynamic and heat transfer performance of turbomachinery cascades, and they can result in high-performance airfoils in very few iterations.

  5. A Study on Brain Mapping Technique Based on Hierarchical Decomposition Analysis

    NASA Astrophysics Data System (ADS)

    Oura, Kunihiko

    In this paper, brain functional mapping method by hierarchical decomposition analysis (HDA) is proposed. HDA is one of the multi-dimensional AR modeling methods and well-known for its validity to detect temporal lobe seizures. The author transforms the estimated AR model in the form of transfer function from the inner blood flow signal to the cerebral cortex. The signal for HDA is oxidized hemoglobin density HbO, which is measured by near infrared spectroscopy (NIRS). Comparing the 2 tasks which use arithmetic sense, the difference of brain activity becomes clear by proposed technique.

  6. Transparent, 3-dimensional light-collected, and flexible fiber-type dye-sensitized solar cells based on highly ordered hierarchical anatase TiO2 nanorod arrays

    NASA Astrophysics Data System (ADS)

    Liang, Jia; Zhang, Gengmin; Yin, Jianbo; Yang, Yingchao

    2014-12-01

    Two kinds of hierarchical anatase TiO2 structures are synthesized by a facile hydrothermal method in this report. A new transparent, 3D light-collected, and flexible fiber-type dye-sensitized solar cell (FF-DSSC) with such hierarchical TiO2 structures is developed. The conversion efficiency of the FF-DSSC based on a TiCl4-treated TiO2 nanorod array (hierarchical structure I) exhibits about 4 times higher than that based on a HCl-treated TiO2 nanorod array, and further rises to 4.4% when the TiCl4-treated TiO2 nanorod array is treated in a mixed solution of (NH4)2TiF6 and H3BO3 three times (hierarchical structure II). The obvious enhancement in conversion efficiency can be ascribed to the dye adsorption promotion benefiting from their hierarchical structures. Beyond the attractive conversion efficiency, the new designed FF-DSSC possesses several advantages including good flexibility, excellent stability, and 3D light-collection. The conversion efficiencies of the FF-DSSCs can still keep 85%-90% even the FF-DSSCs are bent for 1000 times. The maximum power outputs of the FF-DSSCs characterized by Diffuse Illumination Mode using home-made Al reflector exhibit about 3 times higher than that done by Standard Illumination Mode due to 3D light-collections. The FF-DSSCs based on highly ordered hierarchical anatase TiO2 nanorod arrays hold great promise in future energy harvest.

  7. Genetic Network Inference Using Hierarchical Structure

    PubMed Central

    Kimura, Shuhei; Tokuhisa, Masato; Okada-Hatakeyama, Mariko

    2016-01-01

    Many methods for inferring genetic networks have been proposed, but the regulations they infer often include false-positives. Several researchers have attempted to reduce these erroneous regulations by proposing the use of a priori knowledge about the properties of genetic networks such as their sparseness, scale-free structure, and so on. This study focuses on another piece of a priori knowledge, namely, that biochemical networks exhibit hierarchical structures. Based on this idea, we propose an inference approach that uses the hierarchical structure in a target genetic network. To obtain a reasonable hierarchical structure, the first step of the proposed approach is to infer multiple genetic networks from the observed gene expression data. We take this step using an existing method that combines a genetic network inference method with a bootstrap method. The next step is to extract a hierarchical structure from the inferred networks that is consistent with most of the networks. Third, we use the hierarchical structure obtained to assign confidence values to all candidate regulations. Numerical experiments are also performed to demonstrate the effectiveness of using the hierarchical structure in the genetic network inference. The improvement accomplished by the use of the hierarchical structure is small. However, the hierarchical structure could be used to improve the performances of many existing inference methods. PMID:26941653

  8. Hierarchical image enhancement

    NASA Astrophysics Data System (ADS)

    Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa

    2016-05-01

    Image enhancement is an important technique in computer vision. In this paper, we propose a hierarchical image enhancement approach based on the structure layer and texture layer. In the structure layer, we propose a structure-based method based on GMM, which better exploits structure details with fewer noise. In the texture layer, we present a structure-filtering method to filter unwanted texture with keeping completeness of detected salient structure. Next, we introduce a structure constraint prior to integrate them, leading to an improved enhancement result. Extensive experiments demonstrate that the proposed approach achieves higher quality results than previous approaches.

  9. Recombination reduction on lead halide perovskite solar cells based on low temperature synthesized hierarchical TiO₂ nanorods.

    PubMed

    Jaramillo-Quintero, Oscar A; Solís de la Fuente, Mauricio; Sanchez, Rafael S; Recalde, Ileana B; Juarez-Perez, Emilio J; Rincón, Marina E; Mora-Seró, Iván

    2016-03-28

    Intensive research on the electron transport material (ETM) has been pursued to improve the efficiency of perovskite solar cells (PSCs) and decrease their cost. More importantly, the role of the ETM layer is not yet fully understood, and research on new device architectures is still needed. Here, we report the use of three-dimensional (3D) TiO2 with a hierarchical architecture based on rutile nanorods (NR) as photoanode material for PSCs. The proposed hierarchical nanorod (HNR) films were synthesized by a two-step low temperature (180 °C) hydrothermal method, and consist of TiO2 nanorod trunks with optimal lengths of 540 nm and TiO2 nanobranches with lengths of 45 nm. Different device configurations were fabricated with TiO2 structures (compact layer, NR and HNR) and CH3NH3PbI3, using different synthetic routes, as the active material. PSCs based on HNR-CH3NH3PbI3 achieved the highest power conversion efficiency compared to PSCs with other TiO2 structures. This result can be ascribed mainly to lower charge recombination as determined by impedance spectroscopy. Furthermore, we have observed that the CH3NH3PbI3 perovskite deposited by the two-step route shows higher efficiency, surface coverage and infiltration within the structure of 3D HNR than the one-step CH3NH3PbI(3-x)Cl(x) perovskite.

  10. Hierarchical clustering of EMD based interest points for road sign detection

    NASA Astrophysics Data System (ADS)

    Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

    2014-04-01

    This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

  11. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks.

    PubMed

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-01-01

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) "downward-IDS (D-IDS)" to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) "upward-IDS (U-IDS)" to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

  12. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

    PubMed Central

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-01-01

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

  13. Security clustering algorithm based on reputation in hierarchical peer-to-peer network

    NASA Astrophysics Data System (ADS)

    Chen, Mei; Luo, Xin; Wu, Guowen; Tan, Yang; Kita, Kenji

    2013-03-01

    For the security problems of the hierarchical P2P network (HPN), the paper presents a security clustering algorithm based on reputation (CABR). In the algorithm, we take the reputation mechanism for ensuring the security of transaction and use cluster for managing the reputation mechanism. In order to improve security, reduce cost of network brought by management of reputation and enhance stability of cluster, we select reputation, the historical average online time, and the network bandwidth as the basic factors of the comprehensive performance of node. Simulation results showed that the proposed algorithm improved the security, reduced the network overhead, and enhanced stability of cluster.

  14. Predicting Hydrologic Response Through a Pooled Watershed Knowledge Base: A Hierarchical Bayesian Approach

    NASA Astrophysics Data System (ADS)

    Smith, T. J.; Marshall, L. A.; Sharma, A.

    2011-12-01

    Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across a wide array of watersheds, often under very limited data conditions. Statistical methods for hydrologic modeling have evolved rapidly over the recent past in response to these challenges, from improved strategies to both estimate optimal parameter values and predictive uncertainty to approaches that aim to link model parameters to watershed characteristics and allow parameters to be transferred to data-poor watersheds. However, despite the advances that have been made in the application of such statistical tools there remains significant work to be done, particularly regarding the quantification/transfer of predictive uncertainty at/to data-limited locations. Here, we present a hierarchical Bayesian modeling technique referred to as Bayes Empirical Bayes (BEB) as a means of addressing the difficulties in making reliable hydrologic predictions under uncertainty in data-limited watersheds. The BEB technique utilizes formal hierarchical Bayesian analysis (specifically the resultant posterior probability distributions for each estimated model parameter) to pool information from auxiliary watersheds to generate informed probability distributions for each parameter at a data-limited watershed of interest. The application of such a method has thus far been untested in hydrologic applications but has been used more extensively in ecological studies. This technique represents a significant departure from earlier attempts to make predictions in data-limited watersheds in both its usage of available data and its ability to simultaneously quantify predictive uncertainty directly. By utilizing the Bayesian toolkit under a hierarchical approach, information available from auxiliary watersheds can be integrated and summarized into the prediction at the site of interest.

  15. Deterministic hierarchical networks

    NASA Astrophysics Data System (ADS)

    Barrière, L.; Comellas, F.; Dalfó, C.; Fiol, M. A.

    2016-06-01

    It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and also scale-free (the degrees are distributed according to a power law). Moreover, these networks are very often hierarchical, as they describe the modularity of the systems that are modeled. Most of the studies for complex networks are based on stochastic methods. However, a deterministic method, with an exact determination of the main relevant parameters of the networks, has proven useful. Indeed, this approach complements and enhances the probabilistic and simulation techniques and, therefore, it provides a better understanding of the modeled systems. In this paper we find the radius, diameter, clustering coefficient and degree distribution of a generic family of deterministic hierarchical small-world scale-free networks that has been considered for modeling real-life complex systems.

  16. ASTEROID FAMILY IDENTIFICATION USING THE HIERARCHICAL CLUSTERING METHOD AND WISE/NEOWISE PHYSICAL PROPERTIES

    SciTech Connect

    Masiero, Joseph R.; Mainzer, A. K.; Bauer, J. M.; Nugent, C. R.; Stevenson, R.

    2013-06-10

    Using albedos from WISE/NEOWISE to separate distinct albedo groups within the Main Belt asteroids, we apply the Hierarchical Clustering Method to these subpopulations and identify dynamically associated clusters of asteroids. While this survey is limited to the {approx}35% of known Main Belt asteroids that were detected by NEOWISE, we present the families linked from these objects as higher confidence associations than can be obtained from dynamical linking alone. We find that over one-third of the observed population of the Main Belt is represented in the high-confidence cores of dynamical families. The albedo distribution of family members differs significantly from the albedo distribution of background objects in the same region of the Main Belt; however, interpretation of this effect is complicated by the incomplete identification of lower-confidence family members. In total we link 38,298 asteroids into 76 distinct families. This work represents a critical step necessary to debias the albedo and size distributions of asteroids in the Main Belt and understand the formation and history of small bodies in our solar system.

  17. Supercapacitive performance of hierarchical porous carbon microspheres prepared by simple one-pot method

    NASA Astrophysics Data System (ADS)

    Zhao, Qinglan; Wang, Xianyou; Wu, Chun; Liu, Jing; Wang, Hao; Gao, Jiao; Zhang, Youwei; Shu, Hongbo

    2014-05-01

    The hierarchical porous carbon microspheres (HPCMSs) using furfuryl alcohol as carbon resource have been prepared by a simple one-pot method. The HPCMSs are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and nitrogen adsorption/desorption isotherm at 77 K, cyclic voltammetry (CV), galvanostatic charge/discharge tests, electrochemical impedance spectroscopy (EIS) and cycle life measurements in 6 M KOH. The results show that all the HPCMSs samples, which can be fabricated by adjusting the ratio of furfuryl alcohol/tetraethyl orthosilicate, possess three-dimensionally tailored pore structures with unique micro-, meso- and macroporous systems. Particularly, the HPCMS-2 prepared at the mole ratio of 2/1 (furfuryl alcohol/tetraethyl orthosilicate) shows the largest specific surface area of 709 m2 g-1, and the HPCMS-2 electrode owns specific capacitance as high as 221 F g-1 at the current density of 1 A g-1. The supercapacitor using HPCMS-2 as the active material shows high specific capacitance and excellent cycle stability, which exhibits a specific capacitance of 56 F g-1 at the charge/discharge current density of 0.5 A g-1. Furthermore, the HPCMS-2 supercapacitor delivers high energy densities of 6.1 Wh kg-1 at the power density of 5000 W kg-1, revealing a promising application in supercapacitors.

  18. Topology of the correlation networks among major currencies using hierarchical structure methods

    NASA Astrophysics Data System (ADS)

    Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

    2011-02-01

    We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

  19. A novel method for a multi-level hierarchical composite with brick-and-mortar structure.

    PubMed

    Brandt, Kristina; Wolff, Michael F H; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A

    2013-01-01

    The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

  20. A novel method for a multi-level hierarchical composite with brick-and-mortar structure

    NASA Astrophysics Data System (ADS)

    Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

    2013-07-01

    The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

  1. A novel method for a multi-level hierarchical composite with brick-and-mortar structure

    PubMed Central

    Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

    2013-01-01

    The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships. PMID:23900554

  2. Spatiotemporal antibiotic resistance pattern monitoring using geographical information system based hierarchical cluster analysis.

    PubMed

    Hewapathirana, Roshan; Wijayarathna, Gamini

    2010-01-01

    Bacterial antimicrobial resistance in both the medical and agricultural fields has become a serious problem worldwide. Antibiotic resistant strains of bacteria are an increasing threat to human health, with resistance mechanisms having been described to all known antimicrobials currently available for clinical use. Monitoring the geotemporal variations of antibiotic resistance pattern is crucial factor in planning a successful therapeutic guidelines preventing further emergence of antibiotic resistance. This study is based on the retrospective spatiotemporal analysis of laboratory results of Antibiotic Sensitivity Tests, time stamped with the date and time of the microbiological specimen dispatched to the laboratory. Geographic location of the isolated bacterial colony is specified with the latitude and the longitude of the patient's location. Agglomerative Hierarchical Clustering was performed on antimicrobial resistance findings based on the geographic locations generating series of Heatmaps to visualize the extent of the resistance pattern. Sequential Hierarchical cluster analysis was proven to be effective in visualization of antibiotic resistance using Heatmaps demonstrating the temporal variations of the antibiotic resistance patterns.

  3. Enhanced field electron emission properties of hierarchically structured MWCNT-based cold cathodes

    NASA Astrophysics Data System (ADS)

    Gautier, Loïck-Alexandre; Le Borgne, Vincent; Al Moussalami, Samir; El Khakani, My Ali

    2014-02-01

    Hierarchically structured MWCNT (h-MWCNT)-based cold cathodes were successfully achieved by means of a relatively simple and highly effective approach consisting of the appropriate combination of KOH-based pyramidal texturing of Si (100) substrates and PECVD growth of vertically aligned MWCNTs. By controlling the aspect ratio (AR) of the Si pyramids, we were able to tune the field electron emission (FEE) properties of the h-MWCNT cathodes. Indeed, when the AR is increased from 0 (flat Si) to 0.6, not only the emitted current density was found to increase exponentially, but more importantly its associated threshold field (TF) was reduced from 3.52 V/μm to reach a value as low as 1.95 V/μm. The analysis of the J- E emission curves in the light of the conventional Fowler-Nordheim model revealed the existence of two distinct low-field (LF) and high-field (HF) FEE regimes. In both regimes, the hierarchical structuring was found to increase significantly the associated β LF and β HF field enhancement factors of the h-MWCNT cathodes (by a factor of 1.7 and 2.2, respectively). Pyramidal texturing of the cathodes is believed to favor vacuum space charge effects, which could be invoked to account for the significant enhancement of the FEE, particularly in the HF regime where a β HF as high as 6,980 was obtained for the highest AR value of 0.6.

  4. Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism

    PubMed Central

    2015-01-01

    , cofactors and vitamins. Conclusions The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems. PMID:26099921

  5. Layered HEVC/H.265 video transmission scheme based on hierarchical QAM optimization

    NASA Astrophysics Data System (ADS)

    Feng, Weidong; Zhou, Cheng; Xiong, Chengyi; Chen, Shaobo; Wang, Junxi

    2015-12-01

    High Efficiency Video Coding (HEVC) is the state-of-art video compression standard which fully support scalability features and is able to generate layered video streams with unequal importance. Unfortunately, when the base layer (BL) which is more importance to the stream is lost during the transmission, the enhancement layer (EL) based on the base layer must be discarded by receiver. Obviously, using the same transmittal strategies for BL and EL is unreasonable. This paper proposed an unequal error protection (UEP) system using different hierarchical amplitude modulation (HQAM). The BL data with high priority are mapped into the most reliable HQAM mode and the EL data with low priority are mapped into HQAM mode with fast transmission efficiency. Simulations on scalable HEVC codec show that the proposed optimized video transmission system is more attractive than the traditional equal error protection (EEP) scheme because it effectively balances the transmission efficiency and reconstruction video quality.

  6. Improved initialisation of model-based clustering using Gaussian hierarchical partitions

    PubMed Central

    Scrucca, Luca; Raftery, Adrian E.

    2015-01-01

    Initialisation of the EM algorithm in model-based clustering is often crucial. Various starting points in the parameter space often lead to different local maxima of the likelihood function and, so to different clustering partitions. Among the several approaches available in the literature, model-based agglomerative hierarchical clustering is used to provide initial partitions in the popular mclust R package. This choice is computationally convenient and often yields good clustering partitions. However, in certain circumstances, poor initial partitions may cause the EM algorithm to converge to a local maximum of the likelihood function. We propose several simple and fast refinements based on data transformations and illustrate them through data examples. PMID:26949421

  7. Compression of multispectral fluorescence microscopic images based on a modified set partitioning in hierarchal trees

    NASA Astrophysics Data System (ADS)

    Mansoor, Awais; Robinson, J. Paul; Rajwa, Bartek

    2009-02-01

    Modern automated microscopic imaging techniques such as high-content screening (HCS), high-throughput screening, 4D imaging, and multispectral imaging are capable of producing hundreds to thousands of images per experiment. For quick retrieval, fast transmission, and storage economy, these images should be saved in a compressed format. A considerable number of techniques based on interband and intraband redundancies of multispectral images have been proposed in the literature for the compression of multispectral and 3D temporal data. However, these works have been carried out mostly in the elds of remote sensing and video processing. Compression for multispectral optical microscopy imaging, with its own set of specialized requirements, has remained under-investigated. Digital photography{oriented 2D compression techniques like JPEG (ISO/IEC IS 10918-1) and JPEG2000 (ISO/IEC 15444-1) are generally adopted for multispectral images which optimize visual quality but do not necessarily preserve the integrity of scientic data, not to mention the suboptimal performance of 2D compression techniques in compressing 3D images. Herein we report our work on a new low bit-rate wavelet-based compression scheme for multispectral fluorescence biological imaging. The sparsity of signicant coefficients in high-frequency subbands of multispectral microscopic images is found to be much greater than in natural images; therefore a quad-tree concept such as Said et al.'s SPIHT1 along with correlation of insignicant wavelet coefficients has been proposed to further exploit redundancy at high-frequency subbands. Our work propose a 3D extension to SPIHT, incorporating a new hierarchal inter- and intra-spectral relationship amongst the coefficients of 3D wavelet-decomposed image. The new relationship, apart from adopting the parent-child relationship of classical SPIHT, also brought forth the conditional "sibling" relationship by relating only the insignicant wavelet coefficients of subbands

  8. A debugging system for azimuthally acoustic logging tools based on modular and hierarchical design ideas

    NASA Astrophysics Data System (ADS)

    Zhang, K.; Ju, X. D.; Lu, J. Q.; Men, B. Y.

    2016-08-01

    On the basis of modular and hierarchical design ideas, this study presents a debugging system for an azimuthally sensitive acoustic bond tool (AABT). The debugging system includes three parts: a personal computer (PC), embedded front-end machine and function expansion boards. Modular and hierarchical design ideas are conducted in all design and debug processes. The PC communicates with the front-end machine via the Internet, and the front-end machine and function expansion boards connect each other by the extended parallel bus. In this method, the three parts of the debugging system form stable and high-speed data communication. This study not only introduces the system-level debugging and sub-system level debugging of the tool but also the debugging of the analogue signal processing board, which is important and greatly used in logging tools. Experiments illustrate that the debugging system can greatly improve AABT verification and calibration efficiency and that, board-level debugging can examine and improve analogue signal processing boards. The design thinking is clear and the design structure is reasonable, thus making it easy to extend and upgrade the debugging system.

  9. Hierarchical hydrogen bonds directed multi-functional carbon nanotube-based supramolecular hydrogels.

    PubMed

    Du, Ran; Wu, Juanxia; Chen, Liang; Huang, Huan; Zhang, Xuetong; Zhang, Jin

    2014-04-01

    Supramolecular hydrogels (SMHs) are three-dimensional networks filled with a large amount of water. The crosslinking force in the 3D network is always constructed by relatively weak and dynamic non-covalent interactions, and thus SMHs usually possess extremely high susceptibility to external environment and can show extraordinary stimuli-responsive, self-healing or other attractive properties. However, the overall crosslinking force in hydrogel networks is difficult to flexibly modulate, and this leads to limited functions of the SMHs. In this regard, hierarchical hydrogen bonds, that is, the mixture of relatively strong and relatively weak hydrogen bonds, are used herein as crosslinking force for the hydrogel preparation. The ratio of strong and weak hydrogen bonds can be finely tuned to tailor the properties of resultant gels. Thus, by delicate manipulation of the overall crosslinking force in the system, a hydrogel with multiple (thermal, pH and NIR light) responsiveness, autonomous self-healing property and interesting temperature dependent, reversible adhesion behavior is obtained. This kind of hierarchical hydrogen bond manipulation is proved to be a general method for multiple-functionality hydrogel preparation, and the resultant material shows potential for a range of applications.

  10. Evaluation of B2C website based on the usability factors by using fuzzy AHP & hierarchical fuzzy TOPSIS

    NASA Astrophysics Data System (ADS)

    Masudin, I.; Saputro, T. E.

    2016-02-01

    In today's technology, electronic trading transaction via internet has been utilized properly with rapid growth. This paper intends to evaluate related to B2C e-commerce website in order to find out the one which meets the usability factors better than another. The influential factors to B2C e-commerce website are determined for two big retailer websites. The factors are investigated based on the consideration of several studies and conformed to the website characteristics. The evaluation is conducted by using different methods namely fuzzy AHP and hierarchical fuzzy TOPSIS so that the final evaluation can be compared. Fuzzy triangular number is adopted to deal with imprecise judgment under fuzzy environment.

  11. An Accessible Method for Implementing Hierarchical Models with Spatio-Temporal Abundance Data

    PubMed Central

    Ross, Beth E.; Hooten, Mevin B.; Koons, David N.

    2012-01-01

    A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time. PMID:23166658

  12. An Accessible Method for Implementing Hierarchical Models with Spatio-Temporal Abundance Data

    USGS Publications Warehouse

    Ross, Beth E.; Hooten, Melvin B.; Koons, David N.

    2012-01-01

    A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.

  13. Hierarchical pore structure of calcium phosphate scaffolds by a combination of gel-casting and multiple tape-casting methods.

    PubMed

    Sánchez-Salcedo, S; Werner, J; Vallet-Regí, M

    2008-07-01

    The objective of this work was to design hierarchical pore structure scaffolds with potential applications in bone tissue regeneration. For that purpose, a bioceramic material such as biphasic calcium phosphate, which consists of a mixture of hydroxyapatite and beta-tricalcium phosphate, was selected. Multilayer pieces (MLP) with hierarchical pore structure were developed employing a new technique that combines gel casting and adding porogens, using multiple tape-casting methods. Pieces with functionally graded porosity were fabricated using porogens with different sizes. The porogens used were Porlat K85 and Porlat K86 with diameters <150 microm and 150-300 microm, respectively. Two types of sintered tapes, with different porosity, no cracking and enough interconnection size were selected. MLP with hierarchical pore structure were designed by the multiple tape-casting method. Interconnected pores whose sizes increase from interior tapes (1.6-3.6 microm) towards exterior tapes (20-51.5 microm) and interpenetration between tapes were achieved. Delamination or cracking were not observed after heat treatment. The flexural strength of pieces was investigated by the three-point bending test. This new combination of methods offers the possibility of manufacturing scaffolds with interconnected pore sizes ranging from 1.6 to 51.5 microm.

  14. A pollutant load hierarchical allocation method integrated in an environmental capacity management system for Zhushan Bay, Taihu Lake.

    PubMed

    Liang, Shidong; Jia, Haifeng; Yang, Cong; Melching, Charles; Yuan, Yongping

    2015-11-15

    An environmental capacity management (ECM) system was developed to help practically implement a Total Maximum Daily Load (TMDL) for a key bay in a highly eutrophic lake in China. The ECM system consists of a simulation platform for pollutant load calculation and a pollutant load hierarchical allocation (PLHA) system. The simulation platform was developed by linking the Environmental Fluid Dynamics Code (EFDC) and Water Quality Analysis Simulation Program (WASP). In the PLHA, pollutant loads were allocated top-down in several levels based on characteristics of the pollutant sources. Different allocation methods could be used for the different levels with the advantages of each method combined over the entire allocation. Zhushan Bay of Taihu Lake, one of the most eutrophic lakes in China, was selected as a case study. The allowable loads of total nitrogen, total phosphorus, ammonia, and chemical oxygen demand were found to be 2122.2, 94.9, 1230.4, and 5260.0 t·yr(-1), respectively. The PLHA for the case study consists of 5 levels. At level 0, loads are allocated to those from the lakeshore direct drainage, atmospheric deposition, internal release, and tributary inflows. At level 1 the loads allocated to tributary inflows are allocated to the 3 tributaries. At level 2, the loads allocated to one inflow tributary are allocated to upstream areas and local sources along the tributary. At level 3, the loads allocated to local sources are allocated to the point and non-point sources from different towns. At level 4, the loads allocated to non-point sources in each town are allocated to different villages. Compared with traditional forms of pollutant load allocation methods, PLHA can combine the advantages of different methods which put different priority weights on equity and efficiency, and the PLHA is easy to understand for stakeholders and more flexible to adjust when applied in practical cases. PMID:26172589

  15. A hierarchical pyramid method for managing large-scale high-resolution drainage networks extracted from DEM

    NASA Astrophysics Data System (ADS)

    Bai, Rui; Tiejian, Li; Huang, Yuefei; Jiaye, Li; Wang, Guangqian; Yin, Dongqin

    2015-12-01

    The increasing resolution of Digital Elevation Models (DEMs) and the development of drainage network extraction algorithms make it possible to develop high-resolution drainage networks for large river basins. These vector networks contain massive numbers of river reaches with associated geographical features, including topological connections and topographical parameters. These features create challenges for efficient map display and data management. Of particular interest are the requirements of data management for multi-scale hydrological simulations using multi-resolution river networks. In this paper, a hierarchical pyramid method is proposed, which generates coarsened vector drainage networks from the originals iteratively. The method is based on the Horton-Strahler's (H-S) order schema. At each coarsening step, the river reaches with the lowest H-S order are pruned, and their related sub-basins are merged. At the same time, the topological connections and topographical parameters of each coarsened drainage network are inherited from the former level using formulas that are presented in this study. The method was applied to the original drainage networks of a watershed in the Huangfuchuan River basin extracted from a 1-m-resolution airborne LiDAR DEM and applied to the full Yangtze River basin in China, which was extracted from a 30-m-resolution ASTER GDEM. In addition, a map-display and parameter-query web service was published for the Mississippi River basin, and its data were extracted from the 30-m-resolution ASTER GDEM. The results presented in this study indicate that the developed method can effectively manage and display massive amounts of drainage network data and can facilitate multi-scale hydrological simulations.

  16. Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

    PubMed Central

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-01-01

    We describe algorithms for discovering immunophenotypes from large collections of flow cytometry 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-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are

  17. Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

    PubMed Central

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-01-01

    We describe algorithms for discovering immunophenotypes from large collections of flow cytometry 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-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are

  18. Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples.

    PubMed

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-01-01

    We describe algorithms for discovering immunophenotypes from large collections of flow cytometry 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-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are

  19. Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples.

    PubMed

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-01-01

    We describe algorithms for discovering immunophenotypes from large collections of flow cytometry 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-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are

  20. Nanowire-based hierarchical tin oxide/zinc stannate hollow microspheres: Enhanced solar energy utilization efficiency for dye-sensitized solar cells and photocatalytic degradation of dyes

    NASA Astrophysics Data System (ADS)

    Li, Zhengdao; Zhou, Yong; Mao, Wutao; Zou, Zhigang

    2015-01-01

    Nanowire-based SnO2/Zn2SnO4 hollow microspheres are synthesized using a facile one-pot method for solar energy conversion and environment cleaning. The micrometer-sized hollow spheres possess a hierarchical structure with the shell consisting of nanowires. With the hybrid SnO2/Zn2SnO4 microspheres as photoanodes, the dye-sensitized solar cells (DSSCs) with an overall 4.72% photoconversion efficiency is obtained, nearly 240% improvement over the DSSCs that uses nanorod-based hierarchical SnO2 microspheres. The hybrid microspheres are also determined to be high-performance photocatalyst with a better recyclability for the photodegradation of dyes under simulated sunlight irradiation. These improvements of solar energy utilization are ascribed to the formation of the heterojunctions between SnO2 and Zn2SnO4 to enhance electron transport and charge-separation efficiencies.

  1. Photo-driven autonomous hydrogen generation system based on hierarchically shelled ZnO nanostructures

    SciTech Connect

    Kim, Heejin; Yong, Kijung

    2013-11-25

    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{sup 2} current density at the un-assisted condition.

  2. Recombination reduction on lead halide perovskite solar cells based on low temperature synthesized hierarchical TiO2 nanorods

    NASA Astrophysics Data System (ADS)

    Jaramillo-Quintero, Oscar A.; Solís de La Fuente, Mauricio; Sanchez, Rafael S.; Recalde, Ileana B.; Juarez-Perez, Emilio J.; Rincón, Marina E.; Mora-Seró, Iván

    2016-03-01

    Intensive research on the electron transport material (ETM) has been pursued to improve the efficiency of perovskite solar cells (PSCs) and decrease their cost. More importantly, the role of the ETM layer is not yet fully understood, and research on new device architectures is still needed. Here, we report the use of three-dimensional (3D) TiO2 with a hierarchical architecture based on rutile nanorods (NR) as photoanode material for PSCs. The proposed hierarchical nanorod (HNR) films were synthesized by a two-step low temperature (180 °C) hydrothermal method, and consist of TiO2 nanorod trunks with optimal lengths of 540 nm and TiO2 nanobranches with lengths of 45 nm. Different device configurations were fabricated with TiO2 structures (compact layer, NR and HNR) and CH3NH3PbI3, using different synthetic routes, as the active material. PSCs based on HNR-CH3NH3PbI3 achieved the highest power conversion efficiency compared to PSCs with other TiO2 structures. This result can be ascribed mainly to lower charge recombination as determined by impedance spectroscopy. Furthermore, we have observed that the CH3NH3PbI3 perovskite deposited by the two-step route shows higher efficiency, surface coverage and infiltration within the structure of 3D HNR than the one-step CH3NH3PbI3-xClx perovskite.Intensive research on the electron transport material (ETM) has been pursued to improve the efficiency of perovskite solar cells (PSCs) and decrease their cost. More importantly, the role of the ETM layer is not yet fully understood, and research on new device architectures is still needed. Here, we report the use of three-dimensional (3D) TiO2 with a hierarchical architecture based on rutile nanorods (NR) as photoanode material for PSCs. The proposed hierarchical nanorod (HNR) films were synthesized by a two-step low temperature (180 °C) hydrothermal method, and consist of TiO2 nanorod trunks with optimal lengths of 540 nm and TiO2 nanobranches with lengths of 45 nm. Different

  3. Enhanced field electron emission properties of hierarchically structured MWCNT-based cold cathodes

    PubMed Central

    2014-01-01

    Hierarchically structured MWCNT (h-MWCNT)-based cold cathodes were successfully achieved by means of a relatively simple and highly effective approach consisting of the appropriate combination of KOH-based pyramidal texturing of Si (100) substrates and PECVD growth of vertically aligned MWCNTs. By controlling the aspect ratio (AR) of the Si pyramids, we were able to tune the field electron emission (FEE) properties of the h-MWCNT cathodes. Indeed, when the AR is increased from 0 (flat Si) to 0.6, not only the emitted current density was found to increase exponentially, but more importantly its associated threshold field (TF) was reduced from 3.52 V/μm to reach a value as low as 1.95 V/μm. The analysis of the J-E emission curves in the light of the conventional Fowler-Nordheim model revealed the existence of two distinct low-field (LF) and high-field (HF) FEE regimes. In both regimes, the hierarchical structuring was found to increase significantly the associated βLF and βHF field enhancement factors of the h-MWCNT cathodes (by a factor of 1.7 and 2.2, respectively). Pyramidal texturing of the cathodes is believed to favor vacuum space charge effects, which could be invoked to account for the significant enhancement of the FEE, particularly in the HF regime where a βHF as high as 6,980 was obtained for the highest AR value of 0.6. PMID:24484649

  4. Hierarchical control of ride height system for electronically controlled air suspension based on variable structure and fuzzy control theory

    NASA Astrophysics Data System (ADS)

    Xu, Xing; Zhou, Kongkang; Zou, Nannan; Jiang, Hong; Cui, Xiaoli

    2015-09-01

    The current research of air suspension mainly focuses on the characteristics and design of the air spring. In fact, electronically controlled air suspension (ECAS) has excellent performance in flexible height adjustment during different driving conditions. However, the nonlinearity of the ride height adjusting system and the uneven distribution of payload affect the control accuracy of ride height and the body attitude. Firstly, the three-point measurement system of three height sensors is used to establish the mathematical model of the ride height adjusting system. The decentralized control of ride height and the centralized control of body attitude are presented to design the ride height control system for ECAS. The exact feedback linearization method is adopted for the nonlinear mathematical model of the ride height system. Secondly, according to the hierarchical control theory, the variable structure control (VSC) technique is used to design a controller that is able to adjust the ride height for the quarter-vehicle anywhere, and each quarter-vehicle height control system is independent. Meanwhile, the three-point height signals obtained by three height sensors are tracked to calculate the body pitch and roll attitude over time, and then by calculating the deviation of pitch and roll and its rates, the height control correction is reassigned based on the fuzzy algorithm. Finally, to verify the effectiveness and performance of the proposed combined control strategy, a validating test of ride height control system with and without road disturbance is carried out. Testing results show that the height adjusting time of both lifting and lowering is over 5 s, and the pitch angle and the roll angle of body attitude are less than 0.15°. This research proposes a hierarchical control method that can guarantee the attitude stability, as well as satisfy the ride height tracking system.

  5. Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model.

    PubMed

    Mohammed, Mohammed A; Manktelow, Bradley N; Hofer, Timothy P

    2016-04-01

    There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26278334

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Supramolecular Alternating Polymer from Crown Ether and Pillar[5]arene-Based Double Molecular Recognition for Preparation of Hierarchical Materials.

    PubMed

    Li, Hui; Fan, Xiaodong; Qi, Miao; Yang, Zhen; Zhang, Haitao; Tian, Wei

    2016-01-01

    A novel supramolecular alternating polymer is constructed based on double molecular recognition events of benzo-21-crown-7 with a secondary ammonium salt and of pillar[5]arene with a neutral guest. The resulting polymer is utilized to prepare hierarchical materials with different dimensionalities for the first time. These materials included zero-dimensional spherical aggregates, one-dimensional nanofibers, two-dimensional microstructured films, and three-dimensional ordered glue. This development will be helpful for designing and preparing supramolecular hierarchical materials with different dimensionalities. PMID:26555439

  9. The potential of near-surface geophysical methods in a hierarchical monitoring approach for the detection of shallow CO2 seeps at geological storage sites

    NASA Astrophysics Data System (ADS)

    Sauer, U.; Schuetze, C.; Dietrich, P.

    2013-12-01

    The MONACO project (Monitoring approach for geological CO2 storage sites using a hierarchic observation concept) aims to find reliable monitoring tools that work on different spatial and temporal scales at geological CO2 storage sites. This integrative hierarchical monitoring approach based on different levels of coverage and resolutions is proposed as a means of reliably detecting CO2 degassing areas at ground surface level and for identifying CO2 leakages from storage formations into the shallow subsurface, as well as CO2 releases into the atmosphere. As part of this integrative hierarchical monitoring concept, several methods and technologies from ground-based remote sensing (Open-path Fourier-transform infrared (OP-FTIR) spectroscopy), regional measurements (near-surface geophysics, chamber-based soil CO2 flux measurement) and local in-situ measurements (using shallow boreholes) will either be combined or used complementary to one another. The proposed combination is a suitable concept for investigating CO2 release sites. This also presents the possibility of adopting a modular monitoring concept whereby our monitoring approach can be expanded to incorporate other methods in various coverage scales at any temporal resolution. The link between information obtained from large-scale surveys and local in-situ monitoring can be realized by sufficient geophysical techniques for meso-scale monitoring, such as geoelectrical and self-potential (SP) surveys. These methods are useful for characterizing fluid flow and transport processes in permeable near-surface sedimentary layers and can yield important information concerning CO2-affected subsurface structures. Results of measurements carried out a natural analogue site in the Czech Republic indicate that the hierarchical monitoring approach represents a successful multidisciplinary modular concept that can be used to monitor both physical and chemical processes taking place during CO2 migration and seepage. The

  10. Hierarchical Bi based nanobundles: an excellent photocatalyst for visible-light degradation of Rhodamine B dye.

    PubMed

    Gao, Fangfang; Zhao, Yan; Li, Yawen; Wu, Gongjuan; Lu, Yan; Song, Yuehong; Huang, Zhifang; Li, Na; Zhao, Jingzhe

    2015-06-15

    Hierarchical Bi based nanobundles were self-assembled via an aqueous reduction approach using hydrazine hydrate as reductive agent, and were used as photocatalysts for the degradation of Rhodamine B (RhB) under visible light. PVP molecules were designed as inducing agent to construct the Bi based nanobundles. The as-obtained samples were characterized by X-ray diffraction (XRD), energy dispersive X-ray (EDX), thermogravimetric-differential thermal analyzer (TG-DTA), infrared spectroscopy (IR) and field emission scanning electron microscopy (FESEM) to get clear information of the crystals. A possible formation mechanism for the interesting architectures was proposed in the paper. The Bi based nanobundles exhibited excellent photocatalytic activity and good cycling performance towards photodegradation of RhB under visible light. The pH-sensitive degradation can reach 96% in degradation rate after 90 min, which indicates potential applications of the Bi based nanobundles on the degradation of organic pollutants. Degradation mechanism is proposed on the combination of Bi and BiOCl crystals.

  11. Monitoring biological heterogeneity in a northern mixed prairie using hierarchical remote sensing methods

    NASA Astrophysics Data System (ADS)

    Zhang, Chunhua

    Heterogeneity, the degree of dissimilarity, is one of the most important and widely applicable concepts in ecology. It is highly related to ecosystem conditions and features wildlife habitat. Grasslands have been described as inherently heterogeneous because their composition and productivity are highly variable across multiple scales. Therefore, biological heterogeneity can be an indicator of ecosystem health. The mixed prairie in Canada, characterized by its semiarid environment, sparse canopy, and plant litter, offers a challenging region for environmental research using remote sensing techniques. This thesis dwells with the plant canopy heterogeneity of the mixed prairie ecosystem in the Grasslands National Park (GNP) and surrounding pastures by combining field biological parameters (e.g., grass cover, leaf area index, and biomass), field collected hyperspectral data, and hierarchical resolution satellite imagery. The thesis scrutinized four aspects of heterogeneity study: the importance of scale in grassland research, relationships between biological parameters and remotely collected data, methodology of measuring biological heterogeneity, and the influence of climatic variation on grasslands biological heterogeneity. First, the importance of scale is examined by applying the semivariogram analysis on field collected hyperspectral and biophysical data. Results indicate that 15 - 20 m should be the appropriate resolution when variations of biological parameters and canopy reflectance are sampled. Therefore, it is reasonable to use RADARSAT 1, Landsat TM, and SPOT images, whose resolutions are around 20 m, to assess the variation of biological heterogeneity. Second, the efficiency of vegetation indices derived from SPOT 4 and Landsat 5 TM images in monitoring the northern mixed prairie health was examined using Pearson's correlation and stepwise regression analyses. Results show that the spectral curve of the grass canopy is similar to that of the bare soil with

  12. Bayesian methods for estimating the reliability in complex hierarchical networks (interim report).

    SciTech Connect

    Marzouk, Youssef M.; Zurn, Rena M.; Boggs, Paul T.; Diegert, Kathleen V.; Red-Horse, John Robert; Pebay, Philippe Pierre

    2007-05-01

    Current work on the Integrated Stockpile Evaluation (ISE) project is evidence of Sandia's commitment to maintaining the integrity of the nuclear weapons stockpile. In this report, we undertake a key element in that process: development of an analytical framework for determining the reliability of the stockpile in a realistic environment of time-variance, inherent uncertainty, and sparse available information. This framework is probabilistic in nature and is founded on a novel combination of classical and computational Bayesian analysis, Bayesian networks, and polynomial chaos expansions. We note that, while the focus of the effort is stockpile-related, it is applicable to any reasonably-structured hierarchical system, including systems with feedback.

  13. Breath Figures of Nanoscale Bricks: A Universal Method for Creating Hierarchic Porous Materials from Inorganic Nanoparticles Stabilized with Mussel-Inspired Copolymers.

    PubMed

    Saito, Yuta; Shimomura, Masatsugu; Yabu, Hiroshi

    2014-09-01

    High-performance catalysts and photovoltaics are required for building an environmentally sustainable society. Because catalytic and photovoltaic reactions occur at the interfaces between reactants and surfaces, the chemical, physical, and structural properties of interfaces have been the focus of much research. To improve the performance of these materials further, inorganic porous materials with hierarchic porous architectures have been fabricated. The breath figure technique allows preparing porous films by using water droplets as templates. In this study, a valuable preparation method for hierarchic porous inorganic materials is shown. Hierarchic porous materials are prepared from surface-coated inorganic nanoparticles with amphiphilic copolymers having catechol moieties followed by sintering. Micron-scale pores are prepared by using water droplets as templates, and nanoscale pores are formed between the nanoparticles. The fabrication method allows the preparation of hierarchic porous films from inorganic nanoparticles of various shapes and materials.

  14. A novel vehicle dynamics stability control algorithm based on the hierarchical strategy with constrain of nonlinear tyre forces

    NASA Astrophysics Data System (ADS)

    Li, Liang; Jia, Gang; Chen, Jie; Zhu, Hongjun; Cao, Dongpu; Song, Jian

    2015-08-01

    Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.

  15. Ut-Minimos a Hierarchical Transport Model Based Simulator for Deep Submicron Silicon Devices

    NASA Astrophysics Data System (ADS)

    Yeap, Choh-Fei

    1995-01-01

    The challenge of Ultra Large Scale Integration (ULSI) of integrated circuits reinforces the need for accurate and efficient simulations to speed development and reduce cost. The predictive power of conventional simulation based on the drift-diffusion (DD) model has diminished to a critically low level. An improved transport model must now replace, what has been the foundation of semiconductor device simulation, the DD model. The hydrodynamic (HD) transport model, that addresses non-local effects such as velocity overshoot and carrier heating, is an attractive candidate. The true viability of the HD models in replacing the DD model rests on their availability in well-accepted device simulators, physical accuracy and ease of solution. This work is an attempt to hasten and facilitate this replacement. The focus of this dissertation is an effort towards implementing a hierarchy of promising HD transport model candidates in an established and well-accepted device simulator using robust and efficient discretization and solution methods. Thus, UT-MiniMOS 3.0, a 2-D two -carrier integrated simulator for deep submicron silicon devices, has been developed to include a hierarchy of transport models and to construct a programming environment for easy implementation and maintenance of the physical models and numerical techniques. The hierarchy of transport models includes the DD model, post-processing current contour HD model, parabolic HD model, Stratton's energy balance model, Chen's energy transport model, Lee's HD model, Stettler's HD model, Bordelon's non-parabolic HD (NPHD) model, lattice temperature model, and Monte Carlo (MC) model. Each of these HD models is cast into a generalized HD formulation with four controlling parameters. This generalized HD formulation allows a unified discretization for all HD models. The NPHD model has been shown to provide the best overall agreement to MC energy, velocity and concentration. HD simulation in UT-MiniMOS for a bias point

  16. An oil droplet template method for the synthesis of hierarchical structured Co3O4/C anodes for Li-ion batteries

    NASA Astrophysics Data System (ADS)

    Sun, Jie; Liu, Haimei; Chen, Xu; Evans, David G.; Yang, Wensheng

    2013-07-01

    Superposed cobalt(ii)-cobalt(iii) layered double hydroxide (CoII-CoIII-LDH) nanoplates were synthesized by an oil droplet template method, in which the main steps are as follows: LDH nanosheets were first assembled on an oil droplet template to form a multishell sphere, and then the oil droplet was easily removed under centrifugal force due to its very different density from that of the assembled LDH shell. This resulted in the multishell spheres being split open to create superposed LDH nanoplates. The resulting material has a three-stage architecture, namely, the primary building blocks of nanosheets, the secondary architecture of shells derived from the nanosheets, and the long-range architecture of superposed nanoplates assembled from the vertically stacked shells. Most importantly, the as-fabricated LDH-based hierarchical structure can be readily converted to a Co3O4/C composite via calcination, without obvious structural alteration, where the residual surfactant is the source of the carbon. When used as an anode material for Li-ion batteries, the Co3O4/C electrode exhibits an excellent electrochemical performance, which is attributed to the unique hierarchically porous structure.Superposed cobalt(ii)-cobalt(iii) layered double hydroxide (CoII-CoIII-LDH) nanoplates were synthesized by an oil droplet template method, in which the main steps are as follows: LDH nanosheets were first assembled on an oil droplet template to form a multishell sphere, and then the oil droplet was easily removed under centrifugal force due to its very different density from that of the assembled LDH shell. This resulted in the multishell spheres being split open to create superposed LDH nanoplates. The resulting material has a three-stage architecture, namely, the primary building blocks of nanosheets, the secondary architecture of shells derived from the nanosheets, and the long-range architecture of superposed nanoplates assembled from the vertically stacked shells. Most

  17. A Survey of Model Evaluation Approaches with a Tutorial on Hierarchical Bayesian Methods

    ERIC Educational Resources Information Center

    Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan

    2008-01-01

    This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…

  18. Analysis of the twin spacing and grain size effects on mechanical properties in hierarchically nanotwinned face-centered cubic metals based on a mechanism-based plasticity model

    NASA Astrophysics Data System (ADS)

    Zhu, Linli; Qu, Shaoxing; Guo, Xiang; Lu, Jian

    2015-03-01

    Hierarchical twin lamellae in polycrystalline face-centered cubic (fcc) metals possess a possibility to achieve higher strength with keeping an acceptable elongation. The present work is concerned with the analysis of twin spacing and grain size-dependent plastic performance in hierarchically nanotwinned fcc metals using a generalized strain-gradient plasticity model. The dislocation density-based physical model for constitutive description of nanotwinned fcc metals is expanded for the hierarchical structures of nanotwins. The strengthening mechanism and the failure behavior in these hierarchical nanostructures are studied to evaluate the strength and ductility. Moreover, the transition twin spacing between the strengthening and softening is obtained in different order of twin lamellae. A dislocation-based model on nucleating deformation twins is presented to predict the critical twin spacing in the lowest twin lamellae for generating the subordinate twin lamellae. Our simulation results demonstrate that the existence of the hierarchical nanotwins gives rise to a significant enhancement in the strength, and the resulting global flow stresses are sensitive to the twin spacings of the hierarchical twin lamellae and the grain size. Two softening stages are observed with variation of twin spacing, and the relevant transition twin spacing depends on the microstructural size in hierarchically nanotwinned metals. We further find that the predicted failure strain decreases with decreasing the twin spacing, which is quite different from the case of the individually nanotwinned fcc metals. The critical twin spacing for generating subordinate twins also depends on the twin spacing of superordinate twin lamellae and the grain size. These findings suggest that the high yield strength and good ductility can be achieved by optimizing the grain size and the twin spacings in the hierarchical twins.

  19. Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

    PubMed

    Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

    2014-12-01

    This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

  20. Expansion of the Hierarchical Terminology Auditing Framework Through Usage of Levenshtein Distance-Based Criterion.

    PubMed

    Zakharchenko, Aleksandr; Geller, James

    2016-01-01

    We continue our previous work of creating and improving a framework for detecting the differences between hierarchical terminologies and suggesting ways to connect them, which is implemented in an automated tool. PMID:27577431

  1. Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation

    PubMed Central

    Dura-Bernal, Salvador; Wennekers, Thomas; Denham, Susan L.

    2012-01-01

    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-up interactions, for

  2. Web-based Hierarchical Ordering Mechanism (WHOM) tool for MODIS data from Terra

    NASA Astrophysics Data System (ADS)

    Sikder, M. S.; Eaton, P.; Leptoukh, G.; McCrimmon, N.; Zhou, B.

    2001-05-01

    At the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC), we have substantially enhanced the popular Web-based Hierarchical Ordering Mechanism (WHOM) to include data from the Earth Observing System (EOS). The GES DAAC archives unprecedented volumes of remotely sensed data and large number of geophysical products derived from the MODIS instrument on board Terra satellite, and distributes them to the world scientific and applications user community. These products are currently divided into three groups: Radiometric and Geolocation, Atmosphere, and Ocean data products. The so-called Terra-WHOM (http://acdisx.gsfc.nasa.gov/data/dataset/MODIS/index.html) is a GES DAAC developed search and order user interface which is a smaller segment of the WHOM interface that provides access to all other GES DAAC data holdings. Terra-WHOM specifically provides user access to MODIS data archived at the GES DAAC. It allows users to navigate through all the available data products and submit a data request with minimal effort. The WHOM modular design and hierarchical architecture makes this tool unique, user-friendly, and very efficient to complete the search and order. The main principle of WHOM is that it advertises the available data products, so, users always know what they can get. The WHOM design includes: simple point & click, flexible, web pages generated from templates, consistent look and feel throughout interface, and easy configuration management due to contents being encapsulated and separated from software. Modular search algorithms provide dynamic Spatial and Temporal search capability and return the search results as html pages using CGI scripts. In Terra-WHOM, calendar pages show the actual number of data granules archived for each day for high-resolution local scenes, and from there the user can go to a page showing the geo-coverage for every granule for a given day. This feature significantly optimizes user's effort for selecting data. The

  3. High performance solid state flexible supercapacitor based on molybdenum sulfide hierarchical nanospheres

    NASA Astrophysics Data System (ADS)

    Javed, Muhammad Sufyan; Dai, Shuge; Wang, Mingjun; Guo, Donglin; Chen, Lin; Wang, Xue; Hu, Chenguo; Xi, Yi

    2015-07-01

    Molybdenum sulfide (MoS2) hierarchical nanospheres are synthesized using a hydrothermal method and characterized by X-ray powder diffraction, Brunauer-Emmett-Teller, scanning electron microscopy and transmission electron microscopy. The prepared MoS2 is used to fabricate solid state flexible supercapacitors which show excellent electrochemical performance such as high capacitance 368 F g-1 at a scan rate of 5 mV s-1 and high power density of 128 W kg-1 at energy density of 5.42 Wh kg-1. The fabricated supercapacitor presents good characteristics such as lightweight, low cast, portability, high flexibility, and long term cycling stability by retaining 96.5% after 5000 cycles at constant discharge current of 0.8 mA. Electrochemical impedance spectroscopy (EIS) results reveal low resistance and suggest that MoS2 nanospheres would be a promising candidate for supercapacitors. Three charged supercapacitors connected in series can light 8 red color commercial light emitting diodes (LEDs) for 2 min, demonstrating its capability as a good storage device.

  4. A subsumptive, hierarchical, and distributed vision-based architecture for smart robotics.

    PubMed

    DeSouza, Guilherme N; Kak, Avinash C

    2004-10-01

    We present a distributed vision-based architecture for smart robotics that is composed of multiple control loops, each with a specialized level of competence. Our architecture is subsumptive and hierarchical, in the sense that each control loop can add to the competence level of the loops below, and in the sense that the loops can present a coarse-to-fine gradation with respect to vision sensing. At the coarsest level, the processing of sensory information enables a robot to become aware of the approximate location of an object in its field of view. On the other hand, at the finest end, the processing of stereo information enables a robot to determine more precisely the position and orientation of an object in the coordinate frame of the robot. The processing in each module of the control loops is completely independent and it can be performed at its own rate. A control Arbitrator ranks the results of each loop according to certain confidence indices, which are derived solely from the sensory information. This architecture has clear advantages regarding overall performance of the system, which is not affected by the "slowest link," and regarding fault tolerance, since faults in one module does not affect the other modules. At this time we are able to demonstrate the utility of the architecture for stereoscopic visual servoing. The architecture has also been applied to mobile robot navigation and can easily be extended to tasks such as "assembly-on-the-fly."

  5. Hierarchical Control Scheme for Improving Transient Voltage Recovery of a DFIG-Based WPP

    SciTech Connect

    Kim, Jinho; Muljadi, Eduard; Kang, Yong Cheol

    2015-06-05

    Modern grid codes require that wind power plants (WPPs) inject reactive power according to the voltage dip at a point of interconnection (POI). This requirement helps to support a POI voltage during a fault. However, if a fault is cleared, the POI and wind turbine generator (WTG) voltages are likely to exceed acceptable levels unless the WPP reduces the injected reactive power quickly. This might deteriorate the stability of a grid by allowing the disconnection of WTGs to avoid any damage. This paper proposes a hierarchical control scheme of a doubly-fed induction generator (DFIG)-based WPP. The proposed scheme aims to improve the reactive power injecting capability during the fault and suppress the overvoltage after the fault clearance. To achieve the former, an adaptive reactive power-to-voltage scheme is implemented in each DFIG controller so that a DFIG with a larger reactive power capability will inject more reactive power. To achieve the latter, a washout filter is used to capture a high frequency component contained in the WPP voltage, which is used to remove the accumulated values in the proportional-integral controllers. Test results indicate that the scheme successfully supports the grid voltage during the fault, and recovers WPP voltages without exceeding the limit after the fault clearance.

  6. Hierarchical Conformational Analysis of Native Lysozyme Based on Sub-Millisecond Molecular Dynamics Simulations

    PubMed Central

    Wang, Kai; Long, Shiyang; Tian, Pu

    2015-01-01

    Hierarchical organization of free energy landscape (FEL) for native globular proteins has been widely accepted by the biophysics community. However, FEL of native proteins is usually projected onto one or a few dimensions. Here we generated collectively 0.2 milli-second molecular dynamics simulation trajectories in explicit solvent for hen egg white lysozyme (HEWL), and carried out detailed conformational analysis based on backbone torsional degrees of freedom (DOF). Our results demonstrated that at micro-second and coarser temporal resolutions, FEL of HEWL exhibits hub-like topology with crystal structures occupying the dominant structural ensemble that serves as the hub of conformational transitions. However, at 100ns and finer temporal resolutions, conformational substates of HEWL exhibit network-like topology, crystal structures are associated with kinetic traps that are important but not dominant ensembles. Backbone torsional state transitions on time scales ranging from nanoseconds to beyond microseconds were found to be associated with various types of molecular interactions. Even at nanoseconds temporal resolution, the number of conformational substates that are of statistical significance is quite limited. These observations suggest that detailed analysis of conformational substates at multiple temporal resolutions is both important and feasible. Transition state ensembles among various conformational substates at microsecond temporal resolution were observed to be considerably disordered. Life times of these transition state ensembles are found to be nearly independent of the time scales of the participating torsional DOFs. PMID:26057625

  7. A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer.

    PubMed

    Khan, Adil Mehmood; Lee, Young-Koo; Lee, Sungyoung Y; Kim, Tae-Seong

    2010-09-01

    Physical-activity recognition via wearable sensors can provide valuable information regarding an individual's degree of functional ability and lifestyle. In this paper, we present an accelerometer sensor-based approach for human-activity recognition. Our proposed recognition method uses a hierarchical scheme. At the lower level, the state to which an activity belongs, i.e., static, transition, or dynamic, is recognized by means of statistical signal features and artificial-neural nets (ANNs). The upper level recognition uses the autoregressive (AR) modeling of the acceleration signals, thus, incorporating the derived AR-coefficients along with the signal-magnitude area and tilt angle to form an augmented-feature vector. The resulting feature vector is further processed by the linear-discriminant analysis and ANNs to recognize a particular human activity. Our proposed activity-recognition method recognizes three states and 15 activities with an average accuracy of 97.9% using only a single triaxial accelerometer attached to the subject's chest.

  8. Prolonging the Lifetime of Wireless Sensor Networks Interconnected to Fixed Network Using Hierarchical Energy Tree Based Routing Algorithm

    PubMed Central

    Kalpana, M.; Dhanalakshmi, R.; Parthiban, P.

    2014-01-01

    This research work proposes a mathematical model for the lifetime of wireless sensor networks (WSN). It also proposes an energy efficient routing algorithm for WSN called hierarchical energy tree based routing algorithm (HETRA) based on hierarchical energy tree constructed using the available energy in each node. The energy efficiency is further augmented by reducing the packet drops using exponential congestion control algorithm (TCP/EXP). The algorithms are evaluated in WSNs interconnected to fixed network with seven distribution patterns, simulated in ns2 and compared with the existing algorithms based on the parameters such as number of data packets, throughput, network lifetime, and data packets average network lifetime product. Evaluation and simulation results show that the combination of HETRA and TCP/EXP maximizes longer network lifetime in all the patterns. The lifetime of the network with HETRA algorithm has increased approximately 3.2 times that of the network implemented with AODV. PMID:25535626

  9. Development of Hierarchical Bayesian Model Based on Regional Frequency Analysis and Its Application to Estimate Areal Rainfall in South Korea

    NASA Astrophysics Data System (ADS)

    Kim, J.; Kwon, H. H.

    2014-12-01

    The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, This study aims to develop a hierarchical Bayesian model based regional frequency analysis in that spatial patterns of the design rainfall with geographical information are explicitly incorporated. This study assumes that the parameters of Gumbel distribution are a function of geographical characteristics (e.g. altitude, latitude and longitude) within a general linear regression framework. Posterior distributions of the regression parameters are estimated by Bayesian Markov Chain Monte Calro (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the Gumbel distribution by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Acknowledgement: This research was supported by a grant (14AWMP-B079364-01) from Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  10. Model-based automatic target recognition using hierarchical foveal machine vision

    NASA Astrophysics Data System (ADS)

    McKee, Douglas C.; Bandera, Cesar; Ghosal, Sugata; Rauss, Patrick J.

    1996-06-01

    This paper presents a target detection and interrogation techniques for a foveal automatic target recognition (ATR) system based on the hierarchical scale-space processing of imagery from a rectilinear tessellated multiacuity retinotopology. Conventional machine vision captures imagery and applies early vision techniques with uniform resolution throughout the field-of-view (FOV). In contrast, foveal active vision features graded acuity imagers and processing coupled with context sensitive gaze control, analogous to that prevalent throughout vertebrate vision. Foveal vision can operate more efficiently in dynamic scenarios with localized relevance than uniform acuity vision because resolution is treated as a dynamically allocable resource. Foveal ATR exploits the difference between detection and recognition resolution requirements and sacrifices peripheral acuity to achieve a wider FOV (e.g. faster search), greater localized resolution where needed (e.g., more confident recognition at the fovea), and faster frame rates (e.g., more reliable tracking and navigation) without increasing processing requirements. The rectilinearity of the retinotopology supports a data structure that is a subset of the image pyramid. This structure lends itself to multiresolution and conventional 2-D algorithms, and features a shift invariance of perceived target shape that tolerates sensor pointing errors and supports multiresolution model-based techniques. The detection technique described in this paper searches for regions-of- interest (ROIs) using the foveal sensor's wide FOV peripheral vision. ROIs are initially detected using anisotropic diffusion filtering and expansion template matching to a multiscale Zernike polynomial-based target model. Each ROI is then interrogated to filter out false target ROIs by sequentially pointing a higher acuity region of the sensor at each ROI centroid and conducting a fractal dimension test that distinguishes targets from structured clutter.

  11. Influence of geometry on mechanical properties of bio-inspired silica-based hierarchical materials.

    PubMed

    Dimas, Leon S; Buehler, Markus J

    2012-09-01

    Diatoms, bone, nacre and deep-sea sponges are mineralized natural structures found abundantly in nature. They exhibit mechanical properties on par with advanced engineering materials, yet their fundamental building blocks are brittle and weak. An intriguing characteristic of these structures is their heterogeneous distribution of mechanical properties. Specifically, diatoms exhibit nanoscale porosity in specific geometrical configurations to create regions with distinct stress strain responses, notably based on a single and simple building block, silica. The study reported here, using models derived from first principles based full atomistic studies with the ReaxFF reactive force field, focuses on the mechanics and deformation mechanisms of silica-based nanocomposites inspired by mineralized structures. We examine single edged notched tensile specimens and analyze stress and strain fields under varied sample size in order to gain fundamental insights into the deformation mechanisms of structures with distinct ordered arrangements of soft and stiff phases. We find that hierarchical arrangements of silica nanostructures markedly change the stress and strain transfer in the samples. The combined action of strain transfer in the deformable phase, and stress transfer in the strong phase, acts synergistically to reduce the intensity of stress concentrations around a crack tip, and renders the resulting composites less sensitive to the presence of flaws, for certain geometrical configurations it even leads to stable crack propagation. A systematic study allows us to identify composite structures with superior fracture mechanical properties relative to their constituents, akin to many natural biomineralized materials that turn the weaknesses of building blocks into a strength of the overall system. PMID:22740585

  12. Hierarchical ensemble of background models for PTZ-based video surveillance.

    PubMed

    Liu, Ning; Wu, Hefeng; Lin, Liang

    2015-01-01

    In this paper, we study a novel hierarchical background model for intelligent video surveillance with the pan-tilt-zoom (PTZ) camera, and give rise to an integrated system consisting of three key components: background modeling, observed frame registration, and object tracking. First, we build the hierarchical background model by separating the full range of continuous focal lengths of a PTZ camera into several discrete levels and then partitioning the wide scene at each level into many partial fixed scenes. In this way, the wide scenes captured by a PTZ camera through rotation and zoom are represented by a hierarchical collection of partial fixed scenes. A new robust feature is presented for background modeling of each partial scene. Second, we locate the partial scenes corresponding to the observed frame in the hierarchical background model. Frame registration is then achieved by feature descriptor matching via fast approximate nearest neighbor search. Afterwards, foreground objects can be detected using background subtraction. Last, we configure the hierarchical background model into a framework to facilitate existing object tracking algorithms under the PTZ camera. Foreground extraction is used to assist tracking an object of interest. The tracking outputs are fed back to the PTZ controller for adjusting the camera properly so as to maintain the tracked object in the image plane. We apply our system on several challenging scenarios and achieve promising results.

  13. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    NASA Astrophysics Data System (ADS)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  14. Hierarchical CaCO3 chromatography: a stationary phase based on biominerals.

    PubMed

    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.

  15. A Hierarchical Clustering Methodology for the Estimation of Toxicity

    EPA Science Inventory

    A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

  16. Systematic hierarchical coarse-graining with the inverse Monte Carlo method

    SciTech Connect

    Lyubartsev, Alexander P.; Naômé, Aymeric; Vercauteren, Daniel P.; Laaksonen, Aatto

    2015-12-28

    We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730–3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile.

  17. Systematic hierarchical coarse-graining with the inverse Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Lyubartsev, Alexander P.; Naômé, Aymeric; Vercauteren, Daniel P.; Laaksonen, Aatto

    2015-12-01

    We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730-3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile.

  18. Synthesis of hierarchical porous carbon monoliths with incorporated metal-organic frameworks for enhancing volumetric based CO₂ capture capability.

    PubMed

    Qian, Dan; Lei, Cheng; Hao, Guang-Ping; Li, Wen-Cui; Lu, An-Hui

    2012-11-01

    This work aims to optimize the structural features of hierarchical porous carbon monolith (HCM) by incorporating the advantages of metal-organic frameworks (MOFs) (Cu₃(BTC)₂) to maximize the volumetric based CO₂ capture capability (CO₂ capacity in cm³ per cm³ adsorbent), which is seriously required for the practical application of CO₂ capture. The monolithic HCM was used as a matrix, in which Cu₃(BTC)₂ was in situ synthesized, to form HCM-Cu₃(BTC)₂ composites by a step-by-step impregnation and crystallization method. The resulted HCM-Cu₃(BTC)₂ composites, which retain the monolithic shape and exhibit unique hybrid structure features of both HCM and Cu₃(BTC)₂, show high CO₂ uptake of 22.7 cm³ cm⁻³ on a volumetric basis. This value is nearly as twice as the uptake of original HCM. The dynamic gas separation measurement of HCM-Cu₃(BTC)₂, using 16% (v/v) CO₂ in N₂ as feedstock, illustrates that CO₂ can be easily separated from N₂ under the ambient conditions and achieves a high separation factor for CO₂ over N₂, ranging from 67 to 100, reflecting a strongly competitive CO₂ adsorption by the composite. A facile CO₂ release can be realized by purging an argon flow through the fixed-bed adsorber at 25 °C, indicating the good regeneration ability.

  19. Reverse hierarchical PIV processing

    NASA Astrophysics Data System (ADS)

    Rohály, J.; Frigerio, F.; Hart, D. P.

    2002-07-01

    A novel hierarchical processing scheme is proposed to efficiently increase the spatial resolution and dynamic range of detecting particle image displacements in PIV images. The technique takes full advantage of the multi-resolution characteristic of the discrete correlation function by starting the processing at the smallest scale and, if necessary, gradually building correlation planes into larger interrogation areas based on the result of inter-level correlation correction and validation. It is shown that the algorithm can be implemented in both direct and FFT based correlation algorithms with greatly reduced computational complexity. The technique opens new perspectives for locally adaptive super-resolution processing taking flow field, seeding, and imaging anomalies into account. Processing at the lowest scale (e.g. pixel or particle image size) allows the combination of correlation planes on any shape. Hence the proposed reverse hierarchical processing represents interrogation area optimization both in size and shape in order to maximize the correlation plane signal-to-noise ratio. The method is successfully demonstrated on experimentally obtained images.

  20. A classification framework for content-based extraction of biomedical objects from hierarchically decomposed images

    NASA Astrophysics Data System (ADS)

    Thies, Christian; Schmidt Borreda, Marcel; Seidl, Thomas; Lehmann, Thomas M.

    2006-03-01

    Multiscale analysis provides a complete hierarchical partitioning of images into visually plausible regions. Each of them is formally characterized by a feature vector describing shape, texture and scale properties. Consequently, object extraction becomes a classification of the feature vectors. Classifiers are trained by relevant and irrelevant regions labeled as object and remaining partitions, respectively. A trained classifier is applicable to yet uncategorized partitionings to identify the corresponding region's classes. Such an approach enables retrieval of a-priori unknown objects within a point-and-click interface. In this work, the classification pipeline consists of a framework for data selection, feature selection, classifier training, classification of testing data, and evaluation. According to the no-free-lunch-theorem of supervised learning, the appropriate classification pipeline is determined experimentally. Therefore, each of the steps is varied by state-of-the-art methods and the respective classification quality is measured. Selection of training data from the ground truth is supported by bootstrapping, variance pooling, virtual training data, and cross validation. Feature selection for dimension reduction is performed by linear discriminant analysis, principal component analysis, and greedy selection. Competing classifiers are k-nearest-neighbor, Bayesian classifier, and the support vector machine. Quality is measured by precision and recall to reflect the retrieval task. A set of 105 hand radiographs from clinical routine serves as ground truth, where the metacarpal bones have been labeled manually. In total, 368 out of 39.017 regions are identified as relevant. In initial experiments for feature selection with the support vector machine have been obtained recall, precision and F-measure of 0.58, 0.67, and 0,62, respectively.

  1. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    USGS Publications Warehouse

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  2. Magnetron sputtering based direct fabrication of three dimensional CdTe hierarchical nanotrees exhibiting stable superhydrophobic property

    NASA Astrophysics Data System (ADS)

    Luo, Bingwei; Deng, Yuan; Wang, Yao; Shi, Yongming; Cao, Lili; Zhu, Wei

    2013-09-01

    Three dimensional CdTe hierarchical nanotrees are initially prepared by a simple one-step magnetron sputtering method without any templates or additives. The CdTe hierarchical nanotrees are constructed by the spear-like vertical trunks and horizontal branches with the diameters of about 100 nm at bottom and became cuspidal on the top. The particular nanostructure imparts these materials superhydrophobic property, and this property can be preserved after placing in air for 90 days, and is stable even after the ultraviolet light and X-ray irradiation, respectively. This study provides a simple strategy to achieve superhydrophobic properties for CdTe materials at lower temperature, which opens a new potential for CdTe solar cell with self-cleaning property.

  3. Femtosecond double-pulse fabrication of hierarchical nanostructures based on electron dynamics control for high surface-enhanced Raman scattering.

    PubMed

    Zhang, Ning; Li, Xin; Jiang, Lan; Shi, Xuesong; Li, Cong; Lu, Yongfeng

    2013-09-15

    This Letter presents a simple, efficient approach for high surface-enhanced Raman scattering by one-step controllable fabrication of hierarchical structures (nanoparticles+subwavelength ripples) on silicon substrates in silver nitrate solutions using femtosecond double pulses based on nanoscale electron dynamics control. As the delays of the double pulses increase from 0 fs to 1 ps, the hierarchical structures can be controlled with (1) nanoparticles--the number of nanoparticles in the range of 40-100 nm reaches the maximum at 800 fs and (2) ripples--the subwavelength ripples become intermittent with decreased ablation depths. The redistributed nanoparticles and the modified ripple structures contribute to the maximum enhancement factor of 2.2×10(8) (measured by 10(-6)  M rhodamine 6G solution) at the pulse delay of 800 fs.

  4. Hierarchical superhydrophobic/hydrophilic substrates based on nanospheres self-assembly onto micro-pillars

    NASA Astrophysics Data System (ADS)

    Ma, Pengcheng; Wang, Yifei; Feng, Kaijun; Chen, Zhuojie; Wu, Wengang

    2014-12-01

    We report a novel superhydrophobic/hydrophilic substrate with micro-/nano-hierarchical structures by mimicking the lotus effect. Intrinsic hydrophobic polystyrene nanospheres or intrinsic hydrophilic silica nanospheres, via evaporation-induced self-assembly, are deposited on the surfaces of silicon pillars, including on tops as well as sidewalls. The obtained hierarchical structures with the polystyrene nanosphere deposition could amplify its intrinsic hydrophobicity, because gas interstices between both the nanospheres and micro-pillars jointly enhance the liquid-gas contact fraction significantly. Related theoretical analysis indicates that such structures could easily achieve an apparent contact angle (CA) of higher than 150°. In experiments, we measure the apparent CA of such kinds of hierarchical structures with the silicon pillars in different geometries, and find that the maximum value is up to 163.8°, with a 3.2° slide angle. The hierarchical structures with the silica nanosphere deposition could amplify its intrinsic hydrophilicity as well, because the double structures greatly increase the liquid-solid contact area. The corresponding experiment results show that the apparent CA can be as low as 7.6°.

  5. Higher Order Testlet Response Models for Hierarchical Latent Traits and Testlet-Based Items

    ERIC Educational Resources Information Center

    Huang, Hung-Yu; Wang, Wen-Chung

    2013-01-01

    Both testlet design and hierarchical latent traits are fairly common in educational and psychological measurements. This study aimed to develop a new class of higher order testlet response models that consider both local item dependence within testlets and a hierarchy of latent traits. Due to high dimensionality, the authors adopted the Bayesian…

  6. Use of Hierarchical Hyper Concept Map in Web-Based Courses.

    ERIC Educational Resources Information Center

    Chang, Kuo-En; Sung, Yao-Ting; Chiou, Sheng-Kuang

    2002-01-01

    This study proposes a hierarchical hyper concept map (HHCM) course system which consists of a navigation map, concept maps, and hypermedia documents. Results of testing the HHCM as a course representation showed achievement was greater for students learning from the course represented by HHCM compared with those learning from a linearly…

  7. Hierarchical Auxetic Mechanical Metamaterials

    PubMed Central

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

    2015-01-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts. PMID:25670400

  8. Hierarchical Approximate Bayesian Computation

    PubMed Central

    Turner, Brandon M.; Van Zandt, Trisha

    2013-01-01

    Approximate Bayesian computation (ABC) is a powerful technique for estimating the posterior distribution of a model’s parameters. It is especially important when the model to be fit has no explicit likelihood function, which happens for computational (or simulation-based) models such as those that are popular in cognitive neuroscience and other areas in psychology. However, ABC is usually applied only to models with few parameters. Extending ABC to hierarchical models has been difficult because high-dimensional hierarchical models add computational complexity that conventional ABC cannot accommodate. In this paper we summarize some current approaches for performing hierarchical ABC and introduce a new algorithm called Gibbs ABC. This new algorithm incorporates well-known Bayesian techniques to improve the accuracy and efficiency of the ABC approach for estimation of hierarchical models. We then use the Gibbs ABC algorithm to estimate the parameters of two models of signal detection, one with and one without a tractable likelihood function. PMID:24297436

  9. Morphology-controlled hydrothermal synthesis of MnCO{sub 3} hierarchical superstructures with Schiff base as stabilizer

    SciTech Connect

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

    2011-11-15

    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: {yields} The most interesting in this work is the use of the greenhouse gases CO{sub 2} in atmosphere as carbonate ions source to precipitate with Mn{sup 2+} for producing MnCO{sub 3} crystals. {yields} This work is the first report related to the small organic molecule Schiff base as shape guiding-agent to produce different MnCO{sub 3} hierarchical superstructures. {yields} We are controllable synthesis of the MnCO{sub 3} hierarchical superstructures such as chrysanthemum, straw-bundle, dumbbell and sphere-like microcrystals. {yields} The as-prepared MnCO{sub 3} could be used precursor to fabricate the Mn{sub 2}O{sub 3} hierarchical superstructures after thermal decomposition at high temperature. -- Abstract: MnCO{sub 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{sub 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{sub 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{sub 3} superstructures was proposed based on the rod-dumbbell-sphere model. Furthermore, the MnCO{sub 3} as precursor could be further successfully transferred to Mn{sub 2}O{sub 3} microstructure after heating in the atmosphere at 500 {sup o}C, and the morphology of the Mn{sub 2}O{sub 3} was directly determined by that of the MnCO{sub 3} precursor.

  10. Hybrid hierarchical bio-based materials: Development and characterization through experimentation and computational simulations

    NASA Astrophysics Data System (ADS)

    Haq, Mahmoodul

    but seems to decrease toughness. Thus, the traditionally seen opposite measures of stiffness and toughness can be brought to an efficient balance through the combination of bio-resin and nanoclay. A multiscale computational approach, namely a multi-FE based approach, was implemented to the developed materials to extrapolate the experimental matrix, to provide insight into nano-scale behavior beyond measurements and to hopefully serve as a tool for computational design of hybrid materials. Additionally, an enhanced RVE for modeling the three-phase material was determined by solving a topology optimization based material layout problem to determine the distribution of bio-resin, thereby allowing modeling the nanostructure in greater detail and closer to reality. Overall, eco-friendly, tailorable, cost-effective and multiscale reinforced bio-based composites were successfully developed. The improved multifaceted features possible for these sustainable bio-based materials are likely to increase their appeal for use in transportation and housing structural applications. Additionally, it is believed that the approach of understanding complex materials by integrating simulations and experiments, as attempted in this work, holds great promise, and a similar methodology can be applied for other types of hierarchical materials, thereby providing guidance in designing those materials.

  11. A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations

    PubMed Central

    Kurtz, Camille; Beaulieu, Christopher F.; Napel, Sandy; Rubin, Daniel L.

    2014-01-01

    Computer-assisted image retrieval applications could assist radiologist interpretations by identifying similar images in large archives as a means to providing decision support. However, the semantic gap between low-level image features and their high level semantics may impair the system performances. Indeed, it can be challenging to comprehensively characterize the images using low-level imaging features to fully capture the visual appearance of diseases on images, and recently the use of semantic terms has been advocated to provide semantic descriptions of the visual contents of images. However, most of the existing image retrieval strategies do not consider the intrinsic properties of these terms during the comparison of the images beyond treating them as simple binary (presence/absence) features. We propose a new framework that includes semantic features in images and that enables retrieval of similar images in large databases based on their semantic relations. It is based on two main steps: (1) annotation of the images with semantic terms extracted from an ontology, and (2) evaluation of the similarity of image pairs by computing the similarity between the terms using the Hierarchical Semantic-Based Distance (HSBD) coupled to an ontological measure. The combination of these two steps provides a means of capturing the semantic correlations among the terms used to characterize the images that can be considered as a potential solution to deal with the semantic gap problem. We validate this approach in the context of the retrieval and the classification of 2D regions of interest (ROIs) extracted from computed tomographic (CT) images of the liver. Under this framework, retrieval accuracy of more than 0.96 was obtained on a 30-images dataset using the Normalized Discounted Cumulative Gain (NDCG) index that is a standard technique used to measure the effectiveness of information retrieval algorithms when a separate reference standard is available. Classification

  12. Converting 2D inorganic-organic ZnSe-DETA hybrid nanosheets into 3D hierarchical nanosheet-based ZnSe microspheres with enhanced visible-light-driven photocatalytic performances

    NASA Astrophysics Data System (ADS)

    Wu, Xuan; Xu, Rui; Zhu, Rongjiao; Wu, Rui; Zhang, Bin

    2015-05-01

    Engineering two-dimensional (2D) nanosheets into three-dimensional (3D) hierarchical structures is one of the great challenges in nanochemistry and materials science. We report a facile and simple chemical conversion route to fabricate 3D hierarchical nanosheet-based ZnSe microspheres by using 2D inorganic-organic hybrid ZnSe-DETA (DETA = diethylenetriamine) nanosheets as the starting precursors. The conversion mechanism involves the controlled depletion of the organic-component (DETA) from the hybrid precursors and the subsequent self-assembly of the remnant inorganic-component (ZnSe). The transformation reaction of ZnSe-DETA nanosheets is mainly influenced by the concentration of DETA in the reaction solution. We demonstrated that this organic-component depletion method could be extended to the synthesis of other hierarchical structures of metal sulfides. In addition, the obtained hierarchical nanosheet-based ZnSe microspheres exhibited outstanding performance in visible light photocatalytic degradation of methyl orange and were highly active for photocatalytic H2 production.Engineering two-dimensional (2D) nanosheets into three-dimensional (3D) hierarchical structures is one of the great challenges in nanochemistry and materials science. We report a facile and simple chemical conversion route to fabricate 3D hierarchical nanosheet-based ZnSe microspheres by using 2D inorganic-organic hybrid ZnSe-DETA (DETA = diethylenetriamine) nanosheets as the starting precursors. The conversion mechanism involves the controlled depletion of the organic-component (DETA) from the hybrid precursors and the subsequent self-assembly of the remnant inorganic-component (ZnSe). The transformation reaction of ZnSe-DETA nanosheets is mainly influenced by the concentration of DETA in the reaction solution. We demonstrated that this organic-component depletion method could be extended to the synthesis of other hierarchical structures of metal sulfides. In addition, the obtained

  13. Hierarchical nanoporosity enhanced reversible capacity of bicontinuous nanoporous metal based Li-O2 battery

    PubMed Central

    Guo, Xianwei; Han, Jiuhui; Liu, Pan; Chen, Luyang; Ito, Yoshikazu; Jian, Zelang; Jin, Tienan; Hirata, Akihiko; Li, Fujun; Fujita, Takeshi; Asao, Naoki; Zhou, Haoshen; Chen, Mingwei

    2016-01-01

    High-energy-density rechargeable Li-O2 batteries are one of few candidates that can meet the demands of electric drive vehicles and other high-energy applications because of the ultra-high theoretical specific energy. However, the practical realization of the high rechargeable capacity is usually limited by the conflicted requirements for porous cathodes in high porosity to store the solid reaction products Li2O2 and large accessible surface area for easy formation and decomposition of Li2O2. Here we designed a hierarchical and bicontinuous nanoporous structure by introducing secondary nanopores into the ligaments of coarsened nanoporous gold by two-step dealloying. The hierarchical and bicontinuous nanoporous gold cathode provides high porosity, large accessible surface area and sufficient mass transport path for high capacity and long cycling lifetime of Li-O2 batteries. PMID:27640902

  14. Hierarchical nanoporosity enhanced reversible capacity of bicontinuous nanoporous metal based Li-O2 battery.

    PubMed

    Guo, Xianwei; Han, Jiuhui; Liu, Pan; Chen, Luyang; Ito, Yoshikazu; Jian, Zelang; Jin, Tienan; Hirata, Akihiko; Li, Fujun; Fujita, Takeshi; Asao, Naoki; Zhou, Haoshen; Chen, Mingwei

    2016-01-01

    High-energy-density rechargeable Li-O2 batteries are one of few candidates that can meet the demands of electric drive vehicles and other high-energy applications because of the ultra-high theoretical specific energy. However, the practical realization of the high rechargeable capacity is usually limited by the conflicted requirements for porous cathodes in high porosity to store the solid reaction products Li2O2 and large accessible surface area for easy formation and decomposition of Li2O2. Here we designed a hierarchical and bicontinuous nanoporous structure by introducing secondary nanopores into the ligaments of coarsened nanoporous gold by two-step dealloying. The hierarchical and bicontinuous nanoporous gold cathode provides high porosity, large accessible surface area and sufficient mass transport path for high capacity and long cycling lifetime of Li-O2 batteries. PMID:27640902

  15. Hierarchical surface atomic structure of a manganese-based spinel cathode for lithium-ion batteries.

    PubMed

    Lee, Sanghan; Yoon, Gabin; Jeong, Minseul; Lee, Min-Joon; Kang, Kisuk; Cho, Jaephil

    2015-01-19

    The increasing use of lithium-ion batteries (LIBs) in high-power applications requires improvement of their high-temperature electrochemical performance, including their cyclability and rate capability. Spinel lithium manganese oxide (LiMn2O4) is a promising cathode material because of its high stability and abundance. However, it exhibits poor cycling performance at high temperatures owing to Mn dissolution. Herein we show that when stoichiometric lithium manganese oxide is coated with highly doped spinels, the resulting epitaxial coating has a hierarchical atomic structure consisting of cubic-spinel, tetragonal-spinel, and layered structures, and no interfacial phase is formed. In a practical application of the coating to doped spinel, the material retained 90% of its capacity after 800 cycles at 60 °C. Thus, the formation of an epitaxial coating with a hierarchical atomic structure could enhance the electrochemical performance of LIB cathode materials while preventing large losses in capacity.

  16. Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

    NASA Technical Reports Server (NTRS)

    Menasce, Daniel A.; Pentakalos, Odysseas I.

    1995-01-01

    Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

  17. Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

    NASA Astrophysics Data System (ADS)

    Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

    2014-12-01

    The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key 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 characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

  18. Hierarchical nanosheet-based Bi2MoO6 nanotubes with remarkably improved electrochemical performance

    NASA Astrophysics Data System (ADS)

    Ma, Ying; Jia, Yulong; Wang, Lina; Yang, Min; Bi, Yingpu; Qi, Yanxing

    2016-11-01

    In this work, novel hierarchical Bi2MoO6 nanotubes constructed from interconnected nanosheets have been fabricated and investigated as a high-performance electrochemical material. A facile template-engaged strategy has been utilized to controllably synthesize Bi2MoO6 nanotubes by a reflux reaction. The nanotubes with a high surface area of 68.96 m2/g were constructed of highly ordered ultrathin nanosheets with a thickness of about 5 nm. Benefitting from the structural advantages including ultrathin nanosheets, large exposed surface, and unique three-dimensional tubular structure, the as-obtained hierarchical Bi2MoO6 nanotubes exhibit excellent electrochemical performance. The specific capacitance of the hierarchical nanotubes can be up to 171.3 F g-1 at a current density of 0.585 A g-1 and excellent stability with 92.4% capacitance retention after 1000 cycles, which is much better than that of nanosheets (18.7 F g-1 at a current density of 0.585 A g-1, 69.5% capacitance retention).

  19. Hierarchical segmentation-based image coding using hybrid quad-binary trees.

    PubMed

    Kassim, Ashraf A; Lee, Wei Siong; Zonoobi, Dornoosh

    2009-06-01

    A novel segmentation-based image approximation and coding technique is proposed. A hybrid quad-binary (QB) tree structure is utilized to efficiently model and code geometrical information within images. Compared to other tree-based representation such as wedgelets, the proposed QB-tree based method is more efficient for a wide range of contour features such as junctions, corners and ridges, especially at low bit rates.

  20. Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

    NASA Astrophysics Data System (ADS)

    Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

    2015-12-01

    Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

  1. Parallel hierarchical radiosity rendering

    SciTech Connect

    Carter, M.

    1993-07-01

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

  2. Hierarchical Bayesian Models of Subtask Learning

    ERIC Educational Resources Information Center

    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…

  3. Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset.

    PubMed

    Leutheuser, Heike; Schuldhaus, Dominik; Eskofier, Bjoern M

    2013-01-01

    Insufficient physical activity is the 4th leading risk factor for mortality. Methods for assessing the individual daily life activity (DLA) are of major interest in order to monitor the current health status and to provide feedback about the individual quality of life. The conventional assessment of DLAs with self-reports induces problems like reliability, validity, and sensitivity. The assessment of DLAs with small and light-weight wearable sensors (e.g. inertial measurement units) provides a reliable and objective method. State-of-the-art human physical activity classification systems differ in e.g. the number and kind of sensors, the performed activities, and the sampling rate. Hence, it is difficult to compare newly proposed classification algorithms to existing approaches in literature and no commonly used dataset exists. We generated a publicly available benchmark dataset for the classification of DLAs. Inertial data were recorded with four sensor nodes, each consisting of a triaxial accelerometer and a triaxial gyroscope, placed on wrist, hip, chest, and ankle. Further, we developed a novel, hierarchical, multi-sensor based classification system for the distinction of a large set of DLAs. Our hierarchical classification system reached an overall mean classification rate of 89.6% and was diligently compared to existing state-of-the-art algorithms using our benchmark dataset. For future research, the dataset can be used in the evaluation process of new classification algorithms and could speed up the process of getting the best performing and most appropriate DLA classification system.

  4. Microparticles with hierarchical porosity

    SciTech Connect

    Petsev, Dimiter N; Atanassov, Plamen; Pylypenko, Svitlana; Carroll, Nick; Olson, Tim

    2012-12-18

    The present disclosure provides oxide microparticles with engineered hierarchical porosity and methods of manufacturing the same. Also described are structures that are formed by templating, impregnating, and/or precipitating the oxide microparticles and method for forming the same. Suitable applications include catalysts, electrocatalysts, electrocatalysts support materials, capacitors, drug delivery systems, sensors and chromatography.

  5. Hierarchical Ada robot programming system (HARPS)- A complete and working telerobot control system based on the NASREM model

    NASA Technical Reports Server (NTRS)

    Leake, Stephen; Green, Tom; Cofer, Sue; Sauerwein, Tim

    1989-01-01

    HARPS is a telerobot control system that can perform some simple but useful tasks. This capability is demonstrated by performing the ORU exchange demonstration. HARPS is based on NASREM (NASA Standard Reference Model). All software is developed in Ada, and the project incorporates a number of different CASE (computer-aided software engineering) tools. NASREM was found to be a valid and useful model for building a telerobot control system. Its hierarchical and distributed structure creates a natural and logical flow for implementing large complex robust control systems. The ability of Ada to create and enforce abstraction enhanced the implementation of such control systems.

  6. Catechol-based layer-by-layer assembly of composite coatings: a versatile platform to hierarchical nano-materials.

    PubMed

    Wang, C X; Braendle, A; Menyo, M S; Pester, C W; Perl, E E; Arias, I; Hawker, C J; Klinger, D

    2015-08-21

    Inspired by the marine mussel's ability to adhere to surfaces underwater, an aqueous catechol-based dip coating platform was developed. Using a catechol-functionalized polyacrylamide binder in combination with inorganic nanoparticles enables the facile fabrication of robust composite coatings via a layer-by-layer process. This modular assembly of well-defined building blocks provides a versatile alternative to electrostatic driven approaches with layer thickness and refractive indices being readily tunable. The platform nature of this approach enables the fabrication of hierarchically ordered nano-materials such as Bragg stacks.

  7. Packaging Glass with a Hierarchically Nanostructured Surface: A Universal Method to Achieve Self-Cleaning Omnidirectional Solar Cells.

    PubMed

    Lin, Chin-An; Tsai, Meng-Lin; Wei, Wan-Rou; Lai, Kun-Yu; He, Jr-Hau

    2016-01-26

    Fused-silica packaging glass fabricated with a hierarchical structure by integrating small (ultrathin nanorods) and large (honeycomb nanowalls) structures was demonstrated with exceptional light-harvesting solar performance, which is attributed to the subwavelength feature of the nanorods and an efficient scattering ability of the honeycomb nanowalls. Si solar cells covered with the hierarchically structured packaging glass exhibit enhanced conversion efficiency by 5.2% at normal incidence, and the enhancement went up to 46% at the incident angle of 60°. The hierarchical structured packaging glass shows excellent self-cleaning characteristics: 98.8% of the efficiency is maintained after 6 weeks of outdoor exposure, indicating that the nanostructured surface effectively repels polluting dust/particles. The presented self-cleaning omnidirectional light-harvesting design using the hierarchical structured packaging glass is a potential universal scheme for practical solar applications. PMID:26623934

  8. Hierarchical dynamic allocation procedures based on modified Zelen's approach in multiregional studies with unequal allocation.

    PubMed

    Kuznetsova, Olga M; Tymofyeyev, Yevgen

    2014-01-01

    Morrissey, McEntegart, and Lang (2010) showed that in multicenter studies with equal allocation to several treatment arms, the modified Zelen's approach provides excellent within-center and across-study balance in treatment assignments. In this article, hierarchical balancing procedures for equal allocation to more than two arms (with some elements different from earlier versions) and their unequal allocation expansions that incorporate modified Zelen's approach at the center level are described. The balancing properties of the described procedures for a case study of a multiregional clinical trial with 1:2 allocation where balance within regions as well as in other covariates is required are examined through simulations.

  9. A Hierarchical WENO Reconstructed Discontinuous Galerkin Method for Computing Shock Waves

    NASA Astrophysics Data System (ADS)

    Xia, Y.; Frisbey, M.; Luo, H.

    The discontinuous Galerkin (DG) methods[1] have recently become popular for the solution of systems of conservation laws because of their several attractive features such as easy extension to and compact stencil for higher-order (> 2nd) approximation, flexibility in handling arbitrary types of grids for complex geometries, and amenability to parallelization and hp-adaptation. However, the DG Methods have their own share weaknesses. In particular, how to effectively control spurious oscillations in the presence of strong discontinuities, and how to reduce the computing costs and storage requirements for the DGM remain the two most challenging and unresolved issues in the DGM.

  10. Multi-scale Properties and Processes in Hierarchically-Structured Organic-Inorganic Solids and Surface-Based Microfluidic Systems

    NASA Astrophysics Data System (ADS)

    Messinger, Robert James

    Hierarchically-structured materials and surface-based microfluidic systems exhibit diverse properties that are inherently multi-scale in origin. In particular, different molecular, mesoscopic, and micron-scale properties and processes are often correlated and collectively account for many properties of interest, such as bulk catalytic activities or electrokinetic flow rates. However, such properties and processes often exhibit complex relationships over the different length scales that are not well understood, and consequently, difficult to control. Establishing correlations between them has been challenging, in part due to the difficulty of rigorously characterizing complex, heterogeneous materials and surface-based microfluidic experiments over multiple length scales, particularly at the molecular and mesoscopic levels. Herein, new multi-scale understanding and correlations have been established for different hierarchically-structured organic-inorganic solids or surface-based microfluidic systems, enabling control of material or device properties over discrete length scales. The molecular-level compositions, structures, interactions, and dynamics have been measured in diverse hierarchically-structured materials, such as mesostructured zeolites, mesostructured organosilicas, and organosiloxane foams, and subsequently correlated with their meso- and macroscopic material structures and properties. The results reveal new insights on the molecular-level interactions that govern their syntheses, the resulting local compositions and material structures, and the relationships among material properties over multiple characteristic length scales. Multi-dimensional solid-state nuclear magnetic resonance (NMR) spectroscopy is a cornerstone of these investigations, which enables correlative measurements in multiple frequency dimensions of the through-space or through-bond interactions between the constituent nuclei within the different materials. Other multi

  11. Split-remerge method for eliminating processing window artifacts in recursive hierarchical segmentation

    NASA Technical Reports Server (NTRS)

    Tilton, James C. (Inventor)

    2010-01-01

    A method, computer readable storage, and apparatus for implementing recursive segmentation of data with spatial characteristics into regions including splitting-remerging of pixels with contagious region designations and a user controlled parameter for providing a preference for merging adjacent regions to eliminate window artifacts.

  12. Marine habitat classification for ecosystem-based management: a proposed hierarchical framework.

    PubMed

    Guarinello, Marisa L; Shumchenia, Emily J; King, John W

    2010-04-01

    Creating a habitat classification and mapping system for marine and coastal ecosystems is a daunting challenge due to the complex array of habitats that shift on various spatial and temporal scales. To meet this challenge, several countries have, or are developing, national classification systems and mapping protocols for marine habitats. To be effectively applied by scientists and managers it is essential that classification systems be comprehensive and incorporate pertinent physical, geological, biological, and anthropogenic habitat characteristics. Current systems tend to provide over-simplified conceptual structures that do not capture biological habitat complexity, marginalize anthropogenic features, and remain largely untested at finer scales. We propose a multi-scale hierarchical framework with a particular focus on finer scale habitat classification levels and conceptual schematics to guide habitat studies and management decisions. A case study using published data is included to compare the proposed framework with existing schemes. The example demonstrates how the proposed framework's inclusion of user-defined variables, a combined top-down and bottom-up approach, and multi-scale hierarchical organization can facilitate examination of marine habitats and inform management decisions.

  13. Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

    NASA Technical Reports Server (NTRS)

    Caines, P. E.

    1999-01-01

    The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

  14. Marine Habitat Classification for Ecosystem-Based Management: A Proposed Hierarchical Framework

    NASA Astrophysics Data System (ADS)

    Guarinello, Marisa L.; Shumchenia, Emily J.; King, John W.

    2010-04-01

    Creating a habitat classification and mapping system for marine and coastal ecosystems is a daunting challenge due to the complex array of habitats that shift on various spatial and temporal scales. To meet this challenge, several countries have, or are developing, national classification systems and mapping protocols for marine habitats. To be effectively applied by scientists and managers it is essential that classification systems be comprehensive and incorporate pertinent physical, geological, biological, and anthropogenic habitat characteristics. Current systems tend to provide over-simplified conceptual structures that do not capture biological habitat complexity, marginalize anthropogenic features, and remain largely untested at finer scales. We propose a multi-scale hierarchical framework with a particular focus on finer scale habitat classification levels and conceptual schematics to guide habitat studies and management decisions. A case study using published data is included to compare the proposed framework with existing schemes. The example demonstrates how the proposed framework’s inclusion of user-defined variables, a combined top-down and bottom-up approach, and multi-scale hierarchical organization can facilitate examination of marine habitats and inform management decisions.

  15. A Rasch Hierarchical Measurement Model.

    ERIC Educational Resources Information Center

    Maier, Kimberly S.

    This paper describes a model that integrates an item response theory (IRT) Rasch model and a hierarchical linear model and presents a method of estimating model parameter values that does not rely on large-sample theory and normal approximations. The model resulting from the integration of a hierarchical linear model and the Rasch model allows one…

  16. Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

    NASA Astrophysics Data System (ADS)

    Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

    2015-05-01

    Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

  17. Converting 2D inorganic-organic ZnSe-DETA hybrid nanosheets into 3D hierarchical nanosheet-based ZnSe microspheres with enhanced visible-light-driven photocatalytic performances.

    PubMed

    Wu, Xuan; Xu, Rui; Zhu, Rongjiao; Wu, Rui; Zhang, Bin

    2015-06-01

    Engineering two-dimensional (2D) nanosheets into three-dimensional (3D) hierarchical structures is one of the great challenges in nanochemistry and materials science. We report a facile and simple chemical conversion route to fabricate 3D hierarchical nanosheet-based ZnSe microspheres by using 2D inorganic-organic hybrid ZnSe-DETA (DETA = diethylenetriamine) nanosheets as the starting precursors. The conversion mechanism involves the controlled depletion of the organic-component (DETA) from the hybrid precursors and the subsequent self-assembly of the remnant inorganic-component (ZnSe). The transformation reaction of ZnSe-DETA nanosheets is mainly influenced by the concentration of DETA in the reaction solution. We demonstrated that this organic-component depletion method could be extended to the synthesis of other hierarchical structures of metal sulfides. In addition, the obtained hierarchical nanosheet-based ZnSe microspheres exhibited outstanding performance in visible light photocatalytic degradation of methyl orange and were highly active for photocatalytic H2 production.

  18. Unified method for the total pore volume and pore size distribution of hierarchical zeolites from argon adsorption and mercury intrusion.

    PubMed

    Kenvin, Jeffrey; Jagiello, Jacek; Mitchell, Sharon; Pérez-Ramírez, Javier

    2015-02-01

    A generalized approach to determine the complete distribution of macropores, mesopores, and micropores from argon adsorption and mercury porosimetry is developed and validated for advanced zeolite catalysts with hierarchically structured pore systems in powder and shaped forms. Rather than using a fragmented approach of simple overlays from individual techniques, a unified approach that utilizes a kernel constructed from model isotherms and model intrusion curves is used to calculate the complete pore size distribution and the total pore volume of the material. An added benefit of a single full-range pore size distribution is that the cumulative pore area and the area distribution are also obtained without the need for additional modeling. The resulting complete pore size distribution and the kernel accurately model both the adsorption isotherm and the mercury porosimetry. By bridging the data analysis of two primary characterization tools, this methodology fills an existing gap in the library of familiar methods for porosity assessment in the design of materials with multilevel porosity for novel technological applications.

  19. Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

    NASA Astrophysics Data System (ADS)

    Gendreau, Audrey

    Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing

  20. High Performance All-Solid-State Flexible Micro-Pseudocapacitor Based on Hierarchically Nanostructured Tungsten Trioxide Composite.

    PubMed

    Huang, Xuezhen; Liu, Hewei; Zhang, Xi; Jiang, Hongrui

    2015-12-23

    Microsupercapacitors (MSCs) are promising energy storage devices to power miniaturized portable electronics and microelectromechanical systems. With the increasing attention on all-solid-state flexible supercapacitors, new strategies for high-performance flexible MSCs are highly desired. Here, we demonstrate all-solid-state, flexible micropseudocapacitors via direct laser patterning on crack-free, flexible WO3/polyvinylidene fluoride (PVDF)/multiwalled carbon nanotubes (MWCNTs) composites containing high levels of porous hierarchically structured WO3 nanomaterials (up to 50 wt %) and limited binder (PVDF, <25 wt %). The work leads to an areal capacitance of 62.4 mF·cm(-2) and a volumetric capacitance of 10.4 F·cm(-3), exceeding that of graphene based flexible MSCs by a factor of 26 and 3, respectively. As a noncarbon based flexible MSC, hierarchically nanostructured WO3 in the narrow finger electrode is essential to such enhancement in energy density due to its pseudocapacitive property. The effects of WO3/PVDF/MWCNTs composite composition and the dimensions of interdigital structure on the performance of the flexible MSCs are investigated. PMID:26618406

  1. High Performance All-Solid-State Flexible Micro-Pseudocapacitor Based on Hierarchically Nanostructured Tungsten Trioxide Composite.

    PubMed

    Huang, Xuezhen; Liu, Hewei; Zhang, Xi; Jiang, Hongrui

    2015-12-23

    Microsupercapacitors (MSCs) are promising energy storage devices to power miniaturized portable electronics and microelectromechanical systems. With the increasing attention on all-solid-state flexible supercapacitors, new strategies for high-performance flexible MSCs are highly desired. Here, we demonstrate all-solid-state, flexible micropseudocapacitors via direct laser patterning on crack-free, flexible WO3/polyvinylidene fluoride (PVDF)/multiwalled carbon nanotubes (MWCNTs) composites containing high levels of porous hierarchically structured WO3 nanomaterials (up to 50 wt %) and limited binder (PVDF, <25 wt %). The work leads to an areal capacitance of 62.4 mF·cm(-2) and a volumetric capacitance of 10.4 F·cm(-3), exceeding that of graphene based flexible MSCs by a factor of 26 and 3, respectively. As a noncarbon based flexible MSC, hierarchically nanostructured WO3 in the narrow finger electrode is essential to such enhancement in energy density due to its pseudocapacitive property. The effects of WO3/PVDF/MWCNTs composite composition and the dimensions of interdigital structure on the performance of the flexible MSCs are investigated.

  2. A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

    PubMed

    Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

    2016-03-01

    Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results. PMID:26686458

  3. A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

    PubMed

    Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

    2016-03-01

    Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results.

  4. Interest rates hierarchical structure

    NASA Astrophysics Data System (ADS)

    Di Matteo, T.; Aste, T.; Hyde, S. T.; Ramsden, S.

    2005-09-01

    We propose a general method to study the hierarchical organization of financial data by embedding the structure of their correlations in metric graphs in multi-dimensional spaces. An application to two different sets of interest rates is discussed by constructing triangular embeddings on the sphere. Three-dimensional representations of these embeddings with the correct metric geometry are constructed and visualized. The resulting graphs contain the minimum spanning tree as a sub-graph and they preserve its hierarchical structure. This produces a clear cluster differentiation and allows us to compute new local and global topological quantities.

  5. Towards a sustainable manufacture of hierarchical zeolites.

    PubMed

    Verboekend, Danny; Pérez-Ramírez, Javier

    2014-03-01

    Hierarchical zeolites have been established as a superior type of aluminosilicate catalysts compared to their conventional (purely microporous) counterparts. An impressive array of bottom-up and top-down approaches has been developed during the last decade to design and subsequently exploit these exciting materials catalytically. However, the sustainability of the developed synthetic methods has rarely been addressed. This paper highlights important criteria to ensure the ecological and economic viability of the manufacture of hierarchical zeolites. Moreover, by using base leaching as a promising case study, we verify a variety of approaches to increase reactor productivity, recycle waste streams, prevent the combustion of organic compounds, and minimize separation efforts. By reducing their synthetic footprint, hierarchical zeolites are positioned as an integral part of sustainable chemistry.

  6. Hierarchical optimization for neutron scattering problems

    DOE PAGES

    Bao, Feng; Archibald, Rick; Bansal, Dipanshu; Delaire, Olivier

    2016-03-14

    In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

  7. Magnetically recyclable Bi/Fe-based hierarchical nanostructures via self-assembly for environmental decontamination

    NASA Astrophysics Data System (ADS)

    Hu, Zhong-Ting; Chen, Zhong; Goei, Ronn; Wu, Weiyi; Lim, Teik-Thye

    2016-06-01

    Pristine bismuth ferrite usually possesses weak magnetic properties (e.g., saturation magnetization Ms < 3 emu g-1) for practical magnetic separation applications. Herein, a superparamagnetic bismuth ferrite with coral-like hierarchical morphology (BFO-M) was fabricated through methanol solvothermal treatment of the as-prepared Bi2Fe4O9 nanoclusters (P-BFO). The BFO-M shows a higher Ms of ~31 emu g-1 compared to that of P-BFO treated in water (BFO-A), in ethanol (BFO-E) and in ethylene glycol (BFO-G). Compared to single-crystalline Bi2Fe4O9 (PS) and Bi2Fe4O9 clusters (NSP), BFO-M shows an excellent organic pollutant removal rate by virtue of its high adsorption capacity and catalytic activity when methyl orange (MO) is used as the model organic pollutant. BFO-M also exhibits good visible light photo-Fenton oxidation rates for pharmaceuticals and pesticides. Even at a low catalyst loading of 0.12 g L-1, the removal rate of organic pollutants (e.g., 5-fluorouracil, isoproturon) can be ~99% in 100 min under visible light irradiation. Besides, BFO-M is also a good adsorbent for different kinds of heavy metal ions (Pb(ii), Cr(iii), Cu(ii), As(v), etc.). For example, its maximal adsorption capacity for Pb(ii) is 214.5 mg g-1. The used BFO-M can be recovered via magnetic separation. The outstanding performances of BFO-M can be ascribed to its coral-like hierarchical morphology which consists of the self-assembly of 1D nanowires (~6 nm in diameter) and 2D ultrathin nanoflakes (~4.5 nm in thickness). A schematic illustration of its morphology formation is proposed.Pristine bismuth ferrite usually possesses weak magnetic properties (e.g., saturation magnetization Ms < 3 emu g-1) for practical magnetic separation applications. Herein, a superparamagnetic bismuth ferrite with coral-like hierarchical morphology (BFO-M) was fabricated through methanol solvothermal treatment of the as-prepared Bi2Fe4O9 nanoclusters (P-BFO). The BFO-M shows a higher Ms of ~31 emu g-1 compared to

  8. Bases for the synthesis of nanoparticulated silicas with bimodal hierarchical porosity

    NASA Astrophysics Data System (ADS)

    Huerta, Lenin; Guillem, Carmen; Latorre, Julio; Beltrán, Aurelio; Martínez-Máñez, Ramón; Marcos, M. Dolores; Beltrán, Daniel; Amorós, Pedro

    2006-08-01

    Porous silicas with pore sizes at two length scales (meso and large meso/macroporous) have been prepared through a one-pot surfactant assisted procedure by using a simple template agent and starting from silicon atrane complexes as hydrolytic inorganic precursors. The special organization of these bimodal porous silicas can be related to the nanometric character of their constituent mesoporous particles. Whereas the small intra-particle mesopore system is generated by the templating effect of the surfactant, the large pore system is defined by inter-particle voids. We have studied the effect of different procedural parameters on the small pore system and also on the nucleation and growth of the nanoparticles. The formation of these hierarchical materials is explained on the basis of kinetic (hydrolysis and condensation reaction rates) and thermodynamic (silica solubility) concepts.

  9. Spinal locomotor circuits develop using hierarchical rules based on motorneuron position and identity

    PubMed Central

    Hinckley, Christopher A.; Alaynick, William A.; Gallarda, Benjamin W.; Hayashi, Marito; Hilde, Kathryn L.; Driscoll, Shawn P.; Dekker, Joseph D.; Tucker, Haley O.; Sharpee, Tatyana O.; Pfaff, Samuel L.

    2015-01-01

    Summary The coordination of multi-muscle movements originates in the circuitry that regulates the firing patterns of spinal motorneurons. Sensory neurons rely on the musculotopic organization of motorneurons to establish orderly connections, prompting us to examine whether the intraspinal circuitry that coordinates motor activity likewise uses cell position as an internal wiring reference. We generated a motorneuron-specific GCaMP6f mouse line and employed two-photon imaging to monitor the activity of lumbar motorneurons. We show that the central pattern generator neural network coordinately drives rhythmic columnar-specific motorneuron bursts at distinct phases of the locomotor cycle. Using multiple genetic strategies to perturb the subtype identity and orderly position of motorneurons, we found that neurons retained their rhythmic activity - but cell position was decoupled from the normal phasing pattern underlying flexion and extension. These findings suggest a hierarchical basis of motor circuit formation that relies on increasingly stringent matching of neuronal identity and position. PMID:26335645

  10. Climate information based streamflow and rainfall forecasts for Huai River basin using hierarchical Bayesian modeling

    NASA Astrophysics Data System (ADS)

    Chen, X.; Hao, Z.; Devineni, N.; Lall, U.

    2014-04-01

    A Hierarchal Bayesian model is presented for one season-ahead forecasts of summer rainfall and streamflow using exogenous climate variables for east central China. The model provides estimates of the posterior forecasted probability distribution for 12 rainfall and 2 streamflow stations considering parameter uncertainty, and cross-site correlation. The model has a multi-level structure with regression coefficients modeled from a common multi-variate normal distribution resulting in partial pooling of information across multiple stations and better representation of parameter and posterior distribution uncertainty. Covariance structure of the residuals across stations is explicitly modeled. Model performance is tested under leave-10-out cross-validation. Frequentist and Bayesian performance metrics used include receiver operating characteristic, reduction of error, coefficient of efficiency, rank probability skill scores, and coverage by posterior credible intervals. The ability of the model to reliably forecast season-ahead regional summer rainfall and streamflow offers potential for developing adaptive water risk management strategies.

  11. Self-Healing Underwater Superoleophobic and Antibiofouling Coatings Based on the Assembly of Hierarchical Microgel Spheres.

    PubMed

    Chen, Kunlin; Zhou, Shuxue; Wu, Limin

    2016-01-26

    Marine biofouling has been plaguing people for thousands of years. While various strategies have been developed for antifouling (including superoleophobic) coatings, none of these exhibits self-healing properties because the bestowal of a zoetic self-repairing function to lifeless artificial water/solid interfacial materials is usually confronted with tremendous challenges. Here, we present a self-repairing underwater superoleophobic and antibiofouling coating through the self-assembly of hydrophilic polymeric chain modified hierarchical microgel spheres. The obtained surface material not only has excellent underwater superoleophobicity but also has very good subaqueous antibiofouling properties. More importantly, this surface material can recover the oil- and biofouling-resistant properties once its surface is mechanically damaged, similar to the skins of some marine organisms such as sharks or whales. This approach is feasible and easily mass-produced and could open a pathway and possibility for the fabrication of other self-healing functional water/solid interfacial materials. PMID:26687925

  12. Magnetically recyclable Bi/Fe-based hierarchical nanostructures via self-assembly for environmental decontamination.

    PubMed

    Hu, Zhong-Ting; Chen, Zhong; Goei, Ronn; Wu, Weiyi; Lim, Teik-Thye

    2016-07-01

    Pristine bismuth ferrite usually possesses weak magnetic properties (e.g., saturation magnetization Ms < 3 emu g(-1)) for practical magnetic separation applications. Herein, a superparamagnetic bismuth ferrite with coral-like hierarchical morphology (BFO-M) was fabricated through methanol solvothermal treatment of the as-prepared Bi2Fe4O9 nanoclusters (P-BFO). The BFO-M shows a higher Ms of ∼31 emu g(-1) compared to that of P-BFO treated in water (BFO-A), in ethanol (BFO-E) and in ethylene glycol (BFO-G). Compared to single-crystalline Bi2Fe4O9 (PS) and Bi2Fe4O9 clusters (NSP), BFO-M shows an excellent organic pollutant removal rate by virtue of its high adsorption capacity and catalytic activity when methyl orange (MO) is used as the model organic pollutant. BFO-M also exhibits good visible light photo-Fenton oxidation rates for pharmaceuticals and pesticides. Even at a low catalyst loading of 0.12 g L(-1), the removal rate of organic pollutants (e.g., 5-fluorouracil, isoproturon) can be ∼99% in 100 min under visible light irradiation. Besides, BFO-M is also a good adsorbent for different kinds of heavy metal ions (Pb(ii), Cr(iii), Cu(ii), As(v), etc.). For example, its maximal adsorption capacity for Pb(ii) is 214.5 mg g(-1). The used BFO-M can be recovered via magnetic separation. The outstanding performances of BFO-M can be ascribed to its coral-like hierarchical morphology which consists of the self-assembly of 1D nanowires (∼6 nm in diameter) and 2D ultrathin nanoflakes (∼4.5 nm in thickness). A schematic illustration of its morphology formation is proposed. PMID:27279493

  13. Water Extraction in High Resolution Remote Sensing Image Based on Hierarchical Spectrum and Shape Features

    NASA Astrophysics Data System (ADS)

    Li, Bangyu; Zhang, Hui; Xu, Fanjiang

    2014-03-01

    This paper addresses the problem of water extraction from high resolution remote sensing images (including R, G, B, and NIR channels), which draws considerable attention in recent years. Previous work on water extraction mainly faced two difficulties. 1) It is difficult to obtain accurate position of water boundary because of using low resolution images. 2) Like all other image based object classification problems, the phenomena of "different objects same image" or "different images same object" affects the water extraction. Shadow of elevated objects (e.g. buildings, bridges, towers and trees) scattered in the remote sensing image is a typical noise objects for water extraction. In many cases, it is difficult to discriminate between water and shadow in a remote sensing image, especially in the urban region. We propose a water extraction method with two hierarchies: the statistical feature of spectral characteristic based on image segmentation and the shape feature based on shadow removing. In the first hierarchy, the Statistical Region Merging (SRM) algorithm is adopted for image segmentation. The SRM includes two key steps: one is sorting adjacent regions according to a pre-ascertained sort function, and the other one is merging adjacent regions based on a pre-ascertained merging predicate. The sort step is done one time during the whole processing without considering changes caused by merging which may cause imprecise results. Therefore, we modify the SRM with dynamic sort processing, which conducts sorting step repetitively when there is large adjacent region changes after doing merging. To achieve robust segmentation, we apply the merging region with six features (four remote sensing image bands, Normalized Difference Water Index (NDWI), and Normalized Saturation-value Difference Index (NSVDI)). All these features contribute to segment image into region of object. NDWI and NSVDI are discriminate between water and some shadows. In the second hierarchy, we adopt

  14. An object-based approach to hierarchical classification of the Earth's topography from SRTM data

    NASA Astrophysics Data System (ADS)

    Eisank, C.; Dragut, L.

    2012-04-01

    Digital classification of the Earth's surface has significantly benefited from the availability of global DEMs and recent advances in image processing techniques. Such an innovative approach is object-based analysis, which integrates multi-scale segmentation and rule-based classification. Since the classification is based on spatially configured objects and no longer on solely thematically defined cells, the resulting landforms or landform types are represented in a more realistic way. However, up to now, the object-based approach has not been adopted for broad-scale topographic modelling. Existing global to almost-global terrain classification systems have been implemented on per cell schemes, accepting disadvantages such as the speckled character of outputs and the non-consideration of space. We introduce the first object-based method to automatically classify the Earth's surface as represented by the SRTM into a three-level hierarchy of topographic regions. The new method relies on the concept of decomposing land-surface complexity into ever more homogeneous domains. The SRTM elevation layer is automatically segmented and classified at three levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these recognised scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of the classes satisfy the regionalisation requirements of maximising internal homogeneity while minimising external homogeneity. Most objects have boundaries matching natural discontinuities at the regional level. The method is simple and fully

  15. High-performance sodium-ion pseudocapacitors based on hierarchically porous nanowire composites.

    PubMed

    Chen, Zheng; Augustyn, Veronica; Jia, Xilai; Xiao, Qiangfeng; Dunn, Bruce; Lu, Yunfeng

    2012-05-22

    Electrical energy storage plays an increasingly important role in modern society. Current energy storage methods are highly dependent on lithium-ion energy storage devices, and the expanded use of these technologies is likely to affect existing lithium reserves. The abundance of sodium makes Na-ion-based devices very attractive as an alternative, sustainable energy storage system. However, electrodes based on transition-metal oxides often show slow kinetics and poor cycling stability, limiting their use as Na-ion-based energy storage devices. The present paper details a new direction for electrode architectures for Na-ion storage. Using a simple hydrothermal process, we synthesized interpenetrating porous networks consisting of layer-structured V(2)O(5) nanowires and carbon nanotubes (CNTs). This type of architecture provides facile sodium insertion/extraction and fast electron transfer, enabling the fabrication of high-performance Na-ion pseudocapacitors with an organic electrolyte. Hybrid asymmetric capacitors incorporating the V(2)O(5)/CNT nanowire composites as the anode operated at a maximum voltage of 2.8 V and delivered a maximum energy of ∼40 Wh kg(-1), which is comparable to Li-ion-based asymmetric capacitors. The availability of capacitive storage based on Na-ion systems is an attractive, cost-effective alternative to Li-ion systems.

  16. Nanoclay-based hierarchical interconnected mesoporous CNT/PPy electrode with improved specific capacitance for high performance supercapacitors.

    PubMed

    Oraon, Ramesh; De Adhikari, Amrita; Tiwari, Santosh Kumar; Nayak, Ganesh Chandra

    2016-05-31

    A natural layered clay known as montmorillonite, a lamellar aluminosilicate with ∼1 nm thickness, has attracted intense attention in ongoing research due to its large natural abundance and environmental friendliness. Endowed with highly active surface sites the nanoclay has been extensively used in various fields viz. catalysis, biosensors etc. even though the role played by nanoclay on energy storage performance has not been elucidated. In this present work, a series of nanoclay (Closite 30B) based hierarchical open interconnected mesoporous electrode materials for supercapacitors (SCs) has been synthesized in the presence of carbon nanotubes (CNTs) and polypyrrole (PPy) by a facile in situ and ex situ approach. The role of nanoclay was explored as a dopant and its substantial doping effect exerted on the electrochemical performance towards energy storage was investigated. A coating of PPy over CNTs and nanoclay was confirmed from FESEM analysis which revealed the genesis of a nanoclay-supported hierarchical interconnected mesoporous framework. Furthermore, a PPy-coated CNT array in the presence of nanoclay was found to be highly porous with a high specific surface area without obvious deterioration. These interconnected structures can contribute to better penetration of electrolyte ions by shortening the path length for rapid transport of ions and electrons even at high rates. Cyclic voltammetry measurements revealed that nanoclay based in situ composite (CNP) and ex situ composite (CPN) exhibited a maximum specific capacitance of 425 F g(-1) and 317 F g(-1), respectively at a scan rate of 10 mV s(-1), which is comparatively higher than that of CP (i.e. PPy-coated CNTs) (76.77 F g(-1)). Similarly, a 273% increase in the specific capacitance of PPy was achieved after nanoclay incorporation in the nanocomposite NP (i.e. PPy-coated nanoclay) as compared to virgin PPy. These results are in good agreement with the specific capacitance performance by galvanostatic

  17. HERB: A production system for programming with hierarchical expert rule bases: User's manual, HERB Version 1. 0

    SciTech Connect

    Hummel, K.E.

    1987-12-01

    Expert systems are artificial intelligence programs that solve problems requiring large amounts of heuristic knowledge, based on years of experience and tradition. Production systems are domain-independent tools that support the development of rule-based expert systems. This document describes a general purpose production system known as HERB. This system was developed to support the programming of expert systems using hierarchically structured rule bases. HERB encourages the partitioning of rules into multiple rule bases and supports the use of multiple conflict resolution strategies. Multiple rule bases can also be placed on a system stack and simultaneously searched during each interpreter cycle. Both backward and forward chaining rules are supported by HERB. The condition portion of each rule can contain both patterns, which are matched with facts in a data base, and LISP expressions, which are explicitly evaluated in the LISP environment. Properties of objects can also be stored in the HERB data base and referenced within the scope of each rule. This document serves both as an introduction to the principles of LISP-based production systems and as a user's manual for the HERB system. 6 refs., 17 figs.

  18. Hierarchical, Job Content, and Double Plateaus: A Mixed-Method Study of Stress, Depression and Coping Responses

    ERIC Educational Resources Information Center

    McCleese, Carrie S.; Eby, Lillian T.; Scharlau, Elizabeth A.; Hoffman, Bethany H.

    2007-01-01

    Hierarchically, job content, and double plateaued employees from a variety of industries were surveyed regarding their experiences. Plateau-specific stress was higher than the stress experienced by the general population. Plateaued employees also reported more depression than the general population. Double plateaued employees reported higher…

  19. Social Influence on Information Technology Adoption and Sustained Use in Healthcare: A Hierarchical Bayesian Learning Method Analysis

    ERIC Educational Resources Information Center

    Hao, Haijing

    2013-01-01

    Information technology adoption and diffusion is currently a significant challenge in the healthcare delivery setting. This thesis includes three papers that explore social influence on information technology adoption and sustained use in the healthcare delivery environment using conventional regression models and novel hierarchical Bayesian…

  20. Hierarchical sulfur-based cathode materials with long cycle life for rechargeable lithium batteries.

    PubMed

    Wang, Jiulin; Yin, Lichao; Jia, Hao; Yu, Haitao; He, Yushi; Yang, Jun; Monroe, Charles W

    2014-02-01

    Composite materials of porous pyrolyzed polyacrylonitrile-sulfur@graphene nanosheet (pPAN-S@GNS) are fabricated through a bottom-up strategy. Microspherical particles are formed by spray drying of a mixed aqueous colloid of PAN nanoparticles and graphene nanosheets, followed by a simple heat treatment with elemental sulfur. The pPAN-S primary nanoparticles are wrapped homogeneously and loosely within a three-dimensional network of graphene nanosheets (GNS). The hierarchical pPAN-S@GNS composite shows a high reversible capacity of 1449.3 mAh g(-1) sulfur or 681.2 mAh g(-1) composite in the second cycle; after 300 cycles at a 0.2 C charge/discharge rate the capacity retention is 88.8 % of its initial reversible value. Additionally, the coulombic efficiency (CE) during cycling is near 100 %, apart from in the first cycle, in which CE is 81.1 %. A remarkable capacity of near 700 mAh g(-1) sulfur is obtained, even at a high discharge rate of 10 C. The superior performance of pPAN-S@GNS is ascribed to the spherical secondary GNS structure that creates an electronically conductive 3D framework and also reinforces structural stability. PMID:24155121

  1. A process-based hierarchical framework for monitoring glaciated alpine headwaters

    USGS Publications Warehouse

    Weekes, Anne A.; Torgersen, Christian E.; Montgomery, David R.; Woodward, Andrea; Bolton, Susan M.

    2012-01-01

    Recent studies have demonstrated the geomorphic complexity and wide range of hydrologic regimes found in alpine headwater channels that provide complex habitats for aquatic taxa. These geohydrologic elements are fundamental to better understand patterns in species assemblages and indicator taxa and are necessary to aquatic monitoring protocols that aim to track changes in physical conditions. Complex physical variables shape many biological and ecological traits, including life history strategies, but these mechanisms can only be understood if critical physical variables are adequately represented within the sampling framework. To better align sampling design protocols with current geohydrologic knowledge, we present a conceptual framework that incorporates regional-scale conditions, basin-scale longitudinal profiles, valley-scale glacial macroform structure, valley segment-scale (i.e., colluvial, alluvial, and bedrock), and reach-scale channel types. At the valley segment- and reach-scales, these hierarchical levels are associated with differences in streamflow and sediment regime, water source contribution and water temperature. Examples of linked physical-ecological hypotheses placed in a landscape context and a case study using the proposed framework are presented to demonstrate the usefulness of this approach for monitoring complex temporal and spatial patterns and processes in glaciated basins. This approach is meant to aid in comparisons between mountain regions on a global scale and to improve management of potentially endangered alpine species affected by climate change and other stressors.

  2. Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

    USGS Publications Warehouse

    Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

    2016-01-01

    Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

  3. Non-Markovian reduced dynamics based upon a hierarchical effective-mode representation

    SciTech Connect

    Burghardt, Irene; Martinazzo, Rocco; Hughes, Keith H.

    2012-10-14

    A reduced dynamics representation is introduced which is tailored to a hierarchical, Mori-chain type representation of a bath of harmonic oscillators which are linearly coupled to a subsystem. We consider a spin-boson system where a single effective mode is constructed so as to absorb all system-environment interactions, while the residual bath modes are coupled bilinearly to the primary mode and among each other. Using a cumulant expansion of the memory kernel, correlation functions for the primary mode are obtained, which can be suitably approximated by truncated chains representing the primary-residual mode interactions. A series of reduced-dimensional bath correlation functions is thus obtained, which can be expressed as Fourier-Laplace transforms of spectral densities that are given in truncated continued-fraction form. For a master equation which is second order in the system-bath coupling, the memory kernel is re-expressed in terms of local-in-time equations involving auxiliary densities and auxiliary operators.

  4. Sustainable and hierarchical porous Enteromorpha prolifera based carbon for CO2 capture.

    PubMed

    Zhang, Zhanquan; Wang, Ke; Atkinson, John D; Yan, Xinlong; Li, Xiang; Rood, Mark J; Yan, Zifeng

    2012-08-30

    Nitrogen-containing porous carbon was synthesized from an ocean pollutant, Enteromorpha prolifera, via hydrothermal carbonization and potassium hydroxide activation. Carbons contained as much as 2.6% nitrogen in their as-prepared state. Physical and chemical properties were characterized by XRD, N(2) sorption, FTIR, SEM, TEM, and elemental analysis. The carbon exhibited a hierarchical structure with interconnected microporosity, mesoporosity and macroporosity. Inorganic minerals in the carbon matrix contributed to the development of mesoporosity and macroporosity, functioning as an in situ hard template. The carbon manifested high CO(2) capacity and facile regeneration at room temperature. The CO(2) sorption performance was investigated in the range of 0-75°C. The dynamic uptake of CO(2) is 61.4 mg/g and 105 mg/g at 25°C and 0°C, respectively, using 15% CO(2) (v/v) in N(2). Meanwhile, regeneration under Ar at 25°C recovered 89% of the carbon's initial uptake after eight cycles. A piecewise model was employed to analyze the CO(2) adsorption kinetics; the Avrami model fit well with a correlation coefficient (R(2)) of 0.98 and 0.99 at 0°C and 25°C, respectively.

  5. Approximation of skewed interfaces with tensor-based model reduction procedures: Application to the reduced basis hierarchical model reduction approach

    NASA Astrophysics Data System (ADS)

    Ohlberger, Mario; Smetana, Kathrin

    2016-09-01

    In this article we introduce a procedure, which allows to recover the potentially very good approximation properties of tensor-based model reduction procedures for the solution of partial differential equations in the presence of interfaces or strong gradients in the solution which are skewed with respect to the coordinate axes. The two key ideas are the location of the interface either by solving a lower-dimensional partial differential equation or by using data functions and the subsequent removal of the interface of the solution by choosing the determined interface as the lifting function of the Dirichlet boundary conditions. We demonstrate in numerical experiments for linear elliptic equations and the reduced basis-hierarchical model reduction approach that the proposed procedure locates the interface well and yields a significantly improved convergence behavior even in the case when we only consider an approximation of the interface.

  6. Student conceptions about the DNA structure within a hierarchical organizational level: Improvement by experiment- and computer-based outreach learning.

    PubMed

    Langheinrich, Jessica; Bogner, Franz X

    2015-01-01

    As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module. To give participants the hierarchical organizational level which they have to draw, was a specific feature of our study. We introduced two objective category systems for analyzing drawings and inscriptions. Our results indicated a long- as well as a short-term increase in the level of conceptual understanding and in the number of drawn elements and their grades concerning the DNA structure. Consequently, we regard the "draw and write" technique as a tool for a teacher to get to know students' alternative conceptions. Furthermore, our study points the modification potential of hands-on and computer-supported learning modules.

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

    PubMed

    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.

  8. Simple synthesis of hierarchical porous carbon from Enteromorpha prolifera by a self-template method for supercapacitor electrodes

    NASA Astrophysics Data System (ADS)

    Gao, Yuan; Zhang, Wenli; Yue, Qinyan; Gao, Baoyu; Sun, Yuanyuan; Kong, Jiaojiao; Zhao, Pin

    2014-12-01

    Hierarchical porous carbons (HPCs) with high specific surface area are synthesized by a simple self-template strategy from the alage Enteromorpha prolifera (E. prolifera). The surface of the dried E. prolifera biomass contains carboxylic/hydroxyl groups and mineral salts, which can cooperate together to form metal-organic framework complexes. These salts and complexes can serve as self-templates to produce hierarchical porous structures during the activation process. The activated carbon is used to make an HPC electrode and the electrochemical properties of the supercapacitor fabricated from this HPC electrode are characterized by cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance spectroscopy in 6 mol L-1 KOH solution. The specific capacitance is 210 F g-1 at a current density of 3 A g-1. The good capacitive behavior is attributed to the high BET-surface area of 3332 m2 g-1, large pore volume of 2.46 cm3 g-1 and hierarchical porous structure (an abundance of interconnected mesopores, macropores and micropores). These results demonstrate that E. prolifera is a promising precursor to prepare high performance and low cost electrode materials for electrical double layer capacitors (EDLCs).

  9. Hierarchical distance-based fuzzy approach to evaluate urban water supply systems in a semi-arid region.

    PubMed

    Yekta, Tahereh Sadeghi; Khazaei, Mohammad; Nabizadeh, Ramin; Mahvi, Amir Hossein; Nasseri, Simin; Yari, Ahmad Reza

    2015-01-01

    Hierarchical distance-based fuzzy multi-criteria group decision making was served as a tool to evaluate the drinking water supply systems of Qom, a semi-arid city located in central part of Iran. A list of aspects consisting of 6 criteria and 35 sub-criteria were evaluated based on a linguistic term set by five decision-makers. Four water supply alternatives including "Public desalinated distribution system", "PET Bottled Drinking Water", "Private desalinated water suppliers" and "Household desalinated water units" were assessed based on criteria and sub-criteria. Data were aggregated and normalized to apply Performance Ratings of Alternatives. Also, the Performance Ratings of Alternatives were aggregated again to achieve the Aggregate Performance Ratings. The weighted distances from ideal solution and anti-ideal solution were calculated after secondary normalization. The proximity of each alternative to the ideal solution was determined as the final step. The alternatives were ranked based on the magnitude of ideal solutions. Results showed that "Public desalinated distribution system" was the most appropriate alternative to supply the drinking needs of Qom population. Also, "PET Bottled Drinking Water" was the second acceptable option. A novel classification of alternatives to satisfy the drinking water requirements was proposed which is applicable for the other cities located in semi-arid regions of Iran. The health issues were considered as independent criterion, distinct from the environmental issues. The constraints of high-tech alternatives were also considered regarding to the level of dependency on overseas.

  10. Hierarchical distance-based fuzzy approach to evaluate urban water supply systems in a semi-arid region.

    PubMed

    Yekta, Tahereh Sadeghi; Khazaei, Mohammad; Nabizadeh, Ramin; Mahvi, Amir Hossein; Nasseri, Simin; Yari, Ahmad Reza

    2015-01-01

    Hierarchical distance-based fuzzy multi-criteria group decision making was served as a tool to evaluate the drinking water supply systems of Qom, a semi-arid city located in central part of Iran. A list of aspects consisting of 6 criteria and 35 sub-criteria were evaluated based on a linguistic term set by five decision-makers. Four water supply alternatives including "Public desalinated distribution system", "PET Bottled Drinking Water", "Private desalinated water suppliers" and "Household desalinated water units" were assessed based on criteria and sub-criteria. Data were aggregated and normalized to apply Performance Ratings of Alternatives. Also, the Performance Ratings of Alternatives were aggregated again to achieve the Aggregate Performance Ratings. The weighted distances from ideal solution and anti-ideal solution were calculated after secondary normalization. The proximity of each alternative to the ideal solution was determined as the final step. The alternatives were ranked based on the magnitude of ideal solutions. Results showed that "Public desalinated distribution system" was the most appropriate alternative to supply the drinking needs of Qom population. Also, "PET Bottled Drinking Water" was the second acceptable option. A novel classification of alternatives to satisfy the drinking water requirements was proposed which is applicable for the other cities located in semi-arid regions of Iran. The health issues were considered as independent criterion, distinct from the environmental issues. The constraints of high-tech alternatives were also considered regarding to the level of dependency on overseas. PMID:26221535

  11. Three-dimensional sea-urchin-like hierarchical TiO{sub 2} microspheres synthesized by a one-pot hydrothermal method and their enhanced photocatalytic activity

    SciTech Connect

    Zhou, Yi; Huang, Yan; Li, Dang; He, Wenhong

    2013-07-15

    Graphical abstract: SEM images of the samples synthesized at different hydrothermal temperatures for 8 h: (a) 75; (b) 100; (c) 120; and (d) 140°C, followed by calcination at 450 °C for 2 h. Highlights: ► Effects of calcination temperature on the phase transformation were studied. ► Effects of hydrothermal temperature and time on the morphology growth were studied. ► A two-stage reaction mechanism for the formation was presented. ► The photocatalytic activity was evaluated under sunlight irradiation. ► Effects of calcination temperature on the photocatalytic activity were studied. - Abstract: Novel three-dimensional sea-urchin-like hierarchical TiO{sub 2} superstructures were synthesized on a Ti plate in a mixture of H{sub 2}O{sub 2} and NaOH aqueous solution by a facile one-pot hydrothermal method at a low temperature, followed by protonation and calcination. The results of series of electron microscopy characterizations suggested that the hierarchical TiO{sub 2} superstructures consisted of numerous one-dimensional nanostructures. The microspheres were approximately 2–4 μm in diameter, and the one-dimensional TiO{sub 2} nanostructures were up to 600–700 nm long. A two-stage reaction mechanism, i.e., initial growth and then assembly, was proposed for the formation of these architectures. The three-dimensional sea-urchin-like hierarchical TiO{sub 2} microstructures showed excellent photocatalytic activity for the degradation of Rhodamine B aqueous solution under sunlight irradiation, which was attributed to the special three-dimensional hierarchical superstructure, and increased number of surface active sites. This novel superstructure has promising use in practical aqueous purification.

  12. An Hierarchical approach to Big Data

    NASA Astrophysics Data System (ADS)

    Allen, Mark G.; Fernique, Pierre

    2015-08-01

    The increasing volumes of astronomical data require practical methods for data access, visualisation and analysis. Hierarchical methods based on sky tessellation techniques enable a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. The Hierarchical Progressive Survey (HiPS) scheme based on the HEALPix is able to describe images, catalogues and 3-dimensional data cubes and is a practical solution for managing large volumes of heterogeneous data. We present the development of HiPS, and its implementation for ~200 diverse data sets at the CDS and other data centres. We highlight the ease of implementation and the use of HiPS with Aladin Lite and other applications.

  13. Reduced quantum dynamics with arbitrary bath spectral densities: Hierarchical equations of motion based on several different bath decomposition schemes

    SciTech Connect

    Liu, Hao; Zhu, Lili; Bai, Shuming; Shi, Qiang

    2014-04-07

    We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly in the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.

  14. Efficacy of CBCT for assessment of impacted mandibular third molars: a review – based on a hierarchical model of evidence

    PubMed Central

    Wenzel, A

    2015-01-01

    A radiographic examination of mandibular third molars is meant to support the surgeon in establishing a treatment plan. For years panoramic (PAN) imaging has been the first choice method; however, where an overprojection is observed between the third molar and the mandibular canal and when specific signs suggest a close contact between the molar and the canal, CBCT may be indicated. The present review provides an evaluation of the efficacy of CBCT for assessment of mandibular third molars using a six-tiered hierarchical model by Fryback and Thornbury in 1991. Levels 1–3 include studies on low evidence levels mainly regarding the technical capabilities of a radiographic method and the diagnostic accuracy of the related images. Levels 4–6 include studies on a higher level of evidence and assess the diagnostic impact of a radiographic method on the treatment of the patient in addition to the outcome for the patient and society including cost calculations. Only very few high-evidence studies on the efficacy of CBCT for radiographic examination of mandibular third molars exist and, in conclusion, periapical or PAN examination is sufficient in most cases before removal of mandibular third molars. However, CBCT may be suggested when one or more signs for a close contact between the tooth and the canal are present in the two-dimensional image—if it is believed that CBCT will change the treatment or the treatment outcome for the patient. Further research on high-evidence levels is needed. PMID:25135317

  15. Reduced quantum dynamics with arbitrary bath spectral densities: hierarchical equations of motion based on several different bath decomposition schemes.

    PubMed

    Liu, Hao; Zhu, Lili; Bai, Shuming; Shi, Qiang

    2014-04-01

    We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly in the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.

  16. Supercapacitors Based on Three-Dimensional Hierarchical Graphene Aerogels with Periodic Macropores.

    PubMed

    Zhu, Cheng; Liu, Tianyu; Qian, Fang; Han, T Yong-Jin; Duoss, Eric B; Kuntz, Joshua D; Spadaccini, Christopher M; Worsley, Marcus A; Li, Yat

    2016-06-01

    Graphene is an atomically thin, two-dimensional (2D) carbon material that offers a unique combination of low density, exceptional mechanical properties, thermal stability, large surface area, and excellent electrical conductivity. Recent progress has resulted in macro-assemblies of graphene, such as bulk graphene aerogels for a variety of applications. However, these three-dimensional (3D) graphenes exhibit physicochemical property attenuation compared to their 2D building blocks because of one-fold composition and tortuous, stochastic porous networks. These limitations can be offset by developing a graphene composite material with an engineered porous architecture. Here, we report the fabrication of 3D periodic graphene composite aerogel microlattices for supercapacitor applications, via a 3D printing technique known as direct-ink writing. The key factor in developing these novel aerogels is creating an extrudable graphene oxide-based composite ink and modifying the 3D printing method to accommodate aerogel processing. The 3D-printed graphene composite aerogel (3D-GCA) electrodes are lightweight, highly conductive, and exhibit excellent electrochemical properties. In particular, the supercapacitors using these 3D-GCA electrodes with thicknesses on the order of millimeters display exceptional capacitive retention (ca. 90% from 0.5 to 10 A·g(-1)) and power densities (>4 kW·kg(-1)) that equal or exceed those of reported devices made with electrodes 10-100 times thinner. This work provides an example of how 3D-printed materials, such as graphene aerogels, can significantly expand the design space for fabricating high-performance and fully integrable energy storage devices optimized for a broad range of applications. PMID:26789202

  17. Metabolonote: A Wiki-Based Database for Managing Hierarchical Metadata of Metabolome Analyses

    PubMed Central

    Ara, Takeshi; Enomoto, Mitsuo; Arita, Masanori; Ikeda, Chiaki; Kera, Kota; Yamada, Manabu; Nishioka, Takaaki; Ikeda, Tasuku; Nihei, Yoshito; Shibata, Daisuke; Kanaya, Shigehiko; Sakurai, Nozomu

    2015-01-01

    Metabolomics – technology for comprehensive detection of small molecules in an organism – lags behind the other “omics” in terms of publication and dissemination of experimental data. Among the reasons for this are difficulty precisely recording information about complicated analytical experiments (metadata), existence of various databases with their own metadata descriptions, and low reusability of the published data, resulting in submitters (the researchers who generate the data) being insufficiently motivated. To tackle these issues, we developed Metabolonote, a Semantic MediaWiki-based database designed specifically for managing metabolomic metadata. We also defined a metadata and data description format, called “Togo Metabolome Data” (TogoMD), with an ID system that is required for unique access to each level of the tree-structured metadata such as study purpose, sample, analytical method, and data analysis. Separation of the management of metadata from that of data and permission to attach related information to the metadata provide advantages for submitters, readers, and database developers. The metadata are enriched with information such as links to comparable data, thereby functioning as a hub of related data resources. They also enhance not only readers’ understanding and use of data but also submitters’ motivation to publish the data. The metadata are computationally shared among other systems via APIs, which facilitate the construction of novel databases by database developers. A permission system that allows publication of immature metadata and feedback from readers also helps submitters to improve their metadata. Hence, this aspect of Metabolonote, as a metadata preparation tool, is complementary to high-quality and persistent data repositories such as MetaboLights. A total of 808 metadata for analyzed data obtained from 35 biological species are published currently. Metabolonote and related tools are available free of cost at http

  18. Supercapacitors Based on Three-Dimensional Hierarchical Graphene Aerogels with Periodic Macropores.

    PubMed

    Zhu, Cheng; Liu, Tianyu; Qian, Fang; Han, T Yong-Jin; Duoss, Eric B; Kuntz, Joshua D; Spadaccini, Christopher M; Worsley, Marcus A; Li, Yat

    2016-06-01

    Graphene is an atomically thin, two-dimensional (2D) carbon material that offers a unique combination of low density, exceptional mechanical properties, thermal stability, large surface area, and excellent electrical conductivity. Recent progress has resulted in macro-assemblies of graphene, such as bulk graphene aerogels for a variety of applications. However, these three-dimensional (3D) graphenes exhibit physicochemical property attenuation compared to their 2D building blocks because of one-fold composition and tortuous, stochastic porous networks. These limitations can be offset by developing a graphene composite material with an engineered porous architecture. Here, we report the fabrication of 3D periodic graphene composite aerogel microlattices for supercapacitor applications, via a 3D printing technique known as direct-ink writing. The key factor in developing these novel aerogels is creating an extrudable graphene oxide-based composite ink and modifying the 3D printing method to accommodate aerogel processing. The 3D-printed graphene composite aerogel (3D-GCA) electrodes are lightweight, highly conductive, and exhibit excellent electrochemical properties. In particular, the supercapacitors using these 3D-GCA electrodes with thicknesses on the order of millimeters display exceptional capacitive retention (ca. 90% from 0.5 to 10 A·g(-1)) and power densities (>4 kW·kg(-1)) that equal or exceed those of reported devices made with electrodes 10-100 times thinner. This work provides an example of how 3D-printed materials, such as graphene aerogels, can significantly expand the design space for fabricating high-performance and fully integrable energy storage devices optimized for a broad range of applications.

  19. Hierarchical regression for epidemiologic analyses of multiple exposures.

    PubMed Central

    Greenland, S

    1994-01-01

    Many epidemiologic investigations are designed to study the effects of multiple exposures. Most of these studies are analyzed either by fitting a risk-regression model with all exposures forced in the model, or by using a preliminary-testing algorithm, such as stepwise regression, to produce a smaller model. Research indicates that hierarchical modeling methods can outperform these conventional approaches. These methods are reviewed and compared to two hierarchical methods, empirical-Bayes regression and a variant here called "semi-Bayes" regression, to full-model maximum likelihood and to model reduction by preliminary testing. The performance of the methods in a problem of predicting neonatal-mortality rates are compared. Based on the literature to date, it is suggested that hierarchical methods should become part of the standard approaches to multiple-exposure studies. PMID:7851328

  20. Modular and hierarchical structure of social contact networks

    NASA Astrophysics Data System (ADS)

    Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

    2013-10-01

    Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

  1. The Supervised Hierarchical Dirichlet Process.

    PubMed

    Dai, Andrew M; Storkey, Amos J

    2015-02-01

    We propose the supervised hierarchical Dirichlet process (sHDP), a nonparametric generative model for the joint distribution of a group of observations and a response variable directly associated with that whole group. We compare the sHDP with another leading method for regression on grouped data, the supervised latent Dirichlet allocation (sLDA) model. We evaluate our method on two real-world classification problems and two real-world regression problems. Bayesian nonparametric regression models based on the Dirichlet process, such as the Dirichlet process-generalised linear models (DP-GLM) have previously been explored; these models allow flexibility in modelling nonlinear relationships. However, until now, hierarchical Dirichlet process (HDP) mixtures have not seen significant use in supervised problems with grouped data since a straightforward application of the HDP on the grouped data results in learnt clusters that are not predictive of the responses. The sHDP solves this problem by allowing for clusters to be learnt jointly from the group structure and from the label assigned to each group. PMID:26353239

  2. Hierarchical self-assembly of a biomimetic light-harvesting antenna based on DNA G-quadruplexes.

    PubMed

    Sancho Oltra, Núria; Browne, Wesley R; Roelfes, Gerard

    2013-02-11

    A new modular approach to an artificial light-harvesting antenna system is presented. The approach involves the hierarchical self-assembly of porphyrin acceptor molecules to G-quadruplexes tethered to coumarin donor moieties.

  3. Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

    PubMed Central

    2014-01-01

    This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

  4. Object-based task-level control: A hierarchical control architecture for remote operation of space robots

    NASA Technical Reports Server (NTRS)

    Stevens, H. D.; Miles, E. S.; Rock, S. J.; Cannon, R. H.

    1994-01-01

    Expanding man's presence in space requires capable, dexterous robots capable of being controlled from the Earth. Traditional 'hand-in-glove' control paradigms require the human operator to directly control virtually every aspect of the robot's operation. While the human provides excellent judgment and perception, human interaction is limited by low bandwidth, delayed communications. These delays make 'hand-in-glove' operation from Earth impractical. In order to alleviate many of the problems inherent to remote operation, Stanford University's Aerospace Robotics Laboratory (ARL) has developed the Object-Based Task-Level Control architecture. Object-Based Task-Level Control (OBTLC) removes the burden of teleoperation from the human operator and enables execution of tasks not possible with current techniques. OBTLC is a hierarchical approach to control where the human operator is able to specify high-level, object-related tasks through an intuitive graphical user interface. Infrequent task-level command replace constant joystick operations, eliminating communications bandwidth and time delay problems. The details of robot control and task execution are handled entirely by the robot and computer control system. The ARL has implemented the OBTLC architecture on a set of Free-Flying Space Robots. The capability of the OBTLC architecture has been demonstrated by controlling the ARL Free-Flying Space Robots from NASA Ames Research Center.

  5. Image Search Reranking With Hierarchical Topic Awareness.

    PubMed

    Tian, Xinmei; Yang, Linjun; Lu, Yijuan; Tian, Qi; Tao, Dacheng

    2015-10-01

    With much attention from both academia and industrial communities, visual search reranking has recently been proposed to refine image search results obtained from text-based image search engines. Most of the traditional reranking methods cannot capture both relevance and diversity of the search results at the same time. Or they ignore the hierarchical topic structure of search result. Each topic is treated equally and independently. However, in real applications, images returned for certain queries are naturally in hierarchical organization, rather than simple parallel relation. In this paper, a new reranking method "topic-aware reranking (TARerank)" is proposed. TARerank describes the hierarchical topic structure of search results in one model, and seamlessly captures both relevance and diversity of the image search results simultaneously. Through a structured learning framework, relevance and diversity are modeled in TARerank by a set of carefully designed features, and then the model is learned from human-labeled training samples. The learned model is expected to predict reranking results with high relevance and diversity for testing queries. To verify the effectiveness of the proposed method, we collect an image search dataset and conduct comparison experiments on it. The experimental results demonstrate that the proposed TARerank outperforms the existing relevance-based and diversified reranking methods.

  6. Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

    NASA Astrophysics Data System (ADS)

    León, Madeleine; Escalante-Ramirez, Boris

    2013-11-01

    Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

  7. Nanotribological and wetting performance of hierarchical patterns.

    PubMed

    Grewal, H S; Piao, Shuxue; Cho, Il-Joo; Jhang, Kyung-Young; Yoon, Eui-Sung

    2016-01-21

    Surface modification is a promising method to solve the tribological problems in microsystems. To modify the surface, we fabricated hierarchical patterns with different pitches of nano-scale features and different surface chemistries. Micro- and nano-patterns with similar geometrical configurations were also fabricated for comparison. The nano-tribological behavior of the patterns was investigated using an atomic force microscope at different relative humidity levels (5% to 80%) and applied normal loads (40 nN to 120 nN) under a constant sliding velocity. The results showed significant enhancement in the de-wetting and tribological performance of the hierarchical patterns compared with those of flat and micro- and nano-patterned surfaces. The PTFE-coated hierarchical patterns showed similar dynamic contact angles (advancing and receding) to those of the real lotus leaf. The influence of relative humidity on adhesion and friction behavior was found to be significant for all the tested surfaces. The tribological performance was improved as the pitch of the nano-scale geometry of the hierarchical pattern increased, even though the wetting property was not influenced significantly. A model was proposed based on the role of intermolecular force to explain the effect of the pitch of the hierarchical patterns on the adhesion and friction behavior. According to the model based on the molecular force, the contact between a ball and the patterned surface was a multi-asperity contact, contrary to the single-asperity contact predicted by the Johnson-Kendall-Roberts (JKR) and Maugis-Dugdale (MD) models. The strong intermolecular forces, which are activated in the confined spaces between the adjacent nano-pillars and the ball, contributed to the contact area and hence the adhesion and friction forces.

  8. Nanotribological and wetting performance of hierarchical patterns.

    PubMed

    Grewal, H S; Piao, Shuxue; Cho, Il-Joo; Jhang, Kyung-Young; Yoon, Eui-Sung

    2016-01-21

    Surface modification is a promising method to solve the tribological problems in microsystems. To modify the surface, we fabricated hierarchical patterns with different pitches of nano-scale features and different surface chemistries. Micro- and nano-patterns with similar geometrical configurations were also fabricated for comparison. The nano-tribological behavior of the patterns was investigated using an atomic force microscope at different relative humidity levels (5% to 80%) and applied normal loads (40 nN to 120 nN) under a constant sliding velocity. The results showed significant enhancement in the de-wetting and tribological performance of the hierarchical patterns compared with those of flat and micro- and nano-patterned surfaces. The PTFE-coated hierarchical patterns showed similar dynamic contact angles (advancing and receding) to those of the real lotus leaf. The influence of relative humidity on adhesion and friction behavior was found to be significant for all the tested surfaces. The tribological performance was improved as the pitch of the nano-scale geometry of the hierarchical pattern increased, even though the wetting property was not influenced significantly. A model was proposed based on the role of intermolecular force to explain the effect of the pitch of the hierarchical patterns on the adhesion and friction behavior. According to the model based on the molecular force, the contact between a ball and the patterned surface was a multi-asperity contact, contrary to the single-asperity contact predicted by the Johnson-Kendall-Roberts (JKR) and Maugis-Dugdale (MD) models. The strong intermolecular forces, which are activated in the confined spaces between the adjacent nano-pillars and the ball, contributed to the contact area and hence the adhesion and friction forces. PMID:26549103

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

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    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.

  11. Area-Based Socioeconomic Position and Adult Glioma: A Hierarchical Analysis of Surveillance Epidemiology and End Results Data

    PubMed Central

    Plascak, Jesse J.; Fisher, James L.

    2013-01-01

    Background Glioma rates vary by demographic factors and geo-political boundaries and this variation suggests higher glioma rates in groups of higher socioeconomic position. The primary goal of this analysis is to investigate the relationship between glioma and county socioeconomic position using U.S. Surveillance Epidemiology and End Results (SEER) data. Methods Cases were individuals 25+ years diagnosed with glioma between 2000 and 2006 and residing within the SEER-17 catchment area. County-, sex-, race-, age-specific rates were created in order to investigate individual-level associations (population data from U.S. Census 2000). A Bayesian hierarchical Poisson spatial conditionally autoregressive (CAR) model was utilized to simultaneously estimate individual- and county-level associations while controlling for county spatial dependence. Results Those residing in counties of the second, third, and fourth highest quartiles of socioeconomic position have glioma incidence rates that are 1.10 (95% CI: 1.02,1.19), 1.11 (95% CI: 1.02,1.20), 1.14 (95% CI: 1.05,1.23) times that of the first quartile, respectively. A CAR model properly controlled for error spatial dependence. Investigated lag times suggest year 2000 census data yields superior model fit. Conclusion Demographically adjusted rates of glioma are elevated in counties of higher socioeconomic position. More well-grounded theory concerning the glioma-socioeconomic position association along with socioeconomic data collected at multiple levels is recommended for future studies investigating this relationship. PMID:23585860

  12. Multifunctional substrate of Al alloy based on general hierarchical micro/nanostructures: superamphiphobicity and enhanced corrosion resistance

    PubMed Central

    Li, Xuewu; Shi, Tian; Liu, Cong; Zhang, Qiaoxin; Huang, Xingjiu

    2016-01-01

    Aluminum alloys are vulnerable to penetrating and peeling failures in seawater and preparing a barrier coating to isolate the substrate from corrosive medium is an effective anticorrosion method. Inspired by the lotus leaves effect, a wetting alloy surface with enhanced anticorrosion behavior has been prepared via etch, deposition, and low-surface-energy modification. Results indicate that excellent superamphiphobicity has been achieved after the modification of the constructed hierarchical labyrinth-like microstructures and dendritic nanostructures. The as-prepared surface is also found with good chemical stability and mechanical durability. Furthermore, superior anticorrosion behaviors of the resultant samples in seawater are investigated by electrochemical measurements. Due to trapped air in micro/nanostructures, the newly presented solid-air-liquid contacting interface can help to resist the seawater penetration by greatly reducing the interface interaction between corrosive ions and the superamphiphobic surface. Finally, an optimized two-layer perceptron artificial neural network is set up to model and predict the cause-and-effect relationship between preparation conditions and the anticorrosion parameters. This work provides a great potential to extend the applications of aluminum alloys especially in marine engineering fields. PMID:27775053

  13. A hierarchic approach to examining panArctic vegetation with a focus on the linkages between remote sensing and plot-based studies.

    NASA Astrophysics Data System (ADS)

    Walker, D. A.; Daniëls, F. J. A.; Alsos, I. G.; Bhatt, U. S.; Breen, A. L.; Buchhorn, M.; Bültmann, H.; Edwards, M. E.; Ehrich, D.; Epstein, H. E.; Gould, W. A.; Ims, R. A.; Meltofte, H.; Murray, D. F.; Raynolds, M. K.; Talbot, S. S.

    2015-12-01

    A circumpolar view of Arctic vegetation developed with the advent of satellite-derived remote-sensing products. Interpretations of what the revealed patterns mean are dependent on a foundation of in-situ plot-based observations. Despite the importance of ground-based observations, only a few areas have been intensively sampled and mapped, mainly in the vicinity of permanent Arctic observatories. Much of the information is project specific and is based on sampling protocols that are difficult to compare across sites. Here, we demonstrate a more consistent multi-level hierarchic approach for vegetation description and analysis at the Toolik Lake Field Station, Alaska. We advocate for a well-coordinated, interdisciplinary network of vegetation observation stations. Key recommendations include: (1) Complete local floras for many more areas in than presently exist. Species names should be standardized using the Pan-Arctic Flora. (2) Permanently marked and replicated vegetation monitoring plots in the full range of habitats at each station. Methods of establishing and monitoring the plots should include consistent internationally accepted standards for vegetation data collection, vegetation classification, plot markings, and standardized approaches to describe the local environment, including photo points showing the vegetation and soils up close and in landscape view. (3) Standardized approaches for collecting in-situ time-series of spectral data. Standardized methods for collecting and analyzing phytomass data are especially needed. (4) Interdisciplinary studies. Vegetation observations should be conducted in concert with observations of soils, permafrost, animals and ecosystem processes at the same plots. (5) Periodic (perhaps every 5-10 years) ground-based surveys. These should include surveys of species composition, canopy structure, biomass, leaf-area index, and NDVI, along with high-resolution satellite-based remote-sensing products at the same time.

  14. Large-scale preparation of indium-based infinite coordination polymer hierarchical nanostructures and their good capability for water treatment.

    PubMed

    Jin, Li-Na; Liu, Qing; Yang, Ying; Fu, Hong-Gang; Sun, Wei-Yin

    2014-07-15

    The removal of dyes in wastewater has been of much interest in the recent decades because dyes are stable, toxic and even potentially carcinogenic, and their release into environment causes serious environmental, aesthetical, and health problems. In the current work, indium-based coordination polymer particles (In-CPPs) have been fabricated via a facile solvothermal synthesis without any template or surfactant. In-CPPs are composed of hierarchical nanostructures assembled from abundant nanoplates with thickness of about 20 nm. Owing to their high BET surface area and pore volume, In-CPPs exhibit excellent adsorption capability for Congo red with a maximum capacity of 577 mg g(-1), which was higher than that of most materials reported to now. In-CPPS can also be outstanding adsorbents for removing other dyes such as acid chrome blue K, brilliant red GR and brilliant green. Furthermore, after calcinations in air In-CPPs can be converted to morphology-preserved porous In2O3 products which can detect NOx gas in air at room temperature.

  15. Hierarchically-Porous Carbon Derived from a Large-Scale Iron-based Organometallic Complex for Versatile Energy Storage.

    PubMed

    Fan, Chao-Ying; Li, Huan-Huan; Wang, Hai-Feng; Sun, Hai-Zhu; Wu, Xing-Long; Zhang, Jing-Ping

    2016-06-22

    Inspired by the preparation of the hierarchically-porous carbon (HPC) derived from metal organic frameworks (MOFs) for energy storage, in this work, a simple iron-based metal- organic complex (MOC), which was simpler and cheaper compared with the MOF, was selected to achieve versatile energy storage. The intertwined 1 D nanospindles and enriched-oxygen doping of the HPC was obtained after one-step carbonization of the MOC. When employed in lithium-ion batteries, the HPC exhibited reversible capacity of 778 mA h g(-1) after 60 cycles at 50 mA g(-1) . Moreover, the HPC maintained a capacity of 188 mA h g(-1) after 400 cycles at 100 mA g(-1) as the anode material in a sodium-ion battery. In addition, the HPC served as the cathode matrix for evaluation of a lithium-sulfur battery. The general preparation process of the HPC is commercial, which is responsible for the large-scale production for its practical application. PMID:27219476

  16. Hierarchically-Porous Carbon Derived from a Large-Scale Iron-based Organometallic Complex for Versatile Energy Storage.

    PubMed

    Fan, Chao-Ying; Li, Huan-Huan; Wang, Hai-Feng; Sun, Hai-Zhu; Wu, Xing-Long; Zhang, Jing-Ping

    2016-06-22

    Inspired by the preparation of the hierarchically-porous carbon (HPC) derived from metal organic frameworks (MOFs) for energy storage, in this work, a simple iron-based metal- organic complex (MOC), which was simpler and cheaper compared with the MOF, was selected to achieve versatile energy storage. The intertwined 1 D nanospindles and enriched-oxygen doping of the HPC was obtained after one-step carbonization of the MOC. When employed in lithium-ion batteries, the HPC exhibited reversible capacity of 778 mA h g(-1) after 60 cycles at 50 mA g(-1) . Moreover, the HPC maintained a capacity of 188 mA h g(-1) after 400 cycles at 100 mA g(-1) as the anode material in a sodium-ion battery. In addition, the HPC served as the cathode matrix for evaluation of a lithium-sulfur battery. The general preparation process of the HPC is commercial, which is responsible for the large-scale production for its practical application.

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

    NASA Astrophysics Data System (ADS)

    Meng, Yongming; Lin, Yu; Lin, Yibing; Yang, Jiyuan

    2014-02-01

    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 °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.

  18. Enhanced cellular activities of polycaprolactone/alginate-based cell-laden hierarchical scaffolds for hard tissue engineering applications.

    PubMed

    Lee, HyeongJin; Kim, GeunHyung

    2014-09-15

    Biomedical scaffolds have been widely investigated because they are essential for support and promotion of cell adhesion, proliferation and differentiation in three-dimensional (3D) structures. An ideal scaffold should be highly porous to enable efficient nutrient and oxygen transfer and have a 3D structure that provides optimal micro-environmental conditions for the seeded cells to obtain homogeneous growth after a long culture period. In this study, new hierarchical osteoblast-like cell (MG-63)-laden scaffolds consisting of micro-sized struts/inter-layered micro-nanofibres and cell-laden hydrogel struts with mechanically stable and biologically superior properties were introduced. Poly(ethylene oxide) (PEO) was used as a sacrificial component to generate pores within the cell-laden hydrogel struts to attain a homogeneous cell distribution and rapid cell growth in the scaffold interior. The alginate-based cell-laden struts with PEO induced fast/homogeneous cell release, in contrast to nonporous cell-laden struts. Various weight fractions (0.5, 1, 2, 3 and 3.5 wt%) of PEO were used, of which 2 wt% PEO in the cell-laden strut resulted in the most appropriate cell release and enhanced biological activities (cell proliferation and calcium deposition), compared to nonporous cell-laden struts.

  19. Solving the ECG forward problem by means of standard h- and h-hierarchical adaptive linear boundary element method: comparison with two refinement schemes.

    PubMed

    Shou, Guofa; Xia, Ling; Jiang, Mingfeng; Wei, Qing; Liu, Feng; Crozier, Stuart

    2009-05-01

    The boundary element method (BEM) is a commonly used numerical approach to solve biomedical electromagnetic volume conductor models such as ECG and EEG problems, in which only the interfaces between various tissue regions need to be modeled. The quality of the boundary element discretization affects the accuracy of the numerical solution, and the construction of high-quality meshes is time-consuming and always problem-dependent. Adaptive BEM (aBEM) has been developed and validated as an effective method to tackle such problems in electromagnetic and mechanical fields, but has not been extensively investigated in the ECG problem. In this paper, the h aBEM, which produces refined meshes through adaptive adjustment of the elements' connection, is investigated for the ECG forward problem. Two different refinement schemes: adding one new node (SH1) and adding three new nodes (SH3), are applied for the h aBEM calculation. In order to save the computational time, the h-hierarchical aBEM is also used through the introduction of the h-hierarchical shape functions for SH3. The algorithms were evaluated with a single-layer homogeneous sphere model with assumed dipole sources and a geometrically realistic heart-torso model. The simulations showed that h aBEM can produce better mesh results and is more accurate and effective than the traditional BEM for the ECG problem. While with the same refinement scheme SH3, the h-hierarchical aBEM can save the computational costs about 9% compared to the implementation of standard h aBEM.

  20. HDS: Hierarchical Data System

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  1. A New Malaysian Quality of Life Index Based on Fuzzy Sets and Hierarchical Needs

    ERIC Educational Resources Information Center

    Lazim, M. Abdullah; Abu Osman, M. Tap

    2009-01-01

    The Malaysian Quality of Life Index (MQLI) released by the Economic Planning Unit (EPU), has led authors to search for alternative method of expressing this index. One of the limitations in MQLI computations is the failure to recognise unequal weights for each accounted component. This paper offers a new way of expressing the quality of life index…

  2. Game Immersion Experience: Its Hierarchical Structure and Impact on Game-Based Science Learning

    ERIC Educational Resources Information Center

    Cheng, M.-T.; She, H.-C.; Annetta, L. A.

    2015-01-01

    Many studies have shown the positive impact of serious educational games (SEGs) on learning outcomes. However, there still exists insufficient research that delves into the impact of immersive experience in the process of gaming on SEG-based science learning. The dual purpose of this study was to further explore this impact. One purpose was to…

  3. Thesaurus-Based Hierarchical Semantic Grouping of Medical Terms in Information Extraction.

    PubMed

    Lassoued, Yassine; Deleris, Léa

    2016-01-01

    In this paper we describe a semantic approach for grouping medical terms into a hierarchy of concepts based on the UMLS meta-thesaurus. The context of this work is Medical Recap, a Web system that automatically extracts risk information from PubMed abstracts, and then aggregates this knowledge into dependence graphs or Bayesian networks. PMID:27577422

  4. Surfactant-assisted porphyrin based hierarchical nano/micro assemblies and their efficient photocatalytic behavior.

    PubMed

    Mandal, Sadananda; Nayak, Sandip K; Mallampalli, Sivaramakrishna; Patra, Amitava

    2014-01-01

    In this report, we have demonstrated the synthesis of surfactant-assisted different morphologies of meso-tetra(4-carboxyphenyl)porphyrin assemblies (spherical to flower shaped). These nano/micro assemblies are well characterized by scanning electron microscopy and X-ray diffraction. The formation of assemblies is driven by noncovalent interactions such as hydrophobic-hydrophobic and aromatic π-π stacking between the molecules. The steady state and time-resolved spectroscopic investigation reveal that different assemblies are formed by virtue of special supramolecular organizations. The photocatalytic activities of different assemblies have been demonstrated with an organic pollutant Rhodamine B dye under the visible light irradiation. Such porphyrin based assemblies could pave the way for designing new optical based materials for the applications in photocatalytic, photovoltaic, and light harvesting system. PMID:24344739

  5. Mapping the evolution of hierarchical microstructures in a Ni-based superalloy.

    PubMed

    Vogel, Florian; Wanderka, Nelia; Balogh, Zoltan; Ibrahim, Mohammed; Stender, Patrick; Schmitz, Guido; Banhart, John

    2013-01-01

    Phase separation of γ' precipitates determines the microstructure and mechanical properties of nickel-based superalloys. In the course of ageing, disordered γ spheres form inside ordered (L12) γ' precipitates, undergo a morphological change to plates and finally split the γ' precipitates. The presence of γ particles inside γ' affects coarsening kinetics and increases alloy hardness. Here we use atom probe tomography to visualize phase separation in a Ni86.1Al8.5Ti5.4 alloy in three dimensions and to quantify the composition of all the phases with near-atomic resolution. We find that γ' precipitates are supersaturated in nickel, thereby driving the formation of γ particles and observe a compositional evolution of the γ particles, which accompanies their morphological change. Our results suggest that by controlling nickel supersaturation we can tailor the phase separation and thereby the properties of nickel-based superalloys. PMID:24356413

  6. Mapping the evolution of hierarchical microstructures in a Ni-based superalloy.

    PubMed

    Vogel, Florian; Wanderka, Nelia; Balogh, Zoltan; Ibrahim, Mohammed; Stender, Patrick; Schmitz, Guido; Banhart, John

    2013-01-01

    Phase separation of γ' precipitates determines the microstructure and mechanical properties of nickel-based superalloys. In the course of ageing, disordered γ spheres form inside ordered (L12) γ' precipitates, undergo a morphological change to plates and finally split the γ' precipitates. The presence of γ particles inside γ' affects coarsening kinetics and increases alloy hardness. Here we use atom probe tomography to visualize phase separation in a Ni86.1Al8.5Ti5.4 alloy in three dimensions and to quantify the composition of all the phases with near-atomic resolution. We find that γ' precipitates are supersaturated in nickel, thereby driving the formation of γ particles and observe a compositional evolution of the γ particles, which accompanies their morphological change. Our results suggest that by controlling nickel supersaturation we can tailor the phase separation and thereby the properties of nickel-based superalloys.

  7. Free-Energy Bounds for Hierarchical Spin Models

    NASA Astrophysics Data System (ADS)

    Castellana, Michele; Barra, Adriano; Guerra, Francesco

    2014-04-01

    In this paper we study two non-mean-field (NMF) spin models built on a hierarchical lattice: the hierarchical Edward-Anderson model (HEA) of a spin glass, and Dyson's hierarchical model (DHM) of a ferromagnet. For the HEA, we prove the existence of the thermodynamic limit of the free energy and the replica-symmetry-breaking (RSB) free-energy bounds previously derived for the Sherrington-Kirkpatrick model of a spin glass. These RSB mean-field bounds are exact only if the order-parameter fluctuations (OPF) vanish: given that such fluctuations are not negligible in NMF models, we develop a novel strategy to tackle part of OPF in hierarchical models. The method is based on absorbing part of OPF of a block of spins into an effective Hamiltonian of the underlying spin blocks. We illustrate this method for DHM and show that, compared to the mean-field bound for the free energy, it provides a tighter NMF bound, with a critical temperature closer to the exact one. To extend this method to the HEA model, a suitable generalization of Griffith's correlation inequalities for Ising ferromagnets is needed: since correlation inequalities for spin glasses are still an open topic, we leave the extension of this method to hierarchical spin glasses as a future perspective.

  8. MotionExplorer: exploratory search in human motion capture data based on hierarchical aggregation.

    PubMed

    Bernard, Jürgen; Wilhelm, Nils; Krüger, Björn; May, Thorsten; Schreck, Tobias; Kohlhammer, Jörn

    2013-12-01

    We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work. PMID:24051792

  9. Anisotropic mesh adaptation for solution of finite element problems using hierarchical edge-based error estimates

    SciTech Connect

    Lipnikov, Konstantin; Agouzal, Abdellatif; Vassilevski, Yuri

    2009-01-01

    We present a new technology for generating meshes minimizing the interpolation and discretization errors or their gradients. The key element of this methodology is construction of a space metric from edge-based error estimates. For a mesh with N{sub h} triangles, the error is proportional to N{sub h}{sup -1} and the gradient of error is proportional to N{sub h}{sup -1/2} which are optimal asymptotics. The methodology is verified with numerical experiments.

  10. Growing self-organizing trees for autonomous hierarchical clustering.

    PubMed

    Doan, Nhat-Quang; Azzag, Hanane; Lebbah, Mustapha

    2013-05-01

    This paper presents a new unsupervised learning method based on growing processes and autonomous self-assembly rules. This method, called Growing Self-organizing Trees (GSoT), can grow both network size and tree topology to represent the topological and hierarchical dataset organization, allowing a rapid and interactive visualization. Tree construction rules draw inspiration from elusive properties of biological organization to build hierarchical structures. Experiments conducted on real datasets demonstrate good GSoT performance and provide visual results that are generated during the training process. PMID:23041056

  11. A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

    PubMed

    Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

    2016-03-01

    In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences.

  12. A repeatedly refuelable mediated biofuel cell based on a hierarchical porous carbon electrode

    NASA Astrophysics Data System (ADS)

    Fujita, Shuji; Yamanoi, Shun; Murata, Kenichi; Mita, Hiroki; Samukawa, Tsunetoshi; Nakagawa, Takaaki; Sakai, Hideki; Tokita, Yuichi

    2014-05-01

    Biofuel cells that generate electricity from renewable fuels, such as carbohydrates, must be reusable through repeated refuelling, should these devices be used in consumer electronics. We demonstrate the stable generation of electricity from a glucose-powered mediated biofuel cell through multiple refuelling cycles. This refuelability is achieved by immobilizing nicotinamide adenine dinucleotide (NAD), an electron-transfer mediator, and redox enzymes in high concentrations on porous carbon particles constituting an anode while maintaining their electrochemical and enzymatic activities after the immobilization. This bioanode can be refuelled continuously for more than 60 cycles at 1.5 mA cm-2 without significant potential drop. Cells assembled with these bioanodes and bilirubin-oxidase-based biocathodes can be repeatedly used to power a portable music player at 1 mW cm-3 through 10 refuelling cycles. This study suggests that the refuelability within consumer electronics should facilitate the development of long and repeated use of the mediated biofuel cells as well as of NAD-based biosensors, bioreactors, and clinical applications.

  13. A repeatedly refuelable mediated biofuel cell based on a hierarchical porous carbon electrode

    PubMed Central

    Fujita, Shuji; Yamanoi, Shun; Murata, Kenichi; Mita, Hiroki; Samukawa, Tsunetoshi; Nakagawa, Takaaki; Sakai, Hideki; Tokita, Yuichi

    2014-01-01

    Biofuel cells that generate electricity from renewable fuels, such as carbohydrates, must be reusable through repeated refuelling, should these devices be used in consumer electronics. We demonstrate the stable generation of electricity from a glucose-powered mediated biofuel cell through multiple refuelling cycles. This refuelability is achieved by immobilizing nicotinamide adenine dinucleotide (NAD), an electron-transfer mediator, and redox enzymes in high concentrations on porous carbon particles constituting an anode while maintaining their electrochemical and enzymatic activities after the immobilization. This bioanode can be refuelled continuously for more than 60 cycles at 1.5 mA cm−2 without significant potential drop. Cells assembled with these bioanodes and bilirubin-oxidase-based biocathodes can be repeatedly used to power a portable music player at 1 mW cm−3 through 10 refuelling cycles. This study suggests that the refuelability within consumer electronics should facilitate the development of long and repeated use of the mediated biofuel cells as well as of NAD-based biosensors, bioreactors, and clinical applications. PMID:24820210

  14. Hierarchical scaffold design for mesenchymal stem cell-based gene therapy of hemophilia B.

    PubMed

    Coutu, Daniel L; Cuerquis, Jessica; El Ayoubi, Rouwayda; Forner, Kathy-Ann; Roy, Ranjan; François, Moïra; Griffith, May; Lillicrap, David; Yousefi, Azizeh-Mitra; Blostein, Mark D; Galipeau, Jacques

    2011-01-01

    Gene therapy for hemophilia B and other hereditary plasma protein deficiencies showed great promise in pre-clinical and early clinical trials. However, safety concerns about in vivo delivery of viral vectors and poor post-transplant survival of ex vivo modified cells remain key hurdles for clinical translation of gene therapy. We here describe a 3D scaffold system based on porous hydroxyapatite-PLGA composites coated with biomineralized collagen 1. When combined with autologous gene-engineered factor IX (hFIX) positive mesenchymal stem cells (MSCs) and implanted in hemophilic mice, these scaffolds supported long-term engraftment and systemic protein delivery by MSCs in vivo. Optimization of the scaffolds at the macro-, micro- and nanoscales provided efficient cell delivery capacity, MSC self-renewal and osteogenesis respectively, concurrent with sustained delivery of hFIX. In conclusion, the use of gene-enhanced MSC-seeded scaffolds may be of practical use for treatment of hemophilia B and other plasma protein deficiencies. PMID:20864158

  15. Hierarchical Assembly of Multifunctional Oxide-based Composite Nanostructures for Energy and Environmental Applications

    PubMed Central

    Gao, Pu-Xian; Shimpi, Paresh; Gao, Haiyong; Liu, Caihong; Guo, Yanbing; Cai, Wenjie; Liao, Kuo-Ting; Wrobel, Gregory; Zhang, Zhonghua; Ren, Zheng; Lin, Hui-Jan

    2012-01-01

    Composite nanoarchitectures represent a class of nanostructured entities that integrates various dissimilar nanoscale building blocks including nanoparticles, nanowires, and nanofilms toward realizing multifunctional characteristics. A broad array of composite nanoarchitectures can be designed and fabricated, involving generic materials such as metal, ceramics, and polymers in nanoscale form. In this review, we will highlight the latest progress on composite nanostructures in our research group, particularly on various metal oxides including binary semiconductors, ABO3-type perovskites, A2BO4 spinels and quaternary dielectric hydroxyl metal oxides (AB(OH)6) with diverse application potential. Through a generic template strategy in conjunction with various synthetic approaches— such as hydrothermal decomposition, colloidal deposition, physical sputtering, thermal decomposition and thermal oxidation, semiconductor oxide alloy nanowires, metal oxide/perovskite (spinel) composite nanowires, stannate based nanocompostes, as well as semiconductor heterojunction—arrays and networks have been self-assembled in large scale and are being developed as promising classes of composite nanoarchitectures, which may open a new array of advanced nanotechnologies in solid state lighting, solar absorption, photocatalysis and battery, auto-emission control, and chemical sensing. PMID:22837702

  16. Hierarchical self-assembly of switchable nucleolipid supramolecular gels based on environmentally-sensitive fluorescent nucleoside analogs

    NASA Astrophysics Data System (ADS)

    Nuthanakanti, Ashok; Srivatsan, Seergazhi G.

    2016-02-01

    Exquisite recognition and folding properties have rendered nucleic acids as useful supramolecular synthons for the construction of programmable architectures. Despite their proven applications in nanotechnology, scalability and fabrication of nucleic acid nanostructures still remain a challenge. Here, we describe a novel design strategy to construct new supramolecular nucleolipid synthons by using environmentally-sensitive fluorescent nucleoside analogs, based on 5-(benzofuran-2-yl)uracil and 5-(benzo[b]thiophen-2-yl)uracil cores, as the head group and fatty acids, attached to the ribose sugar, as the lipophilic group. These modified nucleoside-lipid hybrids formed organogels driven by hierarchical structures such as fibers, twisted ribbons, helical ribbons and nanotubes, which depended on the nature of fatty acid chain and nucleobase modification. NMR, single crystal X-ray and powder X-ray diffraction studies revealed the coordinated interplay of various non-covalent interactions invoked by modified nucleobase, sugar and fatty acid chains in setting up the pathway for the gelation process. Importantly, these nucleolipid gels retained or displayed aggregation-induced enhanced emission and their gelation behavior and photophysical properties could be reversibly switched by external stimuli such as temperature, ultrasound and chemicals. Furthermore, the switchable nature of nucleolipid gels to chemical stimuli enabled the selective two channel recognition of fluoride and Hg2+ ions through visual phase transition and fluorescence change. Fluorescent organogels exhibiting such a combination of useful features is rare, and hence, we expect that this innovative design of fluorescent nucleolipid supramolecular synthons could lead to the emergence of a new family of smart optical materials and probes.Exquisite recognition and folding properties have rendered nucleic acids as useful supramolecular synthons for the construction of programmable architectures. Despite their

  17. Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

    NASA Astrophysics Data System (ADS)

    Edwards, Mark; Hu, Fei; Kumar, Sunil

    2004-10-01

    The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report

  18. Multicollinearity in hierarchical linear models.

    PubMed

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model.

  19. Adaptive Sampling in Hierarchical Simulation

    SciTech Connect

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

    2007-07-09

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

  20. Entropy Bounds for Hierarchical Molecular Networks

    PubMed Central

    Dehmer, Matthias; Borgert, Stephan; Emmert-Streib, Frank

    2008-01-01

    In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a recently introduced measure to determine the topological entropy of non-hierarchical networks, we provide bounds for estimating the entropy of hierarchical graphs. Apart from bounds to estimate the entropy of a single hierarchical graph, we see that the derived bounds can also be used for characterizing graph classes. Our contribution is an important extension to previous results about the entropy of non-hierarchical networks because for practical applications hierarchical networks are playing an important role in chemistry and biology. In addition to the derivation of the entropy bounds, we provide a numerical analysis for two special graph classes, rooted trees and generalized trees, and demonstrate hereby not only the computational feasibility of our method but also learn about its characteristics and interpretability with respect to data analysis. PMID:18769487

  1. Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification.

    PubMed

    Zhou, Yicong; Wei, Yantao

    2016-07-01

    This paper proposes a spectral-spatial feature learning (SSFL) method to obtain robust features of hyperspectral images (HSIs). It combines the spectral feature learning and spatial feature learning in a hierarchical fashion. Stacking a set of SSFL units, a deep hierarchical model called the spectral-spatial networks (SSN) is further proposed for HSI classification. SSN can exploit both discriminative spectral and spatial information simultaneously. Specifically, SSN learns useful high-level features by alternating between spectral and spatial feature learning operations. Then, kernel-based extreme learning machine (KELM), a shallow neural network, is embedded in SSN to classify image pixels. Extensive experiments are performed on two benchmark HSI datasets to verify the effectiveness of SSN. Compared with state-of-the-art methods, SSN with a deep hierarchical architecture obtains higher classification accuracy in terms of the overall accuracy, average accuracy, and kappa ( κ ) coefficient of agreement, especially when the number of the training samples is small.

  2. Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

    PubMed Central

    2011-01-01

    Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC

  3. Chemistry Problem Solving Instruction: A Comparison of Three Computer-Based Formats for Learning from Hierarchical Network Problem Representations

    ERIC Educational Resources Information Center

    Ngu, Bing Hiong; Mit, Edwin; Shahbodin, Faaizah; Tuovinen, Juhani

    2009-01-01

    Within the cognitive load theory framework, we designed and compared three alternative instructional solution formats that can be derived from a common static hierarchical network representation depicting problem structure. The interactive-solution format permitted students to search in self-controlled manner for solution steps, static-solution…

  4. Hierarchical modelling of in situ elastic deformation of human enamel based on photoelastic and diffraction analysis of stresses and strains.

    PubMed

    Sui, Tan; Lunt, Alexander J G; Baimpas, Nikolaos; Sandholzer, Michael A; Hu, Jianan; Dolbnya, Igor P; Landini, Gabriel; Korsunsky, Alexander M

    2014-01-01

    Human enamel is a typical hierarchical mineralized tissue with a two-level composite structure. To date, few studies have focused on how the mechanical behaviour of this tissue is affected by both the rod orientation at the microscale and the preferred orientation of mineral crystallites at the nanoscale. In this study, wide-angle X-ray scattering was used to determine the internal lattice strain response of human enamel samples (with differing rod directions) as a function of in situ uniaxial compressive loading. Quantitative stress distribution evaluation in the birefringent mounting epoxy was performed in parallel using photoelastic techniques. The resulting experimental data was analysed using an advanced multiscale Eshelby inclusion model that takes into account the two-level hierarchical structure of human enamel, and reflects the differing rod directions and orientation distributions of hydroxyapatite crystals. The achieved satisfactory agreement between the model and the experimental data, in terms of the values of multidirectional strain components under the action of differently orientated loads, suggests that the multiscale approach captures reasonably successfully the structure-property relationship between the hierarchical architecture of human enamel and its response to the applied forces. This novel and systematic approach can be used to improve the interpretation of the mechanical properties of enamel, as well as of the textured hierarchical biomaterials in general.

  5. Predicting protein function with hierarchical phylogenetic profiles: the Gene3D Phylo-Tuner method applied to eukaryotic genomes.

    PubMed

    Ranea, Juan A G; Yeats, Corin; Grant, Alastair; Orengo, Christine A

    2007-11-01

    "Phylogenetic profiling" is based on the hypothesis that during evolution functionally or physically interacting genes are likely to be inherited or eliminated in a codependent manner. Creating presence-absence profiles of orthologous genes is now a common and powerful way of identifying functionally associated genes. In this approach, correctly determining orthology, as a means of identifying functional equivalence between two genes, is a critical and nontrivial step and largely explains why previous work in this area has mainly focused on using presence-absence profiles in prokaryotic species. Here, we demonstrate that eukaryotic genomes have a high proportion of multigene families whose phylogenetic profile distributions are poor in presence-absence information content. This feature makes them prone to orthology mis-assignment and unsuited to standard profile-based prediction methods. Using CATH structural domain assignments from the Gene3D database for 13 complete eukaryotic genomes, we have developed a novel modification of the phylogenetic profiling method that uses genome copy number of each domain superfamily to predict functional relationships. In our approach, superfamilies are subclustered at ten levels of sequence identity-from 30% to 100%-and phylogenetic profiles built at each level. All the profiles are compared using normalised Euclidean distances to identify those with correlated changes in their domain copy number. We demonstrate that two protein families will "auto-tune" with strong co-evolutionary signals when their profiles are compared at the similarity levels that capture their functional relationship. Our method finds functional relationships that are not detectable by the conventional presence-absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes. PMID:18052542

  6. The hierarchical algorithms--theory and applications

    NASA Astrophysics Data System (ADS)

    Su, Zheng-Yao

    scan scheme applicable to problem domains of any high dimension and of arbitrary geometry (scan is an important primitive of parallel computing). In addition, from implementation results, the hierarchical cluster labeling algorithm has proved to work equally well on MIMD machines, though originally designed for SIMD machines.Based on this success, we further study the hierarchical structure hidden in the algorithm. Hierarchical structure is a conceptual framework frequently used in building models for the study of a great variety of problems. This structure serves not only to describe the complexity of the system at different levels, but also to achieve some goals targeted by the problem, i.e., an algorithm to solve the problem. In this regard, we investigate the similarities and differences between this algorithm and others, including the FFT and the Barnes-Hut method, in terms of their hierarchical structures.

  7. Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

    NASA Technical Reports Server (NTRS)

    Padovan, Joseph; Krishna, Lala; Gute, Douglas

    1997-01-01

    Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

  8. Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

    NASA Technical Reports Server (NTRS)

    Choi, Sang Hyouk (Inventor); Park, Yeonjoon (Inventor); Chu, Sang-Hyon (Inventor); Elliott, James R. (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Lillehei, Peter T. (Inventor); Stoakley, Diane M. (Inventor)

    2011-01-01

    A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

  9. Combining the Strengths of Physically Based Models with Statistical Modelling Tools Using a Hierarchical Mixture of Experts Framework

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Sharma, A.; Nott, D.

    2005-12-01

    Rigidity in a modelling framework has been known to result in considerable bias in cases where the system behaviour is closely linked to the catchment antecedent conditions. An alternative to accommodate such variations in the system makeup is to enable the model to be flexible enough to evolve as antecedent conditions change. We present a framework that incorporates such flexibility by expressing the model through the combination of a number of different model structures. Each structure is adopted at a given time with a probability that depends on the current hydrologic state of the catchment. This framework is known as a Hierarchical Mixture of Experts (HME). When applied in a hydrological context, the HME approach has two major functions. It can act as a powerful predictive tool where simulation is extended beyond the calibration period. It also offers a basis for model development and building based on interpretation of the final model architecture in calibration. The probabilistic nature of HME means that it is ideally specified using Bayesian inference. The Bayesian approach also formalises the incorporation of uncertainty in the model specification. The interpretability of the overall HME framework is largely influenced by the individual model structures. One model which can be applied in the HME context is the popular Topmodel. Topmodel is a modelling tool that allows the simulation of distributed catchment response to rainfall. Many different versions of the basic model structure exist as the underlying concepts are challenged by different catchment studies. One modification often made is to the description of the baseflow recession. This study will investigate the predictive capability of Topmodel when the model is specified using both a Bayesian and HME approach. The specification of the distribution of model errors is investigated by definition of several different probability distributions. The HME approach is applied in a framework that compares two

  10. Hierarchical structured Ni nanoring and hollow sphere arrays by morphology inheritance based on ordered through-pore template and electrodeposition.

    PubMed

    Duan, Guotao; Cai, Weiping; Luo, Yuanyuan; Li, Zhigang; Lei, Yong

    2006-08-17

    Fabrication of micro/nano-hierarchical Ni ordered nanostructured arrays is demonstrated by electrochemical deposition on the ordered alumina through-pore template induced by solution-dipping the colloidal monolayer. The morphology of the Ni nanostructured arrays exhibits a ringlike or hollow spherical structure depending on the template geometry and appropriate deposition parameters. The skeletons of the arrays are of floc- or flakelet-like fine structure on the nanoscale. The formation of such morphologies is attributed to the preferential growth along the inner wall of the alumina pores, while the nanoflakelet fine structure originates from a morphology inheritance process or the transitional product Ni(OH)2 which leads to the final nanostructured Ni crystals. This morphology inherence could be useful in the field of nanofabrication. Such micro/nano-hierarchically structured arrays show good magnetic properties and will find applications in the fields of catalysis, magnetics, optoelectrics, surface-enhanced Raman scattering (SERS), and new nanodevices.

  11. New physiologically-relevant liver tissue model based on hierarchically cocultured primary rat hepatocytes with liver endothelial cells.

    PubMed

    Xiao, Wenjin; Perry, Guillaume; Komori, Kikuo; Sakai, Yasuyuki

    2015-11-01

    To develop an in vitro liver tissue equivalent, hepatocytes should be cocultured with liver non-parenchymal cells to mimic the in vivo physiological microenvironments. In this work, we describe a physiologically-relevant liver tissue model by hierarchically organizing layers of primary rat hepatocytes and human liver sinusoidal endothelial cells (TMNK-1) on an oxygen-permeable polydimethylsiloxane (PDMS) membrane, which facilitates direct oxygenation by diffusion through the membrane. This in vivo-mimicking hierarchical coculture was obtained by simply proceeding the overlay of TMNK-1 cells on the hepatocyte layer re-formed on the collagen immobilized PDMS membranes. The comparison of hepatic functionalities was achieved between coculture and sandwich culture with Matrigel, in the presence and absence of direct oxygenation. A complete double-layered structure of functional liver cells with vertical contact between hepatocytes and TMNK-1 was successfully constructed in the coculture with direct oxygen supply and was well-maintained for 14 days. The hepatocytes in this hierarchical culture exhibited improved survival, functional bile canaliculi formation, cellular level polarization and maintenance of metabolic activities including Cyp1A1/2 activity and albumin production. By contrast, the two cell populations formed discontinuous monolayers on the same surfaces in the non-oxygen-permeable cultures. These results demonstrate that (i) the direct oxygenation through the PDMS membranes enables very simple formation of a hierarchical structure consisting of a hepatocyte layer and a layer of TMNK-1 and (ii) we may include other non-parenchymal cells in this format easily, which can be widely applicable to other epithelial organs.

  12. Assessing Team-Based Instructional Design Problem Solutions of Hierarchical Versus Heterarchical Web-Based Hypermedia Cases

    ERIC Educational Resources Information Center

    Dabbagh, Nada; Denisar, Katrina

    2005-01-01

    For this study, we examined the cogency, comprehensiveness, and viability of team-based problem solutions of a Web-based hypermedia case designed to promote student understanding of the practice of instructional design. Participants were 14 students enrolled in a graduate course on advanced instructional design. The case was presented to students…

  13. Self-Assembly of Hierarchical Chiral Nanostructures Based on Metal-Benzimidazole Interactions: Chiral Nanofibers, Nanotubes, and Microtubular Flowers.

    PubMed

    Zhou, Xiaoqin; Jin, Qingxian; Zhang, Li; Shen, Zhaocun; Jiang, Long; Liu, Minghua

    2016-09-01

    Controlled hierarchical self-assembly of synthetic molecules into chiral nanoarchitectures to mimic those biological chiral structures is of great importance. Here, a low-molecular-weight organogelator containing a benzimidazole moiety conjugated with an amphiphilic l-glutamic amide has been designed and its self-assembly into various hierarchical chiral nanostructures is investigated. Upon gel formation in organic solvents, 1D chiral nanostructure such as nanofiber and nanotube are obtained depending on the solvents. In the presence of transition and rare earth metal ions, hierarchical chiral nanostructures are formed. Specifically, the addition of TbCl3 , EuCl3 , and AgNO3 leads to nanofiber structures, while the addition of Cu(NO3 )2 , Tb(NO3 )3 , or Eu(NO3 )3 provides the microflower structures and microtubular flower structures, respectively. While Eu(III) and Tb(III)-containing microtubular flowers keep the chirality, the Cu(II)-coordinated microflowers lose chirality. More interestingly, the nanofibers formed by the gelator coordinated with Eu(III) or Tb(III) ions show not only the supramolecular chirality but also the circularly polarized luminescence. PMID:27248367

  14. Hierarchical patch dynamics and animal movement pattern.

    PubMed

    Fauchald, Per; Tveraa, Torkild

    2006-09-01

    In hierarchical patch systems, small-scale patches of high density are nested within large-scale patches of low density. The organization of multiple-scale hierarchical systems makes non-random strategies for dispersal and movement particularly important. Here, we apply a new method based on first-passage time on the pathway of a foraging seabird, the Antarctic petrel (Thalassoica antarctica), to quantify its foraging pattern and the spatial dynamics of its foraging areas. Our results suggest that Antarctic petrels used a nested search strategy to track a highly dynamic hierarchical patch system where small-scale patches were congregated within patches at larger scales. The birds searched for large-scale patches by traveling fast and over long distances. Once within a large-scale patch, the birds concentrated their search to find smaller scale patches. By comparing the pathway of different birds we were able to quantify the spatial scale and turnover of their foraging areas. On the largest scale we found foraging areas with a characteristic scale of about 400 km. Nested within these areas we found foraging areas with a characteristic scale of about 100 km. The large-scale areas disappeared or moved within a time frame of weeks while the nested small-scale areas disappeared or moved within days. Antarctic krill (Euphausia superba) is the dominant food item of Antarctic petrels and we suggest that our findings reflect the spatial dynamics of krill in the area. PMID:16794832

  15. Inference and Hierarchical Modeling in the Social Sciences.

    ERIC Educational Resources Information Center

    Draper, David

    1995-01-01

    The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)

  16. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    NASA Astrophysics Data System (ADS)

    Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido

    2015-12-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.

  17. Incorporating Usability Criteria into the Development of Animated Hierarchical Maps

    ERIC Educational Resources Information Center

    Shih, Yu-Cheng; Huang, Pei-Ren; Chen, Sherry Y.

    2013-01-01

    Nowadays, Web-based learning systems have become popular because they can provide multiple tools, among which hierarchical maps are widely used to support teaching and learning. However, traditional hierarchical maps may let learners easily get lost within large information space. This study proposes an animated hierarchical map to address this…

  18. Enhanced photovoltaic performance of fully flexible dye-sensitized solar cells based on the Nb2O5 coated hierarchical TiO2 nanowire-nanosheet arrays

    NASA Astrophysics Data System (ADS)

    Liu, Wenwu; Hong, Chengxun; Wang, Hui-gang; Zhang, Mei; Guo, Min

    2016-02-01

    Nb2O5 coated hierarchical TiO2 nanowire-sheet arrays photoanode was synthesized on flexible Ti-mesh substrate by using a hydrothermal approach. The effect of TiO2 morphology and Nb2O5 coating layer on the photovoltaic performance of the flexible dye sensitized solar cells (DSSCs) based on Ti-mesh supported nanostructures were systematically investigated. Compared to the TiO2 nanowire arrays (NWAs), hierarchical TiO2 nanowire arrays (HNWAs) with enlarged internal surface area and strong light scattering properties exhibited higher overall conversion efficiency. The introduction of thin Nb2O5 coating layers on the surface of the TiO2 HNWAs played a key role in improving the photovoltaic performance of the flexible DSSC. By separating the TiO2 and electrolyte (I-/I3-), the Nb2O5 energy barrier decreased the electron recombination rate and increased electron collection efficiency and injection efficiency, resulting in improved Jsc and Voc. Furthermore, the influence of Nb2O5 coating amounts on the power conversion efficiency were discussed in detail. The fully flexible DSSC based on Nb2O5 coated TiO2 HNWAs films with a thickness of 14 μm displayed a well photovoltaic property of 4.55% (Jsc = 10.50 mA cm-2, Voc = 0.75 V, FF = 0.58). The performance enhancement of the flexible DSSC is largely attributed to the reduced electron recombination, enlarged internal surface area and superior light scattering ability of the formed hierarchical nanostructures.

  19. Classification method based on KCCA

    NASA Astrophysics Data System (ADS)

    Wang, Zhanqing; Zhang, Guilin; Zhao, Guangzhou

    2007-11-01

    Nonlinear CCA extends the linear CCA in that it operates in the kernel space and thus implies the nonlinear combinations in the original space. This paper presents a classification method based on the kernel canonical correlation analysis (KCCA). We introduce the probabilistic label vectors (PLV) for a give pattern which extend the conventional concept of class label, and investigate the correlation between feature variables and PLV variables. A PLV predictor is presented based on KCCA, and then classification is performed on the predicted PLV. We formulate a frame for classification by integrating class information through PLV. Experimental results on Iris data set classification and facial expression recognition show the efficiencies of the proposed method.

  20. Optimisation by hierarchical search

    NASA Astrophysics Data System (ADS)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

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

  1. Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

    PubMed Central

    Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

    2015-01-01

    Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate

  2. A computer-based image analysis method for assessing the severity of hip joint osteoarthritis

    NASA Astrophysics Data System (ADS)

    Boniatis, Ioannis; Costaridou, Lena; Cavouras, Dionisis; Panagiotopoulos, Elias; Panayiotakis, George

    2006-12-01

    A computer-based image analysis method was developed for assessing the severity of hip osteoarthritis (OA). Eighteen pelvic radiographs of patients with verified unilateral hip OA, were digitized and enhanced employing custom developed software. Two ROIs corresponding to osteoarthritic and contralateral-physiological radiographic Hip Joint Spaces (HJSs) were determined on each radiograph. Textural features were extracted from the HJS-ROIs utilizing the run-length matrices and Laws textural measures. A k-Nearest Neighbour based hierarchical tree structure was designed for classifying hips into three OA severity categories labeled as "Normal", "Mild/Moderate", and "Severe". Employing the run-length features, the overall classification accuracy of the hierarchical tree structure was 86.1%. The utilization of Laws' textural measures improved the system classification performance, providing an overall classification accuracy of 94.4%. The proposed method maybe of value to physicians in assessing the severity of hip OA.

  3. Gold Nanoplate-Based 3D Hierarchical Microparticles: A Single Particle with High Surface-Enhanced Raman Scattering Enhancement.

    PubMed

    Ma, Ying; Yung, Lin-Yue Lanry

    2016-08-01

    Formation of intended nano- and microstructures with regular building blocks has attracted much attention because of their potential applications in the fields of optics, electronics, and catalysis. Herein, we report a novel strategy to spontaneously grow three-dimensional (3D) hierarchical cabbagelike microparticles (CLMPs) constructed by individual Au nanoplates. By reducing gold precursor to gold atoms, N-(3-amidino)-aniline (NAAN) itself was oxidized to form poly(N-(3-amidino)-aniline) (PNAAN), which specifically binds on Au(111) facet as a capping agent and which leads to the formation of gold nanoplates. Because of the incomplete coverage of Au(111) facet, new gold nanoplate growth sites were spontaneously generated from the crystal plane of existing Au nanoplates for the growth of other nanoplates. This process continued until the nanoplate density reached its maximum range, eventually resulting in CLMPs with well-controlled structures. This opens a new avenue to utilize the imperfection during nanoparticle (NP) growth for the construction of microstructures. The individual CLMP shows excellent surface-enhanced Raman scattering (SERS) performance with high enhancement factor (EF) and good reproducibility as it integrates the SERS enhancement effects of individual Au nanoplate and the nanogaps formed by the uniform and hierarchical structures. PMID:27452074

  4. Effective SERS-active substrates composed of hierarchical micro/nanostructured arrays based on reactive ion etching and colloidal masks.

    PubMed

    Zhang, Honghua; Liu, Dilong; Hang, Lifeng; Li, Xinyang; Liu, Guangqiang; Cai, Weiping; Li, Yue

    2016-09-30

    A facile route has been proposed for the fabrication of morphology-controlled periodic SiO2 hierarchical micro/nanostructured arrays by reactive ion etching (RIE) using monolayer colloidal crystals as masks. By effectively controlling the experimental conditions of RIE, the morphology of a periodic SiO2 hierarchical micro/nanostructured array could be tuned from a dome-shaped one to a circular truncated cone, and finally to a circular cone. After coating a silver thin layer, these periodic micro/nanostructured arrays were used as surface-enhanced Raman scattering (SERS)-active substrates and demonstrated obvious SERS signals of 4-Aminothiophenol (4-ATP). In addition, the circular cone arrays displayed better SERS enhancement than those of the dome-shaped and circular truncated cone arrays due to the rougher surface caused by physical bombardment. After optimization of the circular cone arrays with different periodicities, an array with the periodicity of 350 nm exhibits much stronger SERS enhancement and possesses a low detection limit of 10(-10) M 4-ATP. This offers a practical platform to conveniently prepare SERS-active substrates.

  5. Effective SERS-active substrates composed of hierarchical micro/nanostructured arrays based on reactive ion etching and colloidal masks

    NASA Astrophysics Data System (ADS)

    Zhang, Honghua; Liu, Dilong; Hang, Lifeng; Li, Xinyang; Liu, Guangqiang; Cai, Weiping; Li, Yue

    2016-09-01

    A facile route has been proposed for the fabrication of morphology-controlled periodic SiO2 hierarchical micro/nanostructured arrays by reactive ion etching (RIE) using monolayer colloidal crystals as masks. By effectively controlling the experimental conditions of RIE, the morphology of a periodic SiO2 hierarchical micro/nanostructured array could be tuned from a dome-shaped one to a circular truncated cone, and finally to a circular cone. After coating a silver thin layer, these periodic micro/nanostructured arrays were used as surface-enhanced Raman scattering (SERS)-active substrates and demonstrated obvious SERS signals of 4-Aminothiophenol (4-ATP). In addition, the circular cone arrays displayed better SERS enhancement than those of the dome-shaped and circular truncated cone arrays due to the rougher surface caused by physical bombardment. After optimization of the circular cone arrays with different periodicities, an array with the periodicity of 350 nm exhibits much stronger SERS enhancement and possesses a low detection limit of 10‑10 M 4-ATP. This offers a practical platform to conveniently prepare SERS-active substrates.

  6. Hierarchically Three-Dimensional Nanofiber Based Textile with High Conductivity and Biocompatibility As a Microbial Fuel Cell Anode.

    PubMed

    Tao, Yifei; Liu, Qiongzhen; Chen, Jiahui; Wang, Bo; Wang, Yuedan; Liu, Ke; Li, Mufang; Jiang, Haiqing; Lu, Zhentan; Wang, Dong

    2016-07-19

    Microbial fuel cells (MFCs) encompass complex bioelectrocatalytic reactions that converting chemical energy of organic compounds to electrical energy. Improving the anode configuration is thought to be a critical step for enhancing MFCs performance. In present study, a hierarchically structured textile polypyrrole/poly(vinyl alcohol-co-polyethylene) nanofibers/poly(ethylene terephthalate) (referred to PPy/NFs/PET) is shown to be excellent anode for MFCs. This hierarchical PPy/NFs/PET anode affords an open porous and three-dimensional interconnecting conductive scaffold with larger surface roughness, facilitating microbial colonization and electron transfer from exoelectrogens to the anode. The mediator-less MFC equipped with PPy/NFs/PET anode achieves a remarkable maximum power density of 2420 mW m(-2) with Escherichia coli as the microbial catalyst at the current density of 5500 mA m(-2), which is approximately 17 times higher compared to a reference anode PPy/PET (144 mW m(-2)). Considering the low cost, low weight, facile fabrication, and good winding, this PPy/NFs/PET textile anode promises a great potential for high-performance and cost-effective MFCs in a large scale. PMID:27294591

  7. Effective SERS-active substrates composed of hierarchical micro/nanostructured arrays based on reactive ion etching and colloidal masks.

    PubMed

    Zhang, Honghua; Liu, Dilong; Hang, Lifeng; Li, Xinyang; Liu, Guangqiang; Cai, Weiping; Li, Yue

    2016-09-30

    A facile route has been proposed for the fabrication of morphology-controlled periodic SiO2 hierarchical micro/nanostructured arrays by reactive ion etching (RIE) using monolayer colloidal crystals as masks. By effectively controlling the experimental conditions of RIE, the morphology of a periodic SiO2 hierarchical micro/nanostructured array could be tuned from a dome-shaped one to a circular truncated cone, and finally to a circular cone. After coating a silver thin layer, these periodic micro/nanostructured arrays were used as surface-enhanced Raman scattering (SERS)-active substrates and demonstrated obvious SERS signals of 4-Aminothiophenol (4-ATP). In addition, the circular cone arrays displayed better SERS enhancement than those of the dome-shaped and circular truncated cone arrays due to the rougher surface caused by physical bombardment. After optimization of the circular cone arrays with different periodicities, an array with the periodicity of 350 nm exhibits much stronger SERS enhancement and possesses a low detection limit of 10(-10) M 4-ATP. This offers a practical platform to conveniently prepare SERS-active substrates. PMID:27573436

  8. Hierarchically Three-Dimensional Nanofiber Based Textile with High Conductivity and Biocompatibility As a Microbial Fuel Cell Anode.

    PubMed

    Tao, Yifei; Liu, Qiongzhen; Chen, Jiahui; Wang, Bo; Wang, Yuedan; Liu, Ke; Li, Mufang; Jiang, Haiqing; Lu, Zhentan; Wang, Dong

    2016-07-19

    Microbial fuel cells (MFCs) encompass complex bioelectrocatalytic reactions that converting chemical energy of organic compounds to electrical energy. Improving the anode configuration is thought to be a critical step for enhancing MFCs performance. In present study, a hierarchically structured textile polypyrrole/poly(vinyl alcohol-co-polyethylene) nanofibers/poly(ethylene terephthalate) (referred to PPy/NFs/PET) is shown to be excellent anode for MFCs. This hierarchical PPy/NFs/PET anode affords an open porous and three-dimensional interconnecting conductive scaffold with larger surface roughness, facilitating microbial colonization and electron transfer from exoelectrogens to the anode. The mediator-less MFC equipped with PPy/NFs/PET anode achieves a remarkable maximum power density of 2420 mW m(-2) with Escherichia coli as the microbial catalyst at the current density of 5500 mA m(-2), which is approximately 17 times higher compared to a reference anode PPy/PET (144 mW m(-2)). Considering the low cost, low weight, facile fabrication, and good winding, this PPy/NFs/PET textile anode promises a great potential for high-performance and cost-effective MFCs in a large scale.

  9. Three-dimensional beehive-like hierarchical porous polyacrylonitrile-based carbons as a high performance supercapacitor electrodes

    NASA Astrophysics Data System (ADS)

    Yao, Long; Yang, Guangzhi; Han, Pan; Tang, Zhihong; Yang, Junhe

    2016-05-01

    Three-dimensional beehive-like hierarchical porous carbons (HPCs) have been prepared by a facile carbonization of polymethylmethacrylate (PMMA)/polyacrylonitrile (PAN) core-shell polymer particle followed by KOH activation. The all-organic porogenic core-shell precursor was synthesized by a simple and green surfactant-free emulsion polymerization. The as-obtained HPCs show favorable features for electrochemical energy storage such as high specific surface area of up to 2085 m2 g-1, high volume of pores up to 1.89 cm3 g-1, hierarchical porosity consisting of micro, meso, and macropores, turbostratic carbon structure, uniform pore size and rich oxygen-doping (21.20%). The supercapacitor performance of HPCs exhibit a high specific capacitance 314 F g-1 at a current density of 0.5 A g-1 and 237 F g-1 at a current density of 20 A g-1, ultra-high rate capability with 83% retention rate from 1 to 20 A g-1 and outstanding cycling stability with 96% capacitance retention after 2000 cycles. The facile, efficient and green synthesis strategy for novel HPCs from polymer sources could find use in supercapacitors, lithium ion batteries, fuel cells and sorbents.

  10. Effective SERS-active substrates composed of hierarchical micro/nanostructured arrays based on reactive ion etching and colloidal masks

    NASA Astrophysics Data System (ADS)

    Zhang, Honghua; Liu, Dilong; Hang, Lifeng; Li, Xinyang; Liu, Guangqiang; Cai, Weiping; Li, Yue

    2016-09-01

    A facile route has been proposed for the fabrication of morphology-controlled periodic SiO2 hierarchical micro/nanostructured arrays by reactive ion etching (RIE) using monolayer colloidal crystals as masks. By effectively controlling the experimental conditions of RIE, the morphology of a periodic SiO2 hierarchical micro/nanostructured array could be tuned from a dome-shaped one to a circular truncated cone, and finally to a circular cone. After coating a silver thin layer, these periodic micro/nanostructured arrays were used as surface-enhanced Raman scattering (SERS)-active substrates and demonstrated obvious SERS signals of 4-Aminothiophenol (4-ATP). In addition, the circular cone arrays displayed better SERS enhancement than those of the dome-shaped and circular truncated cone arrays due to the rougher surface caused by physical bombardment. After optimization of the circular cone arrays with different periodicities, an array with the periodicity of 350 nm exhibits much stronger SERS enhancement and possesses a low detection limit of 10-10 M 4-ATP. This offers a practical platform to conveniently prepare SERS-active substrates.

  11. Sonar image segmentation using an unsupervised hierarchical MRF model.

    PubMed

    Mignotte, M; Collet, C; Perez, P; Bouthemy, P

    2000-01-01

    This paper is concerned with hierarchical Markov random field (MRP) models and their application to sonar image segmentation. We present an original hierarchical segmentation procedure devoted to images given by a high-resolution sonar. The sonar image is segmented into two kinds of regions: shadow (corresponding to a lack of acoustic reverberation behind each object lying on the sea-bed) and sea-bottom reverberation. The proposed unsupervised scheme takes into account the variety of the laws in the distribution mixture of a sonar image, and it estimates both the parameters of noise distributions and the parameters of the Markovian prior. For the estimation step, we use an iterative technique which combines a maximum likelihood approach (for noise model parameters) with a least-squares method (for MRF-based prior). In order to model more precisely the local and global characteristics of image content at different scales, we introduce a hierarchical model involving a pyramidal label field. It combines coarse-to-fine causal interactions with a spatial neighborhood structure. This new method of segmentation, called the scale causal multigrid (SCM) algorithm, has been successfully applied to real sonar images and seems to be well suited to the segmentation of very noisy images. The experiments reported in this paper demonstrate that the discussed method performs better than other hierarchical schemes for sonar image segmentation.

  12. Superamphiphobic, light-trapping FeSe2 particles with a micro-nano hierarchical structure obtained by an improved solvothermal method

    NASA Astrophysics Data System (ADS)

    Yu, Jing; Wang, Hui-Jie; Shao, Wei-Jia; Xu, Xiao-Liang

    2014-01-01

    Wettability and the light-trapping effect of FeSe2 particles with a micro-nano hierarchical structure have been investigated. Particles are synthesized by an improved solvothermal method, wherein hexadecyl trimethyl ammonium bromide (CTAB) is employed as a surfactant. After modifying the particles with heptadecafluorodecyltrimethoxy-silane (HTMS), we find that the water contact angle (WCA) of the FeSe2 particles increases by 6.1° and the water sliding angle (WSA) decreases by 2.5° respectively, and the diffuse reflectivity decreases 29.4% compared with similar FeSe2 particles synthesized by the conventional method. The growth process of the particles is analyzed and a growth scenario is given. Upon altering the PH values of the water, we observe that the superhydrophobic property is maintained quite consistently across a wide PH range of 1-14. Moreover, the modified particles were also found to be superoleophobic. To the best of our knowledge, there is no systematic research on the wettability of FeSe2 particles, so our research provides a reference for other researchers.

  13. Synthesis of hierarchical Ni{sub 11}(HPO{sub 3}){sub 8}(OH){sub 6} superstructures based on nanorods through a soft hydrothermal route

    SciTech Connect

    Liao, Kaiming; Ni, Yonghong

    2010-02-15

    In this paper, we reported the successful synthesis of hierarchical Ni{sub 11}(HPO{sub 3}){sub 8}(OH){sub 6} superstructures based on nanorods via a facile hydrothermal route, employing NiCl{sub 2}.6H{sub 2}O and NaH{sub 2}PO{sub 2}.H{sub 2}O as the reactants in the presences of polyvinylpyrrolidone (PVP) and CH{sub 3}COONa.3H{sub 2}O. The reaction was carried out at 170 {sup o}C for 10 h. HPO{sub 3}{sup 2-} ions were provided via the dismutation reaction of H{sub 2}PO{sub 2}{sup -} ions in a weak basic solution. The as-obtained products were characterized by X-ray powder diffraction (XRD), energy dispersive spectrometry (EDS), field emission scanning electron microscopy (SEM), selected area electron diffraction (SAED) and high resolution transmission electron microscopy (HRTEM). Some factors influencing the morphology of the hierarchical Ni{sub 11}(HPO{sub 3}){sub 8}(OH){sub 6} nanorods, such as the reaction temperature, time, the amounts of PVP and CH{sub 3}COONa, and the initial concentration of Ni{sup 2+} ions, were systematically investigated. A possible growth mechanism was proposed based on experimental results.

  14. A systematic investigation of SO2 removal dynamics by coal-based activated cokes: The synergic enhancement effect of hierarchical pore configuration and gas components

    NASA Astrophysics Data System (ADS)

    Sun, Fei; Gao, Jihui; Liu, Xin; Tang, Xiaofan; Wu, Shaohua

    2015-12-01

    For the aim to break through the long-term roadblock to porous carbon based SO2 removal technology, typical coal-based activated cokes differing in terms of surface area, pore configuration and surface functional properties, were employed to investigate the SO2 removal dynamics. Among the employed activated cokes, the one with a hierarchically porous structure greatly enhanced the SO2 removal dynamics under the simulated flue gas compositions. More detailedly, SO2 separate adsorption property under normal temperature and pressure evidenced that monolayer SO2 molecules anchoring on micropore surface is the main adsorption pattern. The catalytic oxidation of SO2 follows the Eley-Rideal mechanism by which SO2 was firstly oxidized by molecular oxygen into SO3 which could depart partially to release the active sites for further adsorption. For the role of hierarchical pore configuration, it was proposed that micropores serve as gas adsorption and reaction accommodation, meso-/macropores act as byproduct H2SO4 transport and buffing reservoirs, which may in turn gives rise to the recovery of active sites in micropores and guarantees the continuous proceeding of sulfur-containing species transformation in the micropores. The present results suggest that pore configuration or interconnecting pattern, but not mere surface area or pore volume, should be favourably considered for optimizing heterogeneous gas-solid adsorption and reaction.

  15. Hierarchical LiFePO4 with a controllable growth of the (010) facet for lithium-ion batteries

    PubMed Central

    Guo, Binbin; Ruan, Hongcheng; Zheng, Cheng; Fei, Hailong; Wei, Mingdeng

    2013-01-01

    Hierarchically structured LiFePO4 was successfully synthesized by ionic liquid solvothermal method. These hierarchically structured LiFePO4 samples were constructed from nanostructured platelets with their (010) facets mainly exposed. To the best of our knowledge, facet control of a hierarchical LiFePO4 crystal has not been reported yet. Based on a series of experimental results, a tentative mechanism for the formation of these hierarchical structures was proposed. After these hierarchically structured LiFePO4 samples were coated with a thin carbon layer and used as cathode materials for lithium-ion batteries, they exhibited excellent high-rate discharge capability and cycling stability. For instance, a capacity of 95% can be maintained for the LiFePO4 sample at a rate as high as 20 C, even after 1000 cycles. PMID:24071818

  16. A biologically-inspired framework for contour detection using superpixel-based candidates and hierarchical visual cues.

    PubMed

    Sun, Xiao; Shang, Ke; Ming, Delie; Tian, Jinwen; Ma, Jiayi

    2015-10-20

    Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast to previous models that detect contours from pixels, a modified superpixel generation processing is proposed to generate a contour candidate set and then weigh the candidates by extracting hierarchical visual cues. We extract the low-level visual local cues to weigh the contour intrinsic property and mid-level visual cues on the basis of Gestalt principles for weighting the contour grouping constraint. Experimental results tested on the BSDS benchmark show that the proposed framework exhibits promising performances to capture meaningful contours in complex scenes.

  17. The multivariate Wright-Fisher process with mutation: Moment-based analysis and inference using a hierarchical Beta model.

    PubMed

    Hobolth, Asger; Siren, Jukka

    2016-04-01

    We consider the diffusion approximation of the multivariate Wright-Fisher process with mutation. Analytically tractable formulas for the first-and second-order moments of the allele frequency distribution are derived, and the moments are subsequently used to better understand key population genetics parameters and modeling frameworks. In particular we investigate the behavior of the expected homozygosity (the probability that two randomly sampled genes are identical) in the transient and stationary phases, and how appropriate the Dirichlet distribution is for modeling the allele frequency distribution at different evolutionary time scales. We find that the Dirichlet distribution is adequate for the pure drift model (no mutations allowed), but the distribution is not sufficiently flexible for more general mutation models. We suggest a new hierarchical Beta distribution for the allele frequencies in the Wright-Fisher process with a mutation model on the nucleotide level that distinguishes between transitions and transversions. PMID:26612605

  18. A Biologically-Inspired Framework for Contour Detection Using Superpixel-Based Candidates and Hierarchical Visual Cues

    PubMed Central

    Sun, Xiao; Shang, Ke; Ming, Delie; Tian, Jinwen; Ma, Jiayi

    2015-01-01

    Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast to previous models that detect contours from pixels, a modified superpixel generation processing is proposed to generate a contour candidate set and then weigh the candidates by extracting hierarchical visual cues. We extract the low-level visual local cues to weigh the contour intrinsic property and mid-level visual cues on the basis of Gestalt principles for weighting the contour grouping constraint. Experimental results tested on the BSDS benchmark show that the proposed framework exhibits promising performances to capture meaningful contours in complex scenes. PMID:26492252

  19. Analytical finite element matrix elements and global matrix assembly for hierarchical 3-D vector basis functions within the hybrid finite element boundary integral method

    NASA Astrophysics Data System (ADS)

    Li, L.; Wang, K.; Li, H.; Eibert, T. F.

    2014-11-01

    A hybrid higher-order finite element boundary integral (FE-BI) technique is discussed where the higher-order FE matrix elements are computed by a fully analytical procedure and where the gobal matrix assembly is organized by a self-identifying procedure of the local to global transformation. This assembly procedure applys to both, the FE part as well as the BI part of the algorithm. The geometry is meshed into three-dimensional tetrahedra as finite elements and nearly orthogonal hierarchical basis functions are employed. The boundary conditions are implemented in a strong sense such that the boundary values of the volume basis functions are directly utilized within the BI, either for the tangential electric and magnetic fields or for the asssociated equivalent surface current densities by applying a cross product with the unit surface normals. The self-identified method for the global matrix assembly automatically discerns the global order of the basis functions for generating the matrix elements. Higher order basis functions do need more unknowns for each single FE, however, fewer FEs are needed to achieve the same satisfiable accuracy. This improvement provides a lot more flexibility for meshing and allows the mesh size to raise up to λ/3. The performance of the implemented system is evaluated in terms of computation time, accuracy and memory occupation, where excellent results with respect to precision and computation times of large scale simulations are found.

  20. A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules.

    PubMed

    Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

    2015-01-01

    A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis.

  1. A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules

    PubMed Central

    Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

    2015-01-01

    A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis. PMID:26355961

  2. A template-free CVD route to synthesize hierarchical porous ZnO films

    NASA Astrophysics Data System (ADS)

    Duan, Xiangyang; Chen, Guangde; Guo, Lu'an; Zhu, Youzhang; Ye, Honggang; Wu, Yelong

    2015-12-01

    Unique porous ZnO films were successfully synthesized on Si substrates without any catalysts or templates using chemical vapor deposition method. Unlike earlier reports, they are hierarchical porous, containing both macropores and mesopores. The zinc oxide seed layer and the weight ratio of source materials were found to be the major factors that would facilitate the synthesis of these hierarchical porous films. We found that all the macropores were surrounded by grain boundaries. As presented in the SEM images, the newborn ZnO atoms would prefer to adsorb nearby the grain boundaries and nucleate there in the growth stage. A schematic diagram based on the aforesaid phenomenon was proposed to explain the synthesis of the hierarchical porous ZnO film. An unusual strong emission peak located at 420 nm was observed in the photoluminescence spectrum. It was suggested that the emission peak was attributed to the special hierarchical porous structure, especially the grain boundaries in the nanowalls of these films.

  3. An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

    PubMed Central

    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. PMID:24489491

  4. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    NASA Astrophysics Data System (ADS)

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-12-01

    Three-dimensional (3D) porous ZnO-CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO-CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO-CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO-CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM-1cm-2, the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior.

  5. A hierarchical clustering methodology for the estimation of toxicity.

    PubMed

    Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

    2008-01-01

    ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

  6. Differentiation of Isodon japonica and Adulterants Based on Identification and Quantitation 14 Diterpenoids Using LC-MS-MS Library Search Approach and Hierarchical Cluster Analysis.

    PubMed

    Jin, Yiran; Tian, Tingting; Ma, Yinghua; Liu, Minyan; Xie, Weiwei; Wang, Xin; Xu, Huijun; Du, Yingfeng

    2016-03-01

    The aim of this study was to investigate the chemical differences between genunine Isodon japonica and its adulterants. A linear ion trap liquid chromatography with tandem mass spectrometry analytical method has been developed for the identification and quantification of 14 major diterpenoids in I. japonica. Data acquisition was multiple reaction monitoring transitions mode followed by an information-dependent acquisition using the enhanced product ion (EPI) scan in a single run. The target compounds were further identified and confirmed using an EPI spectral library. Overall validation of the assay was carried out including linearity, accuracy, precision, limits of detection and quantification. The results demonstrated that the method was selective, sensitive and reliable. The determination results of 21 batches of I. japonica and adulterants were then analyzed and differentiated by hierarchical clustering analysis. PMID:26489434

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  8. Hierarchically UVO patterned elastomeric and thermoplastic structures

    NASA Astrophysics Data System (ADS)

    Chen, Ying; Kulkarni, Manish; Marshall, Allan; Karim, Alamgir

    2014-03-01

    We demonstrate a simple yet versatile method to fabricate tunable hierarchical micro-nanostructures on flexible Poly(dimethylsiloxane) (PDMS) elastomer and thermoplastic polymer surface by a two-step process. Nanoscale patterned PDMS was obtained by imprinting compact disc (CD)/digital video disc (DVD) patterns. The second micro pattern was superposed by selective densification of PDMS by exposing to ultraviolet-ozone radiation (UVO) through micro-patterned TEM grid as a mask. The nanoscale patterns are preserved through UVO exposure step leading to formation of deep hierarchical patterns, so that for a 19 um square mesh, the micro pattern has a depth of 600nm with 6h PDMS UVO exposure time. This simple method can be promoted to fabricate hierarchical structures of thermoplastic materials (such as polystyrene), from which the mechanism of capillary imprinting and thermal stability of hierarchical patterns are investigated. This study is potentially important to various applications ranging from biomimetic scaffolds to solar cell.

  9. Efficient hierarchical interconnection for multiprocessor systems

    NASA Technical Reports Server (NTRS)

    Wei, Sizheng; Levy, Saul

    1992-01-01

    The authors present a novel approach to the design of a class of hierarchical interconnection networks for multiprocessor systems. This approach, based on an architecture providing separate networks for each level, gives a general and flexible way to construct efficient hierarchical networks. The performance and cost-effectiveness of the resulting networks are analyzed and compared in detail, using both unbuffered and buffered network models. It is shown that, if the design parameters are determined based on the degree of locality, the cost-effectiveness of a hierarchical network can be significantly improved. In addition, the authors investigate how to construct a cost-effectiveness hierarchical network by determining appropriate design parameters. Two associated algorithms are developed for this purpose.

  10. Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.

    PubMed

    Chung, Feng-Hsiang; Jin, Zhen-Hua; Hsu, Tzu-Ting; Hsu, Chueh-Lin; Liu, Hsueh-Chuan; Lee, Hoong-Chien

    2015-01-01

    Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.

  11. Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.

    PubMed

    Chung, Feng-Hsiang; Jin, Zhen-Hua; Hsu, Tzu-Ting; Hsu, Chueh-Lin; Liu, Hsueh-Chuan; Lee, Hoong-Chien

    2015-01-01

    Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases. PMID:26473729

  12. Gene-Set Local Hierarchical Clustering (GSLHC)—A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups

    PubMed Central

    Hsu, Tzu-Ting; Hsu, Chueh-Lin; Liu, Hsueh-Chuan; Lee, Hoong-Chien

    2015-01-01

    Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases. PMID:26473729

  13. Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier

    PubMed Central

    Kambhampati, Satya Samyukta; Singh, Vishal; Ramkumar, Barathram

    2015-01-01

    In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%. PMID:26609414

  14. Hierarchical Bayesian analysis of outcome- and process-based social preferences and beliefs in Dictator Games and sequential Prisoner's Dilemmas.

    PubMed

    Aksoy, Ozan; Weesie, Jeroen

    2014-05-01

    In this paper, using a within-subjects design, we estimate the utility weights that subjects attach to the outcome of their interaction partners in four decision situations: (1) binary Dictator Games (DG), second player's role in the sequential Prisoner's Dilemma (PD) after the first player (2) cooperated and (3) defected, and (4) first player's role in the sequential Prisoner's Dilemma game. We find that the average weights in these four decision situations have the following order: (1)>(2)>(4)>(3). Moreover, the average weight is positive in (1) but negative in (2), (3), and (4). Our findings indicate the existence of strong negative and small positive reciprocity for the average subject, but there is also high interpersonal variation in the weights in these four nodes. We conclude that the PD frame makes subjects more competitive than the DG frame. Using hierarchical Bayesian modeling, we simultaneously analyze beliefs of subjects about others' utility weights in the same four decision situations. We compare several alternative theoretical models on beliefs, e.g., rational beliefs (Bayesian-Nash equilibrium) and a consensus model. Our results on beliefs strongly support the consensus effect and refute rational beliefs: there is a strong relationship between own preferences and beliefs and this relationship is relatively stable across the four decision situations.

  15. Hierarchical video summarization for medical data

    NASA Astrophysics Data System (ADS)

    Zhu, Xingquan; Fan, Jianping; Elmagarmid, Ahmed K.; Aref, Walid G.

    2001-12-01

    To provide users with an overview of medical video content at various levels of abstraction which can be used for more efficient database browsing and access, a hierarchical video summarization strategy has been developed and is presented in this paper. To generate an overview, the key frames of a video are preprocessed to extract special frames (black frames, slides, clip art, sketch drawings) and special regions (faces, skin or blood-red areas). A shot grouping method is then applied to merge the spatially or temporally related shots into groups. The visual features and knowledge from the video shots are integrated to assign the groups into predefined semantic categories. Based on the video groups and their semantic categories, video summaries for different levels are constructed by group merging, hierarchical group clustering and semantic category selection. Based on this strategy, a user can select the layer of the summary to access. The higher the layer, the more concise the video summary; the lower the layer, the greater the detail contained in the summary.

  16. A rational synthesis of hierarchically porous, N-doped carbon from Mg-based MOFs: understanding the link between nitrogen content and oxygen reduction electrocatalysis.

    PubMed

    Eisenberg, David; Stroek, Wowa; Geels, Norbert J; Tanase, Stefania; Ferbinteanu, Marilena; Teat, Simon J; Mettraux, Pierre; Yan, Ning; Rothenberg, Gadi

    2016-07-27

    Controlled mixtures of novel Mg-based metal-organic frameworks (MOFs) were prepared, with H(+) or K(+) as counterions. A linear relation was found between synthesis pH and K/H ratio in the resultant mixture, establishing the tunability of the synthesis. Upon pyrolysis, these precursor mixtures yield nitrogen-doped, hierarchically porous carbons, which have good activity towards the oxygen reduction reaction (ORR) at pH 13. The nitrogen content varies significantly along the homologous carbon series (>400%, 1.3 at% to 5.7 at%), to a much greater extent than microstructural parameters such as surface area and graphitization. This allows us to isolate the positive correlation between nitrogen content and electrocatalytic oxygen reduction ORR activity in this class of metal-free, N-doped, porous carbons. PMID:27412725

  17. Hierarchical Self-Assembly of Polyoxometalate-Based Hybrids Driven by Metal Coordination and Electrostatic Interactions: From Discrete Supramolecular Species to Dense Monodisperse Nanoparticles.

    PubMed

    Izzet, Guillaume; Abécassis, Benjamin; Brouri, Dalil; Piot, Madeleine; Matt, Benjamin; Serapian, Stefano Artin; Bo, Carles; Proust, Anna

    2016-04-20

    The metal-driven self-assembly processes of a covalent polyoxometalate (POM)-based hybrid bearing remote terpyridine binding sites have been investigated. In a strongly dissociating solvent, a discrete metallomacrocycle, described as a molecular triangle, is formed and characterized by 2D diffusion NMR spectroscopy (DOSY), small-angle X-ray scattering (SAXS), and molecular modeling. In a less dissociating solvent, the primary supramolecular structure, combining negatively charged POMs and cationic metal linkers, further self-assemble through intermolecular electrostatic interactions in a reversible process. The resulting hierarchical assemblies are dense monodisperse nanoparticles composed of ca. 50 POMs that were characterized by SAXS and transmission electron microscopy (TEM). This multiscale organized system directed by metal coordination and electrostatic interactions constitutes a promising step for the future design of POM self-assemblies with controllable structure-directing factors. PMID:27019075

  18. Hierarchical structures of amorphous solids characterized by persistent homology.

    PubMed

    Hiraoka, Yasuaki; Nakamura, Takenobu; Hirata, Akihiko; Escolar, Emerson G; Matsue, Kaname; Nishiura, Yasumasa

    2016-06-28

    This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms. Then, specific distributions such as curves and islands in the PDs identify meaningful shape characteristics of the atomic configuration. Although the method can be applied to a wide variety of disordered systems, it is applied here to silica glass, the Lennard-Jones system, and Cu-Zr metallic glass as standard examples of continuous random network and random packing structures. In silica glass, the method classified the atomic rings as short-range and medium-range orders and unveiled hierarchical ring structures among them. These detailed geometric characterizations clarified a real space origin of the first sharp diffraction peak and also indicated that PDs contain information on elastic response. Even in the Lennard-Jones system and Cu-Zr metallic glass, the hierarchical structures in the atomic configurations were derived in a similar way using PDs, although the glass structures and properties substantially differ from silica glass. These results suggest that the PDs provide a unified method that extracts greater depth of geometric information in amorphous solids than conventional methods.

  19. Hierarchical structures of amorphous solids characterized by persistent homology

    PubMed Central

    Hiraoka, Yasuaki; Nakamura, Takenobu; Hirata, Akihiko; Escolar, Emerson G.; Matsue, Kaname; Nishiura, Yasumasa

    2016-01-01

    This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms. Then, specific distributions such as curves and islands in the PDs identify meaningful shape characteristics of the atomic configuration. Although the method can be applied to a wide variety of disordered systems, it is applied here to silica glass, the Lennard-Jones system, and Cu-Zr metallic glass as standard examples of continuous random network and random packing structures. In silica glass, the method classified the atomic rings as short-range and medium-range orders and unveiled hierarchical ring structures among them. These detailed geometric characterizations clarified a real space origin of the first sharp diffraction peak and also indicated that PDs contain information on elastic response. Even in the Lennard-Jones system and Cu-Zr metallic glass, the hierarchical structures in the atomic configurations were derived in a similar way using PDs, although the glass structures and properties substantially differ from silica glass. These results suggest that the PDs provide a unified method that extracts greater depth of geometric information in amorphous solids than conventional methods. PMID:27298351

  20. Guided hierarchical co-assembly of soft patchy nanoparticles

    NASA Astrophysics Data System (ADS)

    Gröschel, André H.; Walther, Andreas; Löbling, Tina I.; Schacher, Felix H.; Schmalz, Holger; Müller, Axel H. E.

    2013-11-01

    The concept of hierarchical bottom-up structuring commonly encountered in natural materials provides inspiration for the design of complex artificial materials with advanced functionalities. Natural processes have achieved the orchestration of multicomponent systems across many length scales with very high precision, but man-made self-assemblies still face obstacles in realizing well-defined hierarchical structures. In particle-based self-assembly, the challenge is to program symmetries and periodicities of superstructures by providing monodisperse building blocks with suitable shape anisotropy or anisotropic interaction patterns (`patches'). Irregularities in particle architecture are intolerable because they generate defects that amplify throughout the hierarchical levels. For patchy microscopic hard colloids, this challenge has been approached by using top-down methods (such as metal shading or microcontact printing), enabling molecule-like directionality during aggregation. However, both top-down procedures and particulate systems based on molecular assembly struggle to fabricate patchy particles controllably in the desired size regime (10-100nm). Here we introduce the co-assembly of dynamic patchy nanoparticles--that is, soft patchy nanoparticles that are intrinsically self-assembled and monodisperse--as a modular approach for producing well-ordered binary and ternary supracolloidal hierarchical assemblies. We bridge up to three hierarchical levels by guiding triblock terpolymers (length scale ~10nm) to form soft patchy nanoparticles (20-50nm) of different symmetries that, in combination, co-assemble into substructured, compartmentalized materials (>10μm) with predictable and tunable nanoscale periodicities. We establish how molecular control over polymer composition programs the building block symmetries and regulates particle positioning, offering a route to well-ordered mixed mesostructures of high complexity.

  1. Guided hierarchical co-assembly of soft patchy nanoparticles.

    PubMed

    Gröschel, André H; Walther, Andreas; Löbling, Tina I; Schacher, Felix H; Schmalz, Holger; Müller, Axel H E

    2013-11-14

    The concept of hierarchical bottom-up structuring commonly encountered in natural materials provides inspiration for the design of complex artificial materials with advanced functionalities. Natural processes have achieved the orchestration of multicomponent systems across many length scales with very high precision, but man-made self-assemblies still face obstacles in realizing well-defined hierarchical structures. In particle-based self-assembly, the challenge is to program symmetries and periodicities of superstructures by providing monodisperse building blocks with suitable shape anisotropy or anisotropic interaction patterns ('patches'). Irregularities in particle architecture are intolerable because they generate defects that amplify throughout the hierarchical levels. For patchy microscopic hard colloids, this challenge has been approached by using top-down methods (such as metal shading or microcontact printing), enabling molecule-like directionality during aggregation. However, both top-down procedures and particulate systems based on molecular assembly struggle to fabricate patchy particles controllably in the desired size regime (10-100 nm). Here we introduce the co-assembly of dynamic patchy nanoparticles--that is, soft patchy nanoparticles that are intrinsically self-assembled and monodisperse--as a modular approach for producing well-ordered binary and ternary supracolloidal hierarchical assemblies. We bridge up to three hierarchical levels by guiding triblock terpolymers (length scale ∼10 nm) to form soft patchy nanoparticles (20-50 nm) of different symmetries that, in combination, co-assemble into substructured, compartmentalized materials (>10 μm) with predictable and tunable nanoscale periodicities. We establish how molecular control over polymer composition programs the building block symmetries and regulates particle positioning, offering a route to well-ordered mixed mesostructures of high complexity.

  2. Hierarchical multifunctional nanocomposites

    NASA Astrophysics Data System (ADS)

    Ghasemi-Nejhad, Mehrdad N.

    2014-03-01

    Nanocomposites; including nano-materials such as nano-particles, nanoclays, nanofibers, nanotubes, and nanosheets; are of significant importance in the rapidly developing field of nanotechnology. Due to the nanometer size of these inclusions, their physicochemical characteristics differ significantly from those of micron size and bulk materials. The field of nanocomposites involves the study of multiphase materials where at least one of the constituent phases has one dimension less than 100 nm. This is the range where the phenomena associated with the atomic and molecular interaction strongly influence the macroscopic properties of materials. Since the building blocks of nanocomposites are at nanoscale, they have an enormous surface area with numerous interfaces between the two intermix phases. The special properties of the nano-composite arise from the interaction of its phases at the interface and/or interphase regions. By contrast, in a conventional composite based on micrometer sized filler such as carbon fibers, the interfaces between the filler and matrix constitutes have a much smaller surface-to-volume fraction of the bulk materials, and hence influence the properties of the host structure to a much smaller extent. The optimum amount of nanomaterials in the nanocomposites depends on the filler size, shape, homogeneity of particles distribution, and the interfacial bonding properties between the fillers and matrix. The promise of nanocomposites lies in their multifunctionality, i.e., the possibility of realizing unique combination of properties unachievable with traditional materials. The challenges in reaching this promise are tremendous. They include control over the distribution in size and dispersion of the nanosize constituents, and tailoring and understanding the role of interfaces between structurally or chemically dissimilar phases on bulk properties. While the properties of the matrix can be improved by the inclusions of nanomaterials, the

  3. Hierarchically Structured Nanomaterials for Electrochemical Energy Conversion.

    PubMed

    Trogadas, Panagiotis; Ramani, Vijay; Strasser, Peter; Fuller, Thomas F; Coppens, Marc-Olivier

    2016-01-01

    Hierarchical nanomaterials are highly suitable as electrocatalysts and electrocatalyst supports in electrochemical energy conversion devices. The intrinsic kinetics of an electrocatalyst are associated with the nanostructure of the active phase and the support, while the overall properties are also affected by the mesostructure. Therefore, both structures need to be controlled. A comparative state-of-the-art review of catalysts and supports is provided along with detailed synthesis methods. To further improve the design of these hierarchical nanomaterials, in-depth research on the effect of materials architecture on reaction and transport kinetics is necessary. Inspiration can be derived from nature, which is full of very effective hierarchical structures. Developing fundamental understanding of how desired properties of biological systems are related to their hierarchical architecture can guide the development of novel catalytic nanomaterials and nature-inspired electrochemical devices. PMID:26549054

  4. High-performance supercapacitor and lithium-ion battery based on 3D hierarchical NH4F-induced nickel cobaltate nanosheet-nanowire cluster arrays as self-supported electrodes.

    PubMed

    Chen, Yuejiao; Qu, Baihua; Hu, Lingling; Xu, Zhi; Li, Qiuhong; Wang, Taihong

    2013-10-21

    A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions at the nanoscale, fast ion and electron transfer and good strain accommodation. Thus, when it is used for supercapacitor testing, a specific capacitance of 1069 F g(-1) at a very high current density of 100 A g(-1) was obtained. Even after more than 10,000 cycles at various large current densities, a capacitance of 2000 F g(-1) at 10 A g(-1) with 93.8% retention can be achieved. It also exhibits a high-power density (26.1 kW kg(-1)) at a discharge current density of 80 A g(-1). When used as an anode material for lithium-ion batteries (LIBs), it presents a high reversible capacity of 976 mA h g(-1) at a rate of 200 mA g(-1) with good cycling stability and rate capability. This array material is rarely used as an anode material. Our results show that this unique 3D hierarchical porous nickel cobaltite is promising for electrochemical energy applications.

  5. Create and Publish a Hierarchical Progressive Survey (HiPS)

    NASA Astrophysics Data System (ADS)

    Fernique, P.; Boch, T.; Pineau, F.; Oberto, A.

    2014-05-01

    Since 2009, the CDS promotes a method for visualizing based on the HEALPix sky tessellation. This method, called “Hierarchical Progressive Survey" or HiPS, allows one to display a survey progressively. It is particularly suited for all-sky surveys or deep fields. This visualization method is now integrated in several applications, notably Aladin, the SiTools/MIZAR CNES framework, and the recent HTML5 “Aladin Lite". Also, more than one hundred surveys are already available in this view mode. In this article, we will present the progress concerning this method and its recent adaptation to the astronomical catalogs such as the GAIA simulation.

  6. Detection of Significant Groups in Hierarchical Clustering by Resampling

    PubMed Central

    Sebastiani, Paola; Perls, Thomas T.

    2016-01-01

    Hierarchical clustering is a simple and reproducible technique to rearrange data of multiple variables and sample units and visualize possible groups in the data. Despite the name, hierarchical clustering does not provide clusters automatically, and “tree-cutting” procedures are often used to identify subgroups in the data by cutting the dendrogram that represents the similarities among groups used in the agglomerative procedure. We introduce a resampling-based technique that can be used to identify cut-points of a dendrogram with a significance level based on a reference distribution for the heights of the branch points. The evaluation on synthetic data shows that the technique is robust in a variety of situations. An example with real biomarker data from the Long Life Family Study shows the usefulness of the method. PMID:27551289

  7. Detection of Significant Groups in Hierarchical Clustering by Resampling.

    PubMed

    Sebastiani, Paola; Perls, Thomas T

    2016-01-01

    Hierarchical clustering is a simple and reproducible technique to rearrange data of multiple variables and sample units and visualize possible groups in the data. Despite the name, hierarchical clustering does not provide clusters automatically, and "tree-cutting" procedures are often used to identify subgroups in the data by cutting the dendrogram that represents the similarities among groups used in the agglomerative procedure. We introduce a resampling-based technique that can be used to identify cut-points of a dendrogram with a significance level based on a reference distribution for the heights of the branch points. The evaluation on synthetic data shows that the technique is robust in a variety of situations. An example with real biomarker data from the Long Life Family Study shows the usefulness of the method. PMID:27551289

  8. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning.

    PubMed

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-01-01

    Three-dimensional (3D) porous ZnO-CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO-CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO-CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO-CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM(-1)cm(-2), the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior. PMID:25488502

  9. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    PubMed Central

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-01-01

    Three-dimensional (3D) porous ZnO–CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO–CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO–CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO–CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM−1cm−2, the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior. PMID:25488502

  10. Analysis of the North American Breeding Bird Survey using hierarchical models

    USGS Publications Warehouse

    Sauer, John R.; Link, William A.

    2011-01-01

    We analyzed population change for 420 bird species from the North American Breeding Bird Survey (BBS) using a hierarchical log-linear model, and compared the results to route regression analysis results. Survey-wide trend estimates based on the hierarchical model were more precise than estimates from the earlier analysis. No consistent pattern of differences existed in magnitude of trends between the analysis methods. Survey-wide trend estimates changed substantially for 15 species between route regression and hierarchical model analyses. We compared regional estimates for states, provinces, and Bird Conservation Regions; differences observed in these regional analyses are likely a consequence of the route regression procedure's inadequate accommodation of temporal differences in survey effort. We used species-specific hierarchical model results to estimate composite change for groups of birds associated with major habitats and migration types. Grassland, aridland, and eastern forest obligate bird species declined, while urban/suburban species increased over the interval 1968-2008. No migration status group experienced significant changes, although Nearctic-Neotropical migrant species showed intervals of decline and permanent resident species increased almost 20% during the interval. Hierarchical model results better portrayed patterns of population change over time than route regression results; we recommend use of hierarchical models for BBS analyses.

  11. Biomimetic cellular metals-using hierarchical structuring for energy absorption.

    PubMed

    Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

    2016-07-19

    Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form

  12. Biomimetic cellular metals-using hierarchical structuring for energy absorption.

    PubMed

    Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

    2016-01-01

    Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form

  13. A hierarchical exact accelerated stochastic simulation algorithm

    PubMed Central

    Orendorff, David; Mjolsness, Eric

    2012-01-01

    A new algorithm, “HiER-leap” (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled “blocks” and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms. PMID:23231214

  14. Efficient scalable algorithms for hierarchically semiseparable matrices

    SciTech Connect

    Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de

    2011-09-14

    Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.

  15. Hierarchical Nanoceramics for Industrial Process Sensors

    SciTech Connect

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

    2011-07-15

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

  16. System and method for knowledge based matching of users in a network

    DOEpatents

    Verspoor, Cornelia Maria; Sims, Benjamin Hayden; Ambrosiano, John Joseph; Cleland, Timothy James

    2011-04-26

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

  17. Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

    SciTech Connect

    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

  18. Hierarchical multilayer perceptron network-based fusion algorithms for detection/classification of mines using multiple acoustic images and magnetic data

    NASA Astrophysics Data System (ADS)

    Bello, Martin G.

    1996-05-01

    Hierarchical neural network approaches have been developed first for combining high and low frequency (HF and LF) Side Scan Sonar imagery, and then for the combination of both acoustic images and Magnetic data. The adopted acoustic data fusion approach consists in a image-screening/HF, LF blob matching stage, followed by an information fusion/classification stage. Three variants of the information fusion/classification algorithm were conceived and evaluated based on `aggregate-feature-combining', `neural-network-discriminant-combining', and individual classifier `decision-based-combining', respectively. The `discriminant- combining' case yielded the best classification performance, and when compared with individual HF, LF classifier performance resulted in at least an order of magnitude reduction in the density of false alarms. Next, results are obtained for combining both acoustic and magnetic data using the described high and low frequency side scan sonar discriminant combining fusion algorithm as a starting point. In the next step, acoustic image pair `tokens' are associated with magnetic `tokens', resulting in three classes of resulting `tokens': `associated' acoustic-pair and magnetic tokens, isolated acoustic-pair tokens, and isolated magnetic `tokens'. Neural network output discriminants are derived for each of the three types of tokens mentioned above, and are employed to make classification decisions. The resulting Detection/Classification Algorithm is evaluated based on a combined ground truth obtained from both acoustic and magnetic sources.

  19. Using Bayesian Networks to Model Hierarchical Relationships in Epidemiological Studies

    PubMed Central

    2011-01-01

    OBJECTIVES To propose an alternative procedure, based on a Bayesian network (BN), for estimation and prediction, and to discuss its usefulness for taking into account the hierarchical relationships among covariates. METHODS The procedure is illustrated by modeling the risk of diarrhea infection for 2,740 children aged 0 to 59 months in Cameroon. We compare the procedure with a standard logistic regression and with a model based on multi-level logistic regression. RESULTS The standard logistic regression approach is inadequate, or at least incomplete, in that it does not attempt to account for potentially causal relationships between risk factors. The multi-level logistic regression does model the hierarchical structure, but does so in a piecewise manner; the resulting estimates and interpretations differ from those of the BN approach proposed here. An advantage of the BN approach is that it enables one to determine the probability that a risk factor (and/or the outcome) is in any specific state, given the states of the others. The currently available approaches can only predict the outcome (disease), given the states of the covariates. CONCLUSION A major advantage of BNs is that they can deal with more complex interrelationships between variables whereas competing approaches deal at best only with hierarchical ones. We propose that BN be considered as well as a worthwhile method for summarizing the data in epidemiological studies whose aim is understanding the determinants of diseases and quantifying their effects. PMID:21779534

  20. A hierarchical model for spatial capture-recapture data

    USGS Publications Warehouse

    Royle, J. Andrew; Young, K.V.

    2008-01-01

    Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

  1. Electrochemical properties and controlled-synthesis of hierarchical {beta}-Ni(OH){sub 2} micro-flowers and hollow microspheres

    SciTech Connect

    Wang, Yong; Zhu, Qingshan

    2010-12-15

    {beta}-Ni(OH){sub 2} hierarchical micro-flowers, hierarchical hollow microspheres and nanosheets were synthesized via a facile, single-step and selected-control hydrothermal method. Both hierarchical micro-flowers and hierarchical hollow microspheres were built from two-dimensional nanosheets with thickness of 50-100 nm. The as-obtained products were characterized by Brunauer-Emmett-Teller (BET) surface area analysis, X-ray powder diffraction (XRD) and field emission scanning electron microscopy (FESEM). It was observed that marked morphological changes in {beta}-Ni(OH){sub 2} depended on the initial concentrations of Ni{sup 2+} ions and glycine. A possible growth mechanism was proposed based on experimental results. In addition, the effect of morphology on the electrochemical properties was also investigated. Both hierarchical micro-flowers and hierarchical hollow microspheres exhibited enhanced specific capacity and high-rate discharge ability as compared with pure Ni(OH){sub 2} nanosheets. Investigations confirmed that hierarchical structures had a pronounced influence upon the electrochemical performance of nickel hydroxide.

  2. Grinding Wheel Condition Monitoring with Hidden Markov Model-Based Clustering Methods

    SciTech Connect

    Liao, T. W.; Hua, G; Qu, Jun; Blau, Peter Julian

    2006-01-01

    Hidden Markov model (HMM) is well known for sequence modeling and has been used for condition monitoring. However, HMM-based clustering methods are developed only recently. This article proposes a HMM-based clustering method for monitoring the condition of grinding wheel used in grinding operations. The proposed method first extract features from signals based on discrete wavelet decomposition using a moving window approach. It then generates a distance (dissimilarity) matrix using HMM. Based on this distance matrix several hierarchical and partitioning-based clustering algorithms are applied to obtain clustering results. The proposed methodology was tested with feature sequences extracted from acoustic emission signals. The results show that clustering accuracy is dependent upon cutting condition. Higher material removal rate seems to produce more discriminatory signals/features than lower material removal rate. The effect of window size, wavelet decomposition level, wavelet basis, clustering algorithm, and data normalization were also studied.

  3. Effects of acid on the microstructures and properties of three-dimensional TiO2 hierarchical structures by solvothermal method

    NASA Astrophysics Data System (ADS)

    Zhou, Jing; Song, Bin; Zhao, Gaoling; Han, Gaorong

    2012-04-01

    Three-dimensional (3D) TiO2 hierarchical structures with various microstructures have been successfully synthesized via a surfactant-free and single-step solvothermal route, in which hydrochloric acid (HCl), nitric acid (HNO3), and acetic acid (HAc) are employed as the acid medium, respectively. The effects of acid medium on the microstructures and properties of 3D TiO2 hierarchical structure have been studied. The results indicate that 3D dandelion-like microspheres assembled of radial rutile nanorods are obtained in the sample prepared with HCl. Both the fraction of rutile and the diameter of nanorod enhance with the increasing HCl concentration. For the products derived from either HNO3 or HAc, 3D spheres composed of anatase nanoparticles are present. The 3D dandelion-like TiO2 hierarchical structures show low reflectance and efficient light harvesting since this ordered rod geometry offers a light-transfer path for incident light as well as multiple reflective and scattering effects. Moreover, 3D TiO2 with this unique topology shows superior photocatalytic activity despite low surface area, which can be ascribed to the enhanced light harvesting, fast electron transport, and low electron/hole recombination loss.

  4. Effects of acid on the microstructures and properties of three-dimensional TiO2 hierarchical structures by solvothermal method

    PubMed Central

    2012-01-01

    Three-dimensional (3D) TiO2 hierarchical structures with various microstructures have been successfully synthesized via a surfactant-free and single-step solvothermal route, in which hydrochloric acid (HCl), nitric acid (HNO3), and acetic acid (HAc) are employed as the acid medium, respectively. The effects of acid medium on the microstructures and properties of 3D TiO2 hierarchical structure have been studied. The results indicate that 3D dandelion-like microspheres assembled of radial rutile nanorods are obtained in the sample prepared with HCl. Both the fraction of rutile and the diameter of nanorod enhance with the increasing HCl concentration. For the products derived from either HNO3 or HAc, 3D spheres composed of anatase nanoparticles are present. The 3D dandelion-like TiO2 hierarchical structures show low reflectance and efficient light harvesting since this ordered rod geometry offers a light-transfer path for incident light as well as multiple reflective and scattering effects. Moreover, 3D TiO2 with this unique topology shows superior photocatalytic activity despite low surface area, which can be ascribed to the enhanced light harvesting, fast electron transport, and low electron/hole recombination loss. PMID:22500985

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Advanced hierarchical distance sampling

    USGS Publications Warehouse

    Royle, Andy

    2016-01-01

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

  7. Full hierarchic versus non-hierarchic classification approaches for mapping sealed surfaces at the rural-urban fringe using high-resolution satellite data.

    PubMed

    De Roeck, Tim; Van de Voorde, Tim; Canters, Frank

    2009-01-01

    Since 2008 more than half of the world population is living in cities and urban sprawl is continuing. Because of these developments, the mapping and monitoring of urban environments and their surroundings is becoming increasingly important. In this study two object-oriented approaches for high-resolution mapping of sealed surfaces are compared: a standard non-hierarchic approach and a full hierarchic approach using both multi-layer perceptrons and decision trees as learning algorithms. Both methods outperform the standard nearest neighbour classifier, which is used as a benchmark scenario. For the multi-layer perceptron approach, applying a hierarchic classification strategy substantially increases the accuracy of the classification. For the decision tree approach a one-against-all hierarchic classification strategy does not lead to an improvement of classification accuracy compared to the standard all-against-all approach. Best results are obtained with the hierarchic multi-layer perceptron classification strategy, producing a kappa value of 0.77. A simple shadow reclassification procedure based on characteristics of neighbouring objects further increases the kappa value to 0.84.

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Managing Clustered Data Using Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  10. DOM Based XSS Detecting Method Based on Phantomjs

    NASA Astrophysics Data System (ADS)

    Dong, Ri-Zhan; Ling, Jie; Liu, Yi

    Because malicious code does not appear in html source code, DOM based XSS cannot be detected by traditional methods. By analyzing the causes of DOM based XSS, this paper proposes a detection method of DOM based XSS based on phantomjs. This paper uses function hijacking to detect dangerous operation and achieves a prototype system. Comparing with existing tools shows that the system improves the detection rate and the method is effective to detect DOM based XSS.

  11. Tucker2 Hierarchical Classes Analysis

    ERIC Educational Resources Information Center

    Ceulemans, Eva; Van Mechelen, Iven

    2004-01-01

    This paper presents a new hierarchical classes model, called Tucker2-HICLAS, for binary three-way three-mode data. As any three-way hierarchical classes model, the Tucker2-HICLAS model includes a representation of the association relation among the three modes and a hierarchical classification of the elements of each mode. A distinctive feature of…

  12. Analysis hierarchical model for discrete event systems

    NASA Astrophysics Data System (ADS)

    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.

  13. Intelligent controllers as hierarchical stochastic automata.

    PubMed

    Lima, P U; Saridis, G N

    1999-01-01

    This paper introduces a design methodology for intelligent controllers, based on a hierarchical linguistic model of command translation by tasks-primitive tasks-primitive actions, and on a two-stage hierarchical learning stochastic automaton that models the translation interfaces of a three-level hierarchical intelligent controller. The methodology relies on the designer's a priori knowledge on how to implement by primitive actions the different primitive tasks which define the intelligent controller. A cost function applicable to any primitive task is introduced and used to learn on-line the optimal choices from the corresponding predesigned sets of primitive actions. The same concept applies to the optimal tasks for each command, whose choice is based on conflict sets of stochastic grammar productions. Optional designs can be compared using this performance measure. A particular design evolves towards the command translation (by tasks-primitive tasks-primitive actions) that minimizes the cost function.

  14. How Hierarchical Topics Evolve in Large Text Corpora.

    PubMed

    Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

    2014-12-01

    Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

  15. How Hierarchical Topics Evolve in Large Text Corpora.

    PubMed

    Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

    2014-12-01

    Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data. PMID:26356942

  16. Free-standing iridium and rhodium-based hierarchically-coiled ultrathin nanosheets for highly selective reduction of nitrobenzene to azoxybenzene under ambient conditions.

    PubMed

    Zhang, Zhi-Ping; Wang, Xin-Yu; Yuan, Kun; Zhu, Wei; Zhang, Tao; Wang, Yu-Hao; Ke, Jun; Zheng, Xiao-Yu; Yan, Chun-Hua; Zhang, Ya-Wen

    2016-08-25

    The fabrication of atom-layered two dimensional (2D) noble metal nanosheets (NSs) in a face-centered cubic (fcc) structure is of broad scientific and technological importance, yet this remains a challenge due to the intrinsic cubic symmetry and high surface energy of fcc noble metals. Herein, we report a solid-liquid interface mediated 2D growth method towards the synthesis of hierarchically-coiled ultrathin Ir NSs (thickness <2 nm) and Rh NSs (0.8 nm thick), and bimetallic Ir-Rh NSs (1.2 nm thick) and Pt-Rh NSs (1.2 nm thick) using the benzyl alcohol solvothermal approach. The formation of NSs was attributed to the 2D oriented attachment of tiny seeds through the lateral growth stemming from the abundant defect sites of the seeds produced in the heterogeneous system. The free-standing Ir NSs, Rh NSs and Ir-Rh NSs exhibited high selectivities (from 83.9% to 88.5%) towards the selective reduction of nitrobenzene to azoxybenzene in ethanol at room temperature with 1 atm of hydrogen, because the condensation step of nitrosobenzene (PhNO) and phenylhydroxylamine (PhNHOH) was more exothermic than the dissociation step of Ph-NHOH on the (111) facets of the NSs under alkaline conditions, as indicated by density functional theory (DFT) calculations. PMID:27526938

  17. Facile Preparation of Hierarchical Structures Using Crystallization-Kinetics Driven Self-Assembly.

    PubMed

    Cai, Jinguang; Lv, Chao; Watanabe, Akira

    2015-08-26

    Hierarchical structures (HSs) constructed by nanoparticle-based building blocks possess not only the properties of the primary building blocks but also collective properties of the assemblies. Here we report the facile preparation of hierarchical Ag nanoparticles/polyhedral oligomeric silsequioxane molecule (POSS) hybrid branched structures within tens of seconds by using spin-coating and doctor-blade methods. An assembly mechanism mainly controlled by POSS-crystallization kinetics and space resistance of Ag nanoparticles toward the diffusion of POSS molecules was tentatively proposed. It was demonstrated as a universal method for the preparation of hierarchical hybrid branched structures on arbitrary substrates, as well as by using other different POSS and inorganic nanoparticles. As a demonstration, Ag hierarchical structures obtained by heat treatment exhibit excellent SERS performance with enhancement factors as high as on the order of 10(7), making them promising sensors for the detection of trace amount of analyte adsorbed on the surface. Two-dimensional SERS mapping was also demonstrated by using a direct imaging system with high mapping speed and high resolution. Moreover, the substrates with Ag hierarchical structures were used as a SERS sensor for in situ detection due to the excellent SERS performance and stability of the structures.

  18. Time Synchronization in Hierarchical TESLA Wireless Sensor Networks

    SciTech Connect

    Jason L. Wright; Milos Manic

    2009-08-01

    Time synchronization and event time correlation are important in wireless sensor networks. In particular, time is used to create a sequence events or time line to answer questions of cause and effect. Time is also used as a basis for determining the freshness of received packets and the validity of cryptographic certificates. This paper presents secure method of time synchronization and event time correlation for TESLA-based hierarchical wireless sensor networks. The method demonstrates that events in a TESLA network can be accurately timestamped by adding only a few pieces of data to the existing protocol.

  19. Hierarchical object-based classification of ultra-high-resolution digital mapping camera (DMC) imagery for rangeland mapping and assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ultra high resolution digital aerial photography has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands...

  20. Student Conceptions about the DNA Structure within a Hierarchical Organizational Level: Improvement by Experiment- and Computer-Based Outreach Learning

    ERIC Educational Resources Information Center

    Langheinrich, Jessica; Bogner, Franz X.

    2015-01-01

    As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module.…

  1. Enhanced Deployment Strategy for Role-Based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

    ERIC Educational Resources Information Center

    Gendreau, Audrey

    2014-01-01

    Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research,…

  2. Hyperspectral image-based methods for spectral diversity

    NASA Astrophysics Data System (ADS)

    Sotomayor, Alejandro; Medina, Ollantay; Chinea, J. D.; Manian, Vidya

    2015-05-01

    Hyperspectral images are an important tool to assess ecosystem biodiversity. To obtain more precise analysis of biodiversity indicators that agree with indicators obtained using field data, analysis of spectral diversity calculated from images have to be validated with field based diversity estimates. The plant species richness is one of the most important indicators of biodiversity. This indicator can be measured in hyperspectral images considering the Spectral Variation Hypothesis (SVH) which states that the spectral heterogeneity is related to spatial heterogeneity and thus to species richness. The goal of this research is to capture spectral heterogeneity from hyperspectral images for a terrestrial neo tropical forest site using Vector Quantization (VQ) method and then use the result for prediction of plant species richness. The results are compared with that of Hierarchical Agglomerative Clustering (HAC). The validation of the process index is done calculating the Pearson correlation coefficient between the Shannon entropy from actual field data and the Shannon entropy computed in the images. One of the advantages of developing more accurate analysis tools would be the extension of the analysis to larger zones. Multispectral image with a lower spatial resolution has been evaluated as a prospective tool for spectral diversity.

  3. Nested Hierarchical Dirichlet Processes.

    PubMed

    Paisley, John; Wang, Chong; Blei, David M; Jordan, Michael I

    2015-02-01

    We develop a nested hierarchical Dirichlet process (nHDP) for hierarchical topic modeling. The nHDP generalizes the nested Chinese restaurant process (nCRP) to allow each word to follow its own path to a topic node according to a per-document distribution over the paths on a shared tree. This alleviates the rigid, single-path formulation assumed by the nCRP, allowing documents to easily express complex thematic borrowings. We derive a stochastic variational inference algorithm for the model, which enables efficient inference for massive collections of text documents. We demonstrate our algorithm on 1.8 million documents from The New York Times and 2.7 million documents from Wikipedia. PMID:26353240

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

    PubMed

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

    2014-08-01

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

  5. Nanorainforest solar cells based on multi-junction hierarchical p-Si/n-CdS/n-ZnO nanoheterostructures

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Zhao, Qing; Laurent, Kevin; Leprince-Wang, Y.; Liao, Zhi-Min; Yu, Dapeng

    2011-12-01

    Solar cells based on one-dimensional nanostructures have recently emerged as one of the most promising candidates to achieve high-efficiency solar energy conversion due to their reduced optical reflection, enhanced light absorption, and enhanced carrier collection. In nature, the rainforest, consisting of several stereo layers of vegetation, is the highest solar-energy-using ecosystem. Herein, we gave an imitation of the rainforest configuration in nanostructure-based solar cell design. Novel multi-layer nanorainforest solar cells based on p-Si nanopillar array/n-CdS nanoparticles/n-ZnO nanowire array heterostructures were achieved via a highly accessible, reproducible and controllable fabrication process. By choosing materials with appropriate bandgaps, an efficient light absorption and enhanced light harvesting were achieved due to the wide range of the solar spectrum covered. Si nanopillar arrays were introduced as direct conduction pathways for photon-generated charges' efficient collection and transport. The unique strategy using PMMA as a void-filling material to obtain a continuous, uniform and low resistance front electrode has significantly improved the overall light conversion efficiency by two orders of magnitude. These results demonstrate that nanorainforest solar cells, along with wafer-scale, low-cost and easily controlled processing, open up substantial opportunities for nanostructure photovoltaic devices.Solar cells based on one-dimensional nanostructures have recently emerged as one of the most promising candidates to achieve high-efficiency solar energy conversion due to their reduced optical reflection, enhanced light absorption, and enhanced carrier collection. In nature, the rainforest, consisting of several stereo layers of vegetation, is the highest solar-energy-using ecosystem. Herein, we gave an imitation of the rainforest configuration in nanostructure-based solar cell design. Novel multi-layer nanorainforest solar cells based on p

  6. Hierarchical video summarization

    NASA Astrophysics Data System (ADS)

    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.

  7. Hierarchical assembly of diphenylalanine into dendritic nanoarchitectures.

    PubMed

    Han, Tae Hee; Oh, Jun Kyun; Lee, Gyoung-Ja; Pyun, Su-Il; Kim, Sang Ouk

    2010-09-01

    Highly ordered, multi-dimensional dendritic nanoarchitectures were created via self-assembly of diphenylalanine from an acidic buffer solution. The self-similarity of dendritic structures was characterized by examining their fractal dimensions with the box-counting method. The fractal dimension was determined to be 1.7, which demonstrates the fractal dimension of structures generated by diffusion limited aggregation on a two-dimensional substrate surface. By confining the dendritic assembly of diphenylalanine within PDMS microchannels, the self-similar dendritic growth could be hierarchically directed to create linearly assembled nanoarchitectures. Our approach offers a novel pathway for creating and directing hierarchical nanoarchitecture from biomolecular assembly. PMID:20605423

  8. Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: assessment in two blind tests.

    PubMed

    Ołdziej, S; Czaplewski, C; Liwo, A; Chinchio, M; Nanias, M; Vila, J A; Khalili, M; Arnautova, Y A; Jagielska, A; Makowski, M; Schafroth, H D; Kaźmierkiewicz, R; Ripoll, D R; Pillardy, J; Saunders, J A; Kang, Y K; Gibson, K D; Scheraga, H A

    2005-05-24

    Recent improvements in the protein-structure prediction method developed in our laboratory, based on the thermodynamic hypothesis, are described. The conformational space is searched extensively at the united-residue level by using our physics-based UNRES energy function and the conformational space annealing method of global optimization. The lowest-energy coarse-grained structures are then converted to an all-atom representation and energy-minimized with the ECEPP/3 force field. The procedure was assessed in two recent blind tests of protein-structure prediction. During the first blind test, we predicted large fragments of alpha and alpha+beta proteins [60-70 residues with C(alpha) rms deviation (rmsd) <6 A]. However, for alpha+beta proteins, significant topological errors occurred despite low rmsd values. In the second exercise, we predicted whole structures of five proteins (two alpha and three alpha+beta, with sizes of 53-235 residues) with remarkably good accuracy. In particular, for the genomic target TM0487 (a 102-residue alpha+beta protein from Thermotoga maritima), we predicted the complete, topologically correct structure with 7.3-A C(alpha) rmsd. So far this protein is the largest alpha+beta protein predicted based solely on the amino acid sequence and a physics-based potential-energy function and search procedure. For target T0198, a phosphate transport system regulator PhoU from T. maritima (a 235-residue mainly alpha-helical protein), we predicted the topology of the whole six-helix bundle correctly within 8 A rmsd, except the 32 C-terminal residues, most of which form a beta-hairpin. These and other examples described in this work demonstrate significant progress in physics-based protein-structure prediction.

  9. Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: Assessment in two blind tests

    PubMed Central

    Ołdziej, S.; Czaplewski, C.; Liwo, A.; Chinchio, M.; Nanias, M.; Vila, J. A.; Khalili, M.; Arnautova, Y. A.; Jagielska, A.; Makowski, M.; Schafroth, H. D.; Kaźmierkiewicz, R.; Ripoll, D. R.; Pillardy, J.; Saunders, J. A.; Kang, Y. K.; Gibson, K. D.; Scheraga, H. A.

    2005-01-01

    Recent improvements in the protein-structure prediction method developed in our laboratory, based on the thermodynamic hypothesis, are described. The conformational space is searched extensively at the united-residue level by using our physics-based UNRES energy function and the conformational space annealing method of global optimization. The lowest-energy coarse-grained structures are then converted to an all-atom representation and energy-minimized with the ECEPP/3 force field. The procedure was assessed in two recent blind tests of protein-structure prediction. During the first blind test, we predicted large fragments of α and α+β proteins [60–70 residues with Cα rms deviation (rmsd) <6 Å]. However, for α+β proteins, significant topological errors occurred despite low rmsd values. In the second exercise, we predicted whole structures of five proteins (two α and three α+β, with sizes of 53–235 residues) with remarkably good accuracy. In particular, for the genomic target TM0487 (a 102-residue α+β protein from Thermotoga maritima), we predicted the complete, topologically correct structure with 7.3-Å Cα rmsd. So far this protein is the largest α+β protein predicted based solely on the amino acid sequence and a physics-based potential-energy function and search procedure. For target T0198, a phosphate transport system regulator PhoU from T. maritima (a 235-residue mainly α-helical protein), we predicted the topology of the whole six-helix bundle correctly within 8 Å rmsd, except the 32 C-terminal residues, most of which form a β-hairpin. These and other examples described in this work demonstrate significant progress in physics-based protein-structure prediction. PMID:15894609

  10. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  11. Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D

    PubMed Central

    Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

    2014-01-01

    A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent. PMID:25834481

  12. Untraditional approach to complex hierarchical periodic arrays with trinary stepwise architectures of micro-, submicro-, and nanosized structures based on binary colloidal crystals and their fine structure enhanced properties.

    PubMed

    Li, Yue; Koshizaki, Naoto; Wang, Hongqiang; Shimizu, Yoshiki

    2011-12-27

    A unique approach for fabricating complex hierarchical periodic arrays with trinary stepwise architectures of micro- and submicro- as well as nanosized structures by combining a novel double-layered binary colloidal crystal with pulsed laser deposition techniques is developed. The present strategy is universal and nanostructures with different materials can be easily prepared in the complex hierarchical periodic arrays. This approach offers the advantage of low costs compared to conventional lithographic techniques. These as-prepared unique structures cannot be directly fabricated by conventional lithography. These special hierarchically structured arrays demonstrate fine structure-enhanced performances, including superhydrophilicity without UV irradiation and surface enhanced Raman scattering (SERS), which is highly valuable for designing micro/nanodevices, such as biosensors or microfluidic devices.

  13. Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

    PubMed Central

    Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

  14. Hierarchical models and the analysis of bird survey information

    USGS Publications Warehouse

    Sauer, J.R.; Link, W.A.

    2003-01-01

    Management of birds often requires analysis of collections of estimates. We describe a hierarchical modeling approach to the analysis of these data, in which parameters associated with the individual species estimates are treated as random variables, and probability statements are made about the species parameters conditioned on the data. A Markov-Chain Monte Carlo (MCMC) procedure is used to fit the hierarchical model. This approach is computer intensive, and is based upon simulation. MCMC allows for estimation both of parameters and of derived statistics. To illustrate the application of this method, we use the case in which we are interested in attributes of a collection of estimates of population change. Using data for 28 species of grassland-breeding birds from the North American Breeding Bird Survey, we estimate the number of species with increasing populations, provide precision-adjusted rankings of species trends, and describe a measure of population stability as the probability that the trend for a species is within a certain interval. Hierarchical models can be applied to a variety of bird survey applications, and we are investigating their use in estimation of population change from survey data.

  15. Impulse-based methods for fluid flow

    SciTech Connect

    Cortez, R.

    1995-05-01

    A Lagrangian numerical method based on impulse variables is analyzed. A relation between impulse vectors and vortex dipoles with a prescribed dipole moment is presented. This relation is used to adapt the high-accuracy cutoff functions of vortex methods for use in impulse-based methods. A source of error in the long-time implementation of the impulse method is explained and two techniques for avoiding this error are presented. An application of impulse methods to the motion of a fluid surrounded by an elastic membrane is presented.

  16. Metal oxide nanostructures with hierarchical morphology

    DOEpatents

    Ren, Zhifeng; Lao, Jing Yu; Banerjee, Debasish

    2007-11-13

    The present invention relates generally to metal oxide materials with varied symmetrical nanostructure morphologies. In particular, the present invention provides metal oxide materials comprising one or more metallic oxides with three-dimensionally ordered nanostructural morphologies, including hierarchical morphologies. The present invention also provides methods for producing such metal oxide materials.

  17. Types of Online Hierarchical Repository Structures

    ERIC Educational Resources Information Center

    Hershkovitz, Arnon; Azran, Ronit; Hardof-Jaffe, Sharon; Nachmias, Rafi

    2011-01-01

    This study presents an empirical investigation of online hierarchical repositories of items presented to university students in Web-supported course websites, using Web mining methods. To this end, data from 1747 courses were collected, and the use of online repositories of content items in these courses was examined. At a later stage, courses…

  18. Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

    PubMed Central

    Varshavsky, Roy; Horn, David; Linial, Michal

    2008-01-01

    Background A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. Methodology/Principal Findings We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. Conclusions Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide

  19. Unveiling Surface Redox Charge Storage of Interacting Two-Dimensional Hetero-Nanosheets in Hierarchical Architectures

    SciTech Connect

    Mahmood, Qasim; Bak, Seong-Min; Kim, Min G.; Yun, Sol; Yang, Xiao-Qing; Shin, Hyeon S.; Kim, Woo S.; Braun, Paul V.; Park, Ho S.

    2015-03-03

    Two-dimensional (2D) heteronanosheets are currently the focus of intense study due to the unique properties that emerge from the interplay between two low-dimensional nanomaterials with different properties. However, the properties and new phenomena based on the two 2D heteronanosheets interacting in a 3D hierarchical architecture have yet to be explored. Here, we unveil the surface redox charge storage mechanism of surface-exposed WS2 nanosheets assembled in a 3D hierarchical heterostructure using in situ synchrotron X-ray absorption and Raman spectroscopic methods. The surface dominating redox charge storage of WS2 is manifested in a highly reversible and ultrafast capacitive fashion due to the interaction of heteronanosheets and the 3D connectivity of the hierarchical structure. In contrast, compositionally identical 2D WS2 structures fail to provide a fast and high capacitance with different modes of lattice vibration. The distinctive surface capacitive behavior of 3D hierarchically structured heteronanosheets is associated with rapid proton accommodation into the in-plane W–S lattice (with the softening of the E2g bands), the reversible redox transition of the surface-exposed intralayers residing in the electrochemically active 1T phase of WS2 (with the reversible change in the interatomic distance and peak intensity of W–W bonds), and the change in the oxidation state during the proton insertion/deinsertion process. This proposed mechanism agrees with the dramatic improvement in the capacitive performance of the two heteronanosheets coupled in the hierarchical structure.

  20. Hierarchically structured, hyaluronic acid-based hydrogel matrices via the covalent integration of microgels into macroscopic networks$

    PubMed Central

    Jha, Amit K.; Malik, Manisha S.; Farach-Carson, Mary C.; Duncan, Randall L.; Jia, Xinqiao

    2010-01-01

    We aimed to develop biomimetic hydrogel matrices that not only exhibit structural hierarchy and mechanical integrity, but also present biological cues in a controlled fashion. To this end, photocrosslinkable, hyaluronic acid (HA)-based hydrogel particles (HGPs) were synthesized via an inverse emulsion crosslinking process followed by chemical modification with glycidyl methacrylate (GMA). HA modified with GMA (HA-GMA) was employed as the soluble macromer. Macroscopic hydrogels containing covalently integrated hydrogel particles (HA-c-HGP) were prepared by radical polymerization of HA-GMA in the presence of crosslinkable HGPs. The covalent linkages between the hydrogel particles and the secondary HA matrix resulted in the formation of a diffuse, fibrilar interface around the particles. Compared to the traditional bulk gels synthesized by photocrosslinking of HA-GMA, these hydrogels exhibited a reduced sol fraction and a lower equilibrium swelling ratio. When tested under uniaxial compression, the HA-c-HGP gels were more pliable than the HA-p-HGP gels and fractured at higher strain than the HA-GMA gels. Primary bovine chondrocytes were photoencapsulated in the HA matrices with minimal cell damage. The 3D microenvironment created by HA-GMA and HA HGPs not only maintained the chondrocyte phenotype but also fostered the production of cartilage specific extracellular matrix. To further improve the biological activities of the HA-c-HGP gels, bone morphogenetic protein 2 (BMP-2) was loaded into the immobilized HGPs. BMP-2 was released from the HA-c-HGP gels in a controlled manner with reduced initial burst over prolonged periods of time. The HA-c-HGP gels are promising candidates for use as bioactive matrices for cartilage tissue engineering. PMID:20936090

  1. Performance Measurement Framework for Hierarchical Text Classification.

    ERIC Educational Resources Information Center

    Sun, Aixin; Lim, Ee-Peng; Ng, Wee-Keong

    2003-01-01

    Discusses hierarchical text classification for electronic information retrieval and the measures used to evaluate performance. Proposes new performance measures that consist of category similarity measures and distance-based measures that consider the contributions of misclassified documents, and explains a blocking measure that identifies…

  2. A new automatic baseline correction method based on iterative method

    NASA Astrophysics Data System (ADS)

    Bao, Qingjia; Feng, Jiwen; Chen, Fang; Mao, Wenping; Liu, Zao; Liu, Kewen; Liu, Chaoyang

    2012-05-01

    A new automatic baseline correction method for Nuclear Magnetic Resonance (NMR) spectra is presented. It is based on an improved baseline recognition method and a new iterative baseline modeling method. The presented baseline recognition method takes advantages of three baseline recognition algorithms in order to recognize all signals in spectra. While in the iterative baseline modeling method, besides the well-recognized baseline points in signal-free regions, the 'quasi-baseline points' in the signal-crowded regions are also identified and then utilized to improve robustness by preventing the negative regions. The experimental results on both simulated data and real metabolomics spectra with over-crowded peaks show the efficiency of this automatic method.

  3. The effect of suspended sediment on fertilization success in the urchin Evechinus chloroticus: analysis of experimental data using hierarchical Bayesian methods.

    PubMed

    Miller, S L; Richardson, K; Edwards, P A

    2014-11-15

    Terrestrial sediments are a significant stressor on coastal ecosystems, with both suspended and deposited sediment having adverse effects on aquatic organisms. However, information on the effect of suspended sediments on fertilization success for urchin species is lacking. Using sediment levels similar to those encountered in situ, a controlled experiment was conducted to test whether suspended sediment affects fertilization success in the urchin Evechinus chloroticus. Analyses used generalized linear mixed models (GLMMs) and hierarchical Bayesian (HB) regression. Both approaches showed a significant decrease in fertilization success with increased suspended sediment levels. Uncertainties in estimates were narrower for HB models, suggesting that this approach has advantages over GLMMs for sparse data problems sometimes encountered in laboratory experiments. Given future global change scenarios, this work is important for predicting the effects of stressors such as sedimentation that may ultimately impact marine populations.

  4. Hierarchical structures based on self-assembling beta-hairpin peptides and their application as biomaterials and hybrid materials

    NASA Astrophysics Data System (ADS)

    Altunbas, Aysegul

    an effective vehicle for the localized delivery of curcumin over sustained periods of time in vitro. The curcumin-hydrogel is prepared in-situ where curcumin encapsulation within the hydrogel network is accomplished concurrently with peptide self-assembly. Physical characterization methods and in vitro biological studies were used to demonstrate the effectiveness of curcumin-loaded beta-hairpin hydrogels as injectable agents for localized curcumin delivery. Notably, rheological characterization of the curcumin loaded hydrogel before and after shear flow have indicated solid-like properties even at high curcumin payloads. In vitro experiments with a medulloblastoma cell line confirm that the encapsulation of the curcumin within the hydrogel does not have an adverse effect on its bioactivity. Most importantly, the rate of curcumin release and its consequent therapeutic efficacy can be conveniently modulated by changing the morphological characteristics of the peptide hydrogel network. Lastly, MAX8 hydrogel cytocompatibility and biocompatibility was assessed with the future aim of utilizing this hydrogel as a scaffold in liver regeneration studies in rats. MAX8 hydrogel cytotoxity was evaluated using MC3T3-E1 and MG63 cell lines. Encapsulation, syringe delivery and subsequent viability of MG63 cells in hydrogels was also assessed to study the feasibility of using hydrogel/cell constructs as minimally invasive cell delivery vehicles. Biocompatibility was evaluated by monitoring inflammatory response induced by the MAX8 hydrogel via a subcutaneous mice model. Biocompatibility of MAX8 hydrogels at sites other than the subcutaneous region was also investigated using a cylindrical punch resection model in rat liver. The preliminary biocompatibility studies provide an elemental understanding of MAX8 hydrogel behavior in vivo.

  5. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    PubMed

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  6. Method for indexing and retrieving manufacturing-specific digital imagery based on image content

    DOEpatents

    Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

    2004-06-15

    A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

  7. The Metabolic Status Drives Acclimation of Iron Deficiency Responses in Chlamydomonas reinhardtii as Revealed by Proteomics Based Hierarchical Clustering and Reverse Genetics*

    PubMed Central

    Höhner, Ricarda; Barth, Johannes; Magneschi, Leonardo; Jaeger, Daniel; Niehues, Anna; Bald, Till; Grossman, Arthur; Fufezan, Christian; Hippler, Michael

    2013-01-01

    Iron is a crucial cofactor in numerous redox-active proteins operating in bioenergetic pathways including respiration and photosynthesis. Cellular iron management is essential to sustain sufficient energy production and minimize oxidative stress. To produce energy for cell growth, the green alga Chlamydomonas reinhardtii possesses the metabolic flexibility to use light and/or carbon sources such as acetate. To investigate the interplay between the iron-deficiency response and growth requirements under distinct trophic conditions, we took a quantitative proteomics approach coupled to innovative hierarchical clustering using different “distance-linkage combinations” and random noise injection. Protein co-expression analyses of the combined data sets revealed insights into cellular responses governing acclimation to iron deprivation and regulation associated with photosynthesis dependent growth. Photoautotrophic growth requirements as well as the iron deficiency induced specific metabolic enzymes and stress related proteins, and yet differences in the set of induced enzymes, proteases, and redox-related polypeptides were evident, implying the establishment of distinct response networks under the different conditions. Moreover, our data clearly support the notion that the iron deficiency response includes a hierarchy for iron allocation within organelles in C. reinhardtii. Importantly, deletion of a bifunctional alcohol and acetaldehyde dehydrogenase (ADH1), which is induced under low iron based on the proteomic data, attenuates the remodeling of the photosynthetic machinery in response to iron deficiency, and at the same time stimulates expression of stress-related proteins such as NDA2, LHCSR3, and PGRL1. This finding provides evidence that the coordinated regulation of bioenergetics pathways and iron deficiency response is sensitive to the cellular and chloroplast metabolic and/or redox status, consistent with systems approach data. PMID:23820728

  8. Automatic Construction of Hierarchical Road Networks

    NASA Astrophysics Data System (ADS)

    Yang, Weiping

    2016-06-01

    This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.

  9. Comparison of a silver nanoparticle-based method and the modified spectrophotometric methods for assessing antioxidant capacity of rapeseed varieties.

    PubMed

    Szydłowska-Czerniak, Aleksandra; Tułodziecka, Agnieszka

    2013-12-01

    The antioxidant capacity of 15 rapeseed varieties was determined by the proposed silver nanoparticle-based (AgNP) method and three modified assays: ferric reducing antioxidant power (FRAP), 2,2'-diphenyl-1-picrylhydrazyl (DPPH) and Folin-Ciocalteu reducing capacity (FC). The average antioxidant capacities of the studied rapeseed cultivars ranged between 5261-9462, 3708-7112, 18864-31245 and 5816-9937 μmol sinapic acid (SA)/100g for AgNP, FRAP, DPPH and FC methods, respectively. There are significant, positive correlations between antioxidant capacities of the studied rapeseed cultivars determined by four analytical methods (r=0.5971-0.9149, p<0.05). The comparable precision for the proposed AgNP method (RSD=1.4-4.4%) and the modified FRAP, DPPH and FC methods (RSD=1.0-4.4%, 0.7-2.1% and 0.8-3.6%, respectively), demonstrate the benefit of the AgNP method in the routine analysis of antioxidant capacity of rapeseed cultivars. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for discrimination the quality of the studied rapeseed varieties based on their antioxidant potential determined by different analytical methods. Three main groups were identified by HCA, while the classification and characterisation of rapeseed varieties within each of these groups were obtained from PCA. The chemometric analyses demonstrated that, rapeseed variety S13 had the highest antioxidant capacity, thus this cultivar should be considered as the richest source of natural antioxidants.

  10. METHOD OF JOINING CARBIDES TO BASE METALS

    DOEpatents

    Krikorian, N.H.; Farr, J.D.; Witteman, W.G.

    1962-02-13

    A method is described for joining a refractory metal carbide such as UC or ZrC to a refractory metal base such as Ta or Nb. The method comprises carburizing the surface of the metal base and then sintering the base and carbide at temperatures of about 2000 deg C in a non-oxidizing atmosphere, the base and carbide being held in contact during the sintering step. To reduce the sintering temperature and time, a sintering aid such as iron, nickel, or cobait is added to the carbide, not to exceed 5 wt%. (AEC)

  11. Sugar apple-shaped TiO2 hierarchical spheres for highly efficient dye-sensitized solar cells

    NASA Astrophysics Data System (ADS)

    Lei, Bing-Xin; Zeng, Li-Li; Zhang, Ping; Qiao, He-Kang; Sun, Zhen-Fan

    2014-05-01

    The sugar apple-shaped TiO2 hierarchical spheres are prepared by a facile hydrothermal method using polyethylene glycol 600 as stabilized reagent, (NH4)2TiF6 and urea as starting materials at 180 °C. The characterizations show that the TiO2 hierarchical sphere has well-defined pyramid-shaped crystal facets. The as-prepared TiO2 hierarchical spheres are crystalline of the anatase phase, with a diameter of about 2-4 μm and a surface area of 36.846 m2 g-1. The optical investigation evidences that the sugar apple-shaped TiO2 hierarchical sphere film exhibits a prominent light scattering effect at a wavelength range of 600-800 nm due to the unique hierarchical morphology. Furthermore, the sugar apple-shaped TiO2 hierarchical spheres are deposited as the scattering layer to balance the dye adsorption and light scattering effect in DSSCs and a 7.20% solar energy conversion efficiency is demonstrated, indicating an improvement compared with the P25 cell (6.68%). Based on the optical and electrochemical investigations, the high conversion efficiency is mainly due to the effective suppression of the back reaction of the injected electron with the I3- in the electrolyte and excellent light scattering ability.

  12. Distribution system reliability assessment using hierarchical Markov modeling

    SciTech Connect

    Brown, R.E.; Gupta, S.; Christie, R.D.; Venkata, S.S.; Fletcher, R.

    1996-10-01

    Distribution system reliability assessment is concerned with power availability and power quality at each customer`s service entrance. This paper presents a new method, termed Hierarchical Markov Modeling (HMM), which can perform predictive distribution system reliability assessment. HMM is unique in that it decomposes the reliability model based on system topology, integrated protection systems, and individual protection devices. This structure, which easily accommodates the effects of backup protection, fault isolation, and load restoration, is compared to simpler reliability models. HMM is then used to assess the reliability of an existing utility distribution system and to explore the reliability impact of several design improvement options.

  13. A hierarchical algorithm for molecular similarity (H-FORMS).

    PubMed

    Ramirez-Manzanares, Alonso; Peña, Joaquin; Azpiroz, Jon M; Merino, Gabriel

    2015-07-15

    A new hierarchical method to determine molecular similarity is introduced. The goal of this method is to detect if a pair of molecules has the same structure by estimating a rigid transformation that aligns the molecules and a correspondence function that matches their atoms. The algorithm firstly detect similarity based on the global spatial structure. If this analysis is not sufficient, the algorithm computes novel local structural rotation-invariant descriptors for the atom neighborhood and uses this information to match atoms. Two strategies (deterministic and stochastic) on the matching based alignment computation are tested. As a result, the atom-matching based on local similarity indexes decreases the number of testing trials and significantly reduces the dimensionality of the Hungarian assignation problem. The experiments on well-known datasets show that our proposal outperforms state-of-the-art methods in terms of the required computational time and accuracy.

  14. Novel and efficient RNA secondary structure prediction using hierarchical folding.

    PubMed

    Jabbari, Hosna; Condon, Anne; Zhao, Shelly

    2008-03-01

    Algorithms for prediction of RNA secondary structure-the set of base pairs that form when an RNA molecule folds-are valuable to biologists who aim to understand RNA structure and function. Improving the accuracy and efficiency of prediction methods is an ongoing challenge, particularly for pseudoknotted secondary structures, in which base pairs overlap. This challenge is biologically important, since pseudoknotted structures play essential roles in functions of many RNA molecules, such as splicing and ribosomal frameshifting. State-of-the-art methods, which are based on free energy minimization, have high run-time complexity (typically Theta(n(5)) or worse), and can handle (minimize over) only limited types of pseudoknotted structures. We propose a new approach for prediction of pseudoknotted structures, motivated by the hypothesis that RNA structures fold hierarchically, with pseudoknot-free (non-overlapping) base pairs forming first, and pseudoknots forming later so as to minimize energy relative to the folded pseudoknot-free structure. Our HFold algorithm uses two-phase energy minimization to predict hierarchically formed secondary structures in O(n(3)) time, matching the complexity of the best algorithms for pseudoknot-free secondary structure prediction via energy minimization. Our algorithm can handle a wide range of biological structures, including kissing hairpins and nested kissing hairpins, which have previously required Theta(n(6)) time.

  15. Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

    PubMed

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

    2015-08-01

    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.

  16. Model-Based Method for Sensor Validation

    NASA Technical Reports Server (NTRS)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  17. Phase transition study of confined water molecules inside carbon nanotubes: hierarchical multiscale method from molecular dynamics simulation to ab initio calculation.

    PubMed

    Javadian, Soheila; Taghavi, Fariba; Yari, Faramarz; Hashemianzadeh, Seyed Majid

    2012-09-01

    In this study, the mechanism of the temperature-dependent phase transition of confined water inside a (9,9) single-walled carbon nanotube (SWCNT) was studied using the hierarchical multi-scale modeling techniques of molecular dynamics (MD) and density functional theory (DFT). The MD calculations verify the formation of hexagonal ice nanotubes at the phase transition temperature T(c)=275K by a sharp change in the location of the oxygen atoms inside the SWCNT. Natural bond orbital (NBO) analysis provides evidence of considerable intermolecular charge transfer during the phase transition and verifies that the ice nanotube contains two different forms of hydrogen bonding due to confinement. Nuclear quadrupole resonance (NQR) and nuclear magnetic resonance (NMR) analyses were used to demonstrate the fundamental influence of intermolecular hydrogen bonding interactions on the formation and electronic structure of ice nanotubes. In addition, the NQR analysis revealed that the rearrangement of nano-confined water molecules during the phase transition could be detected directly by the orientation of ¹⁷O atom EFG tensor components related to the molecular frame axes. The effects of nanoscale confinements in ice nanotubes and water clusters were analyzed by experimentally observable NMR and NQR parameters. These findings showed a close relationship between the phase behavior and orientation of the electronic structure in nanoscale structures and demonstrate the usefulness of NBO and NQR parameters for detecting phase transition phenomena in nanoscale confining environments.

  18. Manifold based methods in facial expression recognition

    NASA Astrophysics Data System (ADS)

    Xie, Kun

    2013-07-01

    This paper describes a novel method for facial expression recognition based on non-linear manifold techniques. The graph-based algorithms are designed to treat structure in data, and regularize accordingly. This same goal is shared by several other algorithms, from linear method principal components analysis (PCA) to modern variants such as Laplacian eigenmaps. In this paper we focus on manifold learning for dimensionality reduction and clustering using Laplacian eigenmaps for facial expression recognition. We evaluate the algorithm by using all the pixels and selected features respectively and compare the performance of the proposed non-linear manifold method with the previous linear manifold approach, and the non linear method produces higher recognition rate than the facial expression representation using linear methods.

  19. Integrating data sources to improve hydraulic head predictions : a hierarchical machine learning approach.

    SciTech Connect

    Michael, W. J.; Minsker, B. S.; Tcheng, D.; Valocchi, A. J.; Quinn, J. J.; Environmental Assessment; Univ. of Illinois

    2005-03-26

    This study investigates how machine learning methods can be used to improve hydraulic head predictions by integrating different types of data, including data from numerical models, in a hierarchical approach. A suite of four machine learning methods (decision trees, instance-based weighting, inverse distance weighting, and neural networks) are tested in several hierarchical configurations with different types of data from the 317/319 area at Argonne National Laboratory-East. The best machine learning model had a mean predicted head error 50% smaller than an existing MODFLOW numerical flow model, and a standard deviation of predicted head error 67% lower than the MODFLOW model, computed across all sampled locations used for calibrating the MODFLOW model. These predictions were obtained using decision trees trained with all historical quarterly data; the hourly head measurements were not as useful for prediction, most likely because of their poor spatial coverage. The results show promise for using hierarchical machine learning approaches to improve predictions and to identify the most essential types of data to guide future sampling efforts. Decision trees were also combined with an existing MODFLOW model to test their capabilities for updating numerical models to improve predictions as new data are collected. The combined model had a mean error 50% lower than the MODFLOW model alone. These results demonstrate that hierarchical machine learning approaches can be used to improve predictive performance of existing numerical models in areas with good data coverage. Further research is needed to compare this approach with methods such as Kalman filtering.

  20. Annular subaperture stitching method based on autocollimation

    NASA Astrophysics Data System (ADS)

    Yiwei, Chen; Erlong, Miao; Yongxin, Sui; Huaijiang, Yang

    2014-11-01

    In this paper, we propose an annular subaperture stitching method based on an autocollimation method to relax the requirements on mechanical location accuracy. In this approach, we move a ball instead of the interferometer and the aspheric surface so that testing results for adjacent annular subapertures are registered. Thus, the stitching algorithm can easily stitch the subaperture testing results together when large mechanical location errors exist. To verify this new method, we perform a simulation experiment. The simulation results demonstrate that this method can stitch together the subaperture testing results under large mechanical location errors.

  1. Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models.

    PubMed

    Alexandrescu, Roxana; Bottle, Alex; Jarman, Brian; Aylin, Paul

    2014-05-01

    The use of hierarchical logistic regression for provider profiling has been recommended due to the clustering of patients within hospitals, but has some associated difficulties. We assess changes in hospital outlier status based on standard logistic versus hierarchical logistic modelling of mortality. The study population consisted of all patients admitted to acute, non-specialist hospitals in England between 2007 and 2011 with a primary diagnosis of acute myocardial infarction, acute cerebrovascular disease or fracture of neck of femur or a primary procedure of coronary artery bypass graft or repair of abdominal aortic aneurysm. We compared standardised mortality ratios (SMRs) from non-hierarchical models with SMRs from hierarchical models, without and with shrinkage estimates of the predicted probabilities (Model 1 and Model 2). The SMRs from standard logistic and hierarchical models were highly statistically significantly correlated (r > 0.91, p = 0.01). More outliers were recorded in the standard logistic regression than hierarchical modelling only when using shrinkage estimates (Model 2): 21 hospitals (out of a cumulative number of 565 pairs of hospitals under study) changed from a low outlier and 8 hospitals changed from a high outlier based on the logistic regression to a not-an-outlier based on shrinkage estimates. Both standard logistic and hierarchical modelling have identified nearly the same hospitals as mortality outliers. The choice of methodological approach should, however, also consider whether the modelling aim is judgment or improvement, as shrinkage may be more appropriate for the former than the latter. PMID:24711175

  2. A Method for Capturing and Reconciling Stakeholder Intentions Based on the Formal Concept Analysis

    NASA Astrophysics Data System (ADS)

    Aoyama, Mikio

    Information systems are ubiquitous in our daily life. Thus, information systems need to work appropriately anywhere at any time for everybody. Conventional information systems engineering tends to engineer systems from the viewpoint of systems functionality. However, the diversity of the usage context requires fundamental change compared to our current thinking on information systems; from the functionality the systems provide to the goals the systems should achieve. The intentional approach embraces the goals and related aspects of the information systems. This chapter presents a method for capturing, structuring and reconciling diverse goals of multiple stakeholders. The heart of the method lies in the hierarchical structuring of goals by goal lattice based on the formal concept analysis, a semantic extension of the lattice theory. We illustrate the effectiveness of the presented method through application to the self-checkout systems for large-scale supermarkets.

  3. Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

    NASA Astrophysics Data System (ADS)

    Gan, Meng; Wang, Cong; Zhu, Chang`an

    2016-05-01

    A novel hierarchical diagnosis network (HDN) is proposed by collecting deep belief networks (DBNs) by layer for the hierarchical identification of mechanical system. The deeper layer in HDN presents a more detailed classification of the result generated from the last layer to provide representative features for different tasks. A two-layer HDN is designed for a two-stage diagnosis with the wavelet packet energy feature. The first layer is intended to identify fault types, while the second layer is developed to further recognize fault severity ranking from the result of the first layer. To confirm the effectiveness of HDN, two similar networks constructed by support vector machine and back propagation neuron networks (BPNN) are employed to present a comprehensive comparison. The experimental results show that HDN is highly reliable for precise multi-stage diagnosis and can overcome the overlapping problem caused by noise and other disturbances.

  4. Estimating sources of winter soil respiration in a subalpine forest using a hierarchical Bayesian process-based stable isotope mixing model

    NASA Astrophysics Data System (ADS)

    Tucker, C.; Ogle, K.; Cable, J.

    2011-12-01

    Recent studies show that snow-covered soils in subalpine forest ecosystems may support high levels of biological activity and significant soil respiration. Most winter soil respiration has been attributed to soil microbial activity, but very little work has been conducted to quantify plant root activity during this time period. The lack of such data may reflect common assumptions about over-winter plant dormancy, leading to the expectation that plant roots are inactive during the winter. In this study, we quantify autotrophic (roots and root-associated microbes) and heterotrophic (free-living microbes and soil fauna) respiration, across four (2008-2011) winter seasons in a subalpine forest in Wyoming. We implement a novel hierarchical Bayesian (HB) model that combines a 13C-CO2 stable isotope mixing model with a process-based model of soil heterotrophic and autotrophic temperature responses to facilitate partitioning total respiration between these sources. In particular, the HB approach simultaneously integrates field data on snowpack CO2 concentration and isotope gradients, snowpack and soil physical characteristics (i.e., temperature, moisture, density), root and microbial biomass, soil carbon, and data obtained from laboratory incubations of roots and soils. The process model components include temperature constraints on root and microbial activity, a Michaelis-Menten-type model for microbial respiration in response to substrate limitation, and a diffusion driven model of CO2 transport through the snow. Averaging across years, soil respiration increased from 0.35 μmol CO2 m-2 s-1 in January to 0.6 μmol CO2 m-2 s-1 in May while snow depth increased and soil temperature remained stable over the same period. The increase in respiration appeared to be driven by a two- to four-fold increase in microbial biomass carbon as winter progressed. Carbon limitation of microbial activity during the winter appears to be negligible, and we suggest that high carbon use

  5. How hierarchical is language use?

    PubMed Central

    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

  6. Hierarchical abstract semantic model for image classification

    NASA Astrophysics Data System (ADS)

    Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

    2015-09-01

    Semantic gap limits the performance of bag-of-visual-words. To deal with this problem, a hierarchical abstract semantics method that builds abstract semantic layers, generates semantic visual vocabularies, measures semantic gap, and constructs classifiers using the Adaboost strategy is proposed. First, abstract semantic layers are proposed to narrow the semantic gap between visual features and their interpretation. Then semantic visual words are extracted as features to train semantic classifiers. One popular form of measurement is used to quantify the semantic gap. The Adaboost training strategy is used to combine weak classifiers into strong ones to further improve performance. For a testing image, the category is estimated layer-by-layer. Corresponding abstract hierarchical structures for popular datasets, including Caltech-101 and MSRC, are proposed for evaluation. The experimental results show that the proposed method is capable of narrowing semantic gaps effectively and performs better than other categorization methods.

  7. A maskless synthesis of TiO2-nanofiber-based hierarchical structures for solid-state dye-sensitized solar cells with improved performance

    PubMed Central

    2014-01-01

    TiO2 hierarchical nanostructures with secondary growth have been successfully synthesized on electrospun nanofibers via surfactant-free hydrothermal route. The effect of hydrothermal reaction time on the secondary nanostructures has been studied. The synthesized nanostructures comprise electrospun nanofibers which are polycrystalline with anatase phase and have single crystalline, rutile TiO2 nanorod-like structures growing on them. These secondary nanostructures have a preferential growth direction [110]. UV–vis spectroscopy measurements point to better dye loading capability and incident photon to current conversion efficiency spectra show enhanced light harvesting of the synthesized hierarchical structures. Concomitantly, the dye molecules act as spacers between the conduction band electrons of TiO2 and holes in the hole transporting medium, i.e., spiro-OMeTAD and thus enhance open circuit voltage. The charge transport and recombination effects are characterized by electrochemical impedance spectroscopy measurements. As a result of improved light harvesting, dye loading, and reduced recombination losses, the hierarchical nanofibers yield 2.14% electrochemical conversion efficiency which is 50% higher than the efficiency obtained by plain nanofibers. PMID:24410851

  8. Synthesis of hierarchically porous structured CaCO3 and TiO2 replicas by sol-gel method using lotus root as template.

    PubMed

    Chen, Jui-Yi; Yang, Ching-Yu; Chen, Po-Yu

    2016-10-01

    Intensive attention has been put in mimicking the morphologies in nature owing to their uniqueness, complexity, and diversity. One of the effective approaches to mimic bio-morphologies is through biotemplating - the technique of using biological structures as template to reproduce intricate structure in other forms of materials. This work presents a facile sol-gel technique that can be widely used to convert various carbon-rich bio-structures into different materials. Lotus root, a biomorphic template with high porosity at varying length scales, was selected as the example to demonstrate this approach. The experiment was conducted by infiltrating precursors - titanium (IV) n-butoxide (TnBT) and acetic acid calcium solution - into the lotus root template under vacuum system, followed by calcination. After the treatment, the replicas were calcite CaCO3 and anatase TiO2. In both CaCO3 and TiO2 replicas, the intact structure of the template was preserved. In spite of the overall similarity of the CaCO3 and TiO2 lotus root replicas, some respective differences were found. TiO2 replica was covered with nanowire bundles of 100-200nm in diameter, formed by preferable crystallization of particles, while CaCO3 replica presented the gradient-distributed pores of 10-100μm, which greatly resembled the microstructure of lotus root template. In the BET result, TiO2 replica was mesoporous structure with pores centralizing in 3-4nm. On the other hand, CaCO3 replica had pores in a wider distribution ranging from micro to macro scale. In addition, the surface area was greatly enhanced in both cases. The synthesized materials with hierarchical biomorphic structures may have great potential for purification applications due to their large specific surface area, photocatalytic property, and high adsorption rate.

  9. A Property Restriction Based Knowledge Merging Method

    NASA Astrophysics Data System (ADS)

    Che, Haiyan; Chen, Wei; Feng, Tie; Zhang, Jiachen

    Merging new instance knowledge extracted from the Web according to certain domain ontology into the knowledge base (KB for short) is essential for the knowledge management and should be processed carefully, since this may introduce redundant or contradictory knowledge, and the quality of the knowledge in the KB, which is very important for a knowledge-based system to provide users high quality services, will suffer from such "bad" knowledge. Advocates a property restriction based knowledge merging method, it can identify the equivalent instances, redundant or contradictory knowledge according to the property restrictions defined in the domain ontology and can consolidate the knowledge about equivalent instances and discard the redundancy and conflict to keep the KB compact and consistent. This knowledge merging method has been used in a semantic-based search engine project: CRAB and the effect is satisfactory.

  10. Dynamic hierarchical algorithm for accelerated microfossil identification

    NASA Astrophysics Data System (ADS)

    Wong, Cindy M.; Joseph, Dileepan

    2015-02-01

    Marine microfossils provide a useful record of the Earth's resources and prehistory via biostratigraphy. To study Hydrocarbon reservoirs and prehistoric climate, geoscientists visually identify the species of microfossils found in core samples. Because microfossil identification is labour intensive, automation has been investigated since the 1980s. With the initial rule-based systems, users still had to examine each specimen under a microscope. While artificial neural network systems showed more promise for reducing expert labour, they also did not displace manual identification for a variety of reasons, which we aim to overcome. In our human-based computation approach, the most difficult step, namely taxon identification is outsourced via a frontend website to human volunteers. A backend algorithm, called dynamic hierarchical identification, uses unsupervised, supervised, and dynamic learning to accelerate microfossil identification. Unsupervised learning clusters specimens so that volunteers need not identify every specimen during supervised learning. Dynamic learning means interim computation outputs prioritize subsequent human inputs. Using a dataset of microfossils identified by an expert, we evaluated correct and incorrect genus and species rates versus simulated time, where each specimen identification defines a moment. The proposed algorithm accelerated microfossil identification effectively, especially compared to benchmark results obtained using a k-nearest neighbour method.

  11. Recommendation advertising method based on behavior retargeting

    NASA Astrophysics Data System (ADS)

    Zhao, Yao; YIN, Xin-Chun; CHEN, Zhi-Min

    2011-10-01

    Online advertising has become an important business in e-commerce. Ad recommended algorithms are the most critical part in recommendation systems. We propose a recommendation advertising method based on behavior retargeting which can avoid leakage click of advertising due to objective reasons and can observe the changes of the user's interest in time. Experiments show that our new method can have a significant effect and can be further to apply to online system.

  12. Highly efficient decomposition of organic dye by aqueous-solid phase transfer and in situ photocatalysis using hierarchical copper phthalocyanine hollow spheres.

    PubMed

    Zhang, Mingyi; Shao, Changlu; Guo, Zengcai; Zhang, Zhenyi; Mu, Jingbo; Zhang, Peng; Cao, Tieping; Liu, Yichun

    2011-07-01

    The hierarchical tetranitro copper phthalocyanine (TNCuPc) hollow spheres were fabricated by a simple solvothermal method. The formation mechanism was proposed based on the evolution of morphology as a function of solvothermal time, which involved the initial formation of nanoparticles followed by their self-aggregation to microspheres and transformation into hierarchical hollow spheres by Ostwald ripening. Furthermore, the hierarchical TNCuPc hollow spheres exhibited high adsorption capacity and excellent simultaneously visible-light-driven photocatalytic performance for Rhodamine B (RB) under visible light. A possible mechanism for the "aqueous-solid phase transfer and in situ photocatalysis" was suggested. Repetitive tests showed that the hierarchical TNCuPc hollow spheres maintained high catalytic activity over several cycles, and it had a better regeneration capability under mild conditions.

  13. Facile fabrication of hierarchical ZnO microstructures assisted with PAMPSA and enhancement of green emission

    NASA Astrophysics Data System (ADS)

    Huang, Qiang; Cun, Tangxiang; Zuo, Wenbin; Liu, Jianping

    2015-03-01

    We report the fabrication of hierarchically microstructured flower-like ZnO by a facile and single-step procedure involving poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PAMPSA) assisted aqueous chemical method. The shapes and sizes can be controlled just by varying the concentrations of the water-soluble polymer. When a suitable PAMPAS concentration was utilized, uniform well-defined and mono-dispersed chrysanthemum-like ZnO microstructures based on nanorod building blocks were obtained. The formation mechanism of the hierarchical structure was presented. The structured studies using XRD, HRTEM and SAED reveal these ZnO nanorods are composed of a single phase nature with wurtzite structure and grow along with the c-axis. FTIR spectrum indicated the incorporation of a trace of PAMPSA into ZnO crystals. HRTEM, Raman and XPS analyses showed that the hierarchical ZnO microstructures contain high concentration of oxygen vacancies which enable them exhibiting a significant intense deep-level emission centered at green luminescence in its photoluminescence spectra. They also show enhanced photocatalytic efficiency in degradation of methylene blue. It is hoped that the present work may provide a simple method to fabricate ZnO hierarchical microstructures and a positive relationship among polar plane, oxygen vacancy and green emission.

  14. Hierarchical organisation in perception of orientation.

    PubMed

    Spinelli, D; Antonucci, G; Daini, R; Martelli, M L; Zoccolotti, P

    1999-01-01

    According to Rock [1990, in The Legacy of Solomon Asch (Hillsdale, NJ: Lawrence Erlbaum Associates)], hierarchical organisation of perception describes cases in which the orientation of an object is affected by the immediately surrounding elements in the visual field. Various experiments were performed to study the hierarchical organisation of orientation perception. In most of them the rod-and-frame-illusion (RFI: change of the apparent vertical measured on a central rod surrounded by a tilted frame) was measured in the presence/absence of a second inner frame. The first three experiments showed that, when the inner frame is vertical, the direction and size of the illusion are consistent with expectancies based on the hierarchical organisation hypothesis. An analysis of published and unpublished data collected on a large number of subjects showed that orientational hierarchical effects are independent from the absolute size of the RFI. In experiments 4 to 7 we examined the perceptual conditions of the inner stimulus (enclosure, orientation, and presence of luminance borders) critical for obtaining a hierarchical organisation effect. Although an inner vertical square was effective in reducing the illusion (experiment 3), an inner circle enclosing the rod was ineffective (experiment 4). This indicates that definite orientation is necessary to modulate the illusion. However, orientational information provided by a vertical or horizontal rectangle presented near the rod, but not enclosing it, did not modulate the RFI (experiment 5). This suggests that the presence of a figure with oriented contours enclosing the rod is critical. In experiments 6 and 7 we studied whether the presence of luminance borders is important or whether the inner upright square might be effective also if made of subjective contours. When the subjective contour figure was salient and the observers perceived it clearly, its effectiveness in modulating the RFI was comparable to that observed with

  15. Generation of Hierarchically Ordered Structures on a Polymer Film by Electrohydrodynamic Structure Formation.

    PubMed

    Tian, Hongmiao; Shao, Jinyou; Hu, Hong; Wang, Li; Ding, Yucheng

    2016-06-29

    The extensive applications of hierarchical structures in optoelectronics, micro/nanofluidics, energy conservation, etc., have led to the development of a variety of approaches for their fabrication, which can be categorized as bottom-up or top-down strategies. Current bottom-up and top-down strategies bear a complementary relationship to each other due to their processing characteristics, i.e., the advantages of one method correspond to the disadvantages of the other, and vice versa. Here we propose a novel method based on electrohydrodynamic structure formation, aimed at combining the main advantages of the two strategies. The method allows the fabrication of a hierarchically ordered structure with well-defined geometry and high mechanical durability on a polymer film, through a simple and low-cost process also suitable for mass-production. In this approach, upon application of an electric field between a template and a substrate sandwiching an air gap and a polymer film, the polymer is pulled toward the template and further flows into the template cavities, resulting in a hierarchical structure with primary and secondary patterns determined by electrohydrodynamic instability and by the template features, respectively. In this work, the fabrication of a hierarchical structure by electrohydrodynamic structure formation is studied using numerical simulations and experimental tests. The proposed method is then employed for the one-step fabrication of a hierarchical structure exhibiting a gradual transition in the periodicity of the primary structure using a slant template and a flat polymer film, which presents an excellent performance on controllable wettability.

  16. Generation of Hierarchically Ordered Structures on a Polymer Film by Electrohydrodynamic Structure Formation.

    PubMed

    Tian, Hongmiao; Shao, Jinyou; Hu, Hong; Wang, Li; Ding, Yucheng

    2016-06-29

    The extensive applications of hierarchical structures in optoelectronics, micro/nanofluidics, energy conservation, etc., have led to the development of a variety of approaches for their fabrication, which can be categorized as bottom-up or top-down strategies. Current bottom-up and top-down strategies bear a complementary relationship to each other due to their processing characteristics, i.e., the advantages of one method correspond to the disadvantages of the other, and vice versa. Here we propose a novel method based on electrohydrodynamic structure formation, aimed at combining the main advantages of the two strategies. The method allows the fabrication of a hierarchically ordered structure with well-defined geometry and high mechanical durability on a polymer film, through a simple and low-cost process also suitable for mass-production. In this approach, upon application of an electric field between a template and a substrate sandwiching an air gap and a polymer film, the polymer is pulled toward the template and further flows into the template cavities, resulting in a hierarchical structure with primary and secondary patterns determined by electrohydrodynamic instability and by the template features, respectively. In this work, the fabrication of a hierarchical structure by electrohydrodynamic structure formation is studied using numerical simulations and experimental tests. The proposed method is then employed for the one-step fabrication of a hierarchical structure exhibiting a gradual transition in the periodicity of the primary structure using a slant template and a flat polymer film, which presents an excellent performance on controllable wettability. PMID:27268135

  17. HierarchicalTopics: visually exploring large text collections using topic hierarchies.

    PubMed

    Dou, Wenwen; Yu, Li; Wang, Xiaoyu; Ma, Zhiqiang; Ribarsky, William

    2013-12-01

    Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be generated in order to capture the meaningful latent themes and nuances in the corpora. However, it is difficult for most of current topic-based visualizations to represent large number of topics without being cluttered or illegible. To facilitate the representation and navigation of a large number of topics, we propose a visual analytics system--HierarchicalTopic (HT). HT integrates a computational algorithm, Topic Rose Tree, with an interactive visual interface. The Topic Rose Tree constructs a topic hierarchy based on a list of topics. The interactive visual interface is designed to present the topic content as well as temporal evolution of topics in a hierarchical fashion. User interactions are provided for users to make changes to the topic hierarchy based on their mental model of the topic space. To qualitatively evaluate HT, we present a case study that showcases how HierarchicalTopics aid expert users in making sense of a large number of topics and discovering interesting patterns of topic groups. We have also conducted a user study to quantitatively evaluate the effect of hierarchical topic structure. The study results reveal that the HT leads to faster identification of large number of relevant topics. We have also solicited user feedback during the experiments and incorporated some suggestions into the current version of HierarchicalTopics.

  18. Bayesian individualization via sampling-based methods.

    PubMed

    Wakefield, J

    1996-02-01

    We consider the situation where we wish to adjust the dosage regimen of a patient based on (in general) sparse concentration measurements taken on-line. A Bayesian decision theory approach is taken which requires the specification of an appropriate prior distribution and loss function. A simple method for obtaining samples from the posterior distribution of the pharmacokinetic parameters of the patient is described. In general, these samples are used to obtain a Monte Carlo estimate of the expected loss which is then minimized with respect to the dosage regimen. Some special cases which yield analytic solutions are described. When the prior distribution is based on a population analysis then a method of accounting for the uncertainty in the population parameters is described. Two simulation studies showing how the methods work in practice are presented. PMID:8827585

  19. Quantification of the Molecular Topology for Hierarchical Macromolecules

    NASA Astrophysics Data System (ADS)

    Beaucage, Gregory

    2009-03-01

    Hierarchical structures are often produced from ramified macromolecules such as comb, star, hyperbranched and dendritic polymers. We have recently derived a method for the description of complex molecular and nanostructural topologies based on a statistical analysis [1,2]. The method has been applied to a wide range of hierarchical materials from long chain branched polyolefins, hyperbranched polymers [3], star polymers, H-branched polymers to cyclics, biopolymers [4], and branched nanostructured aggregates. This method, when applied to neutron scattering data, yields the mole fraction of a structure involved in branching, the number of branch sites, the average branch length, and the number if inner chain segments. Further, quantitative measures of the convolution or tortuosity of the structure and the connectivity of the branching network can be made, opening a new window for our understanding of complex molecular topologies. This understanding has recently been applied to biological chain molecules to understand protein and RNA folding [4] for example as well as to aggregated, nanostructured, carbon soot. [0pt] [1] Beaucage, G, Phys. Rev. E 2004, 70, 031401. [2] Kulkarni, AS & Beaucage, G, J. Polym. Sci. Part B: Polym. Phys. 2006, 44, 1395. [3] Kulkarni, AS & Beaucage, G, Macromol. Rapid Comm. 2007, 28, 1312.?4) Beaucage, G, Biophysical J. 2008, 95, 503.

  20. Hierarchical extraction of landslides from multiresolution remotely sensed optical images

    NASA Astrophysics Data System (ADS)

    Kurtz, Camille; Stumpf, André; Malet, Jean-Philippe; Gançarski, Pierre; Puissant, Anne; Passat, Nicolas

    2014-01-01

    The automated detection and mapping of landslides from Very High Resolution (VHR) images present several challenges related to the heterogeneity of landslide sizes, shapes and soil surface characteristics. However, a common geomorphological characteristic of landslides is to be organized with a series of embedded and scaled features. These properties motivated the use of a multiresolution image analysis approach for their detection. In this work, we propose a hybrid segmentation/classification region-based method, devoted to this specific issue. The method, which uses images of the same area at various spatial resolutions (Medium to Very High Resolution), relies on a recently introduced top-down hierarchical framework. In the specific context of landslide analysis, two main novelties are introduced to enrich this framework. The first novelty consists of using non-spectral information, obtained from Digital Terrain Model (DTM), as a priori knowledge for the guidance of the segmentation/classification process. The second novelty consists of using a new domain adaptation strategy, that allows to reduce the expert's interaction when handling large image datasets. Experiments performed on satellite images acquired over terrains affected by landslides demonstrate the efficiency of the proposed method with different hierarchical levels of detail addressing various operational needs.