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Sample records for hierarchical method based

  1. Nanowire-based polypyrrole hierarchical structures synthesized by a two-step electrochemical method.

    PubMed

    Ge, Dongtao; Huang, Sanqing; Qi, Rucai; Mu, Jing; Shen, Yuqing; Shi, Wei

    2009-08-03

    A simple two-step electrochemical method is proposed for the synthesis of nanowire-based polypyrrole hierarchical structures. In the first step, microstructured polypyrrole films are prepared by electropolymerization. Then, polypyrrole nanowires are electrodeposited on the surface of the as-synthesized microstructured polypyrrole films. As a result, hierarchical structures of polypyrrole nanowires on polypyrrole microstructures are obtained. The surface wettabilities of the resulting nanowire-based polypyrrole hierarchical structures are examined. It is expected that this two-step method can be developed into a versatile route to produce nanowire-based polypyrrole hierarchical structures with different morphologies and surface properties.

  2. Hierarchical flux-based thermal-structural finite element analysis method

    NASA Technical Reports Server (NTRS)

    Polesky, Sandra P.

    1992-01-01

    A hierarchical flux-based finite element method is developed for both a one and two dimensional thermal structural analyses. Derivation of the finite element equations is presented. The resulting finite element matrices associated with the flux based formulation are evaluated in a closed form. The hierarchical finite elements include additional degrees of freedom in the approximation of the element variable distributions by the use of nodeless variables. The nodeless variables offer increased solution accuracy without the need for defining actual nodes and rediscretizing the finite element model. Thermal and structural responses are obtained from a conventional linear finite element method and exact solutions. Results show that the hierarchical flux-based method can provide improved thermal and structural solution accuracy with fewer elements when compared to results for the conventional linear element method.

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

    NASA Astrophysics Data System (ADS)

    Huang, Weizhang; Kamenski, Lennard; Lang, Jens

    2010-03-01

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

  4. 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

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

    PubMed

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

    2016-09-09

    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.

  6. Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

    PubMed

    Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

    2014-01-01

    This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

  7. Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

    PubMed Central

    Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

    2014-01-01

    This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

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

    PubMed

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

    2017-07-19

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

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

    PubMed Central

    Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

    2017-01-01

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

  10. Parallel hierarchical method in networks

    NASA Astrophysics Data System (ADS)

    Malinochka, Olha; Tymchenko, Leonid

    2007-09-01

    This method of parallel-hierarchical Q-transformation offers new approach to the creation of computing medium - of parallel -hierarchical (PH) networks, being investigated in the form of model of neurolike scheme of data processing [1-5]. The approach has a number of advantages as compared with other methods of formation of neurolike media (for example, already known methods of formation of artificial neural networks). The main advantage of the approach is the usage of multilevel parallel interaction dynamics of information signals at different hierarchy levels of computer networks, that enables to use such known natural features of computations organization as: topographic nature of mapping, simultaneity (parallelism) of signals operation, inlaid cortex, structure, rough hierarchy of the cortex, spatially correlated in time mechanism of perception and training [5].

  11. 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

  12. Hierarchical ensemble methods for protein function prediction.

    PubMed

    Valentini, Giorgio

    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.

  13. Experiments with hierarchical concept-based search.

    PubMed

    Moskovitch, Robert; Sa'adon, Roee; Behiri, Eytan; Martins, Susana; Weiss, Aviram; Shahar, Yuval

    2007-01-01

    Many digital libraries use hierarchical indexing schema, such as MeSH to enable concept based search in the retrieval phase. However, improving or outperforming the traditional full text search isn't trivial. We present an extensive set of experiments using a hierarchical concept based search retrieval method, applied in addition to several baselines, within the Vaidruya search and retrieval framework. Concept Based Search applied in addition to a low baseline is outperforming significantly, especially when queried on concepts in the third level and using disjunction within the hierarchical trees.

  14. 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.

  15. 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.

  16. 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.

  17. Development of Generation-Transmission Expansion Planning Method Based on a Hierarchical Model

    NASA Astrophysics Data System (ADS)

    Fukutome, Suguru; Azuma, Hitoshi; Honjou, Nobuyuki; Chen, Luonan

    Generation expansion planning and transmission planning are strongly related. It is increasingly demanded in power industry to optimize such a generation-transmission planning so that whole power system can be operated in a more economic and reliable manner. So far most of existing methods are to either solve generation expansion planning or transmission planning due to the computational burdens, in particular for a large-scale system, and also there are no commercial packages available to solve such a problem directly. In this paper, we propose a bi-level model that divides the original problem into a master problem and two sub-problems. Optimization for such bi-level model is facilitated by using the long-term nodal marginal costs, which is acted as economic signals for the master problem and the sub-problems. To demonstrate the proposed method, we adopt several test systems, which verify the effectiveness of the proposed algorithm.

  18. Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

    PubMed

    Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

    2016-01-01

    With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

  19. Hierarchical video summarization based on context clustering

    NASA Astrophysics Data System (ADS)

    Tseng, Belle L.; Smith, John R.

    2003-11-01

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

  20. A novel load balancing method for hierarchical federation simulation system

    NASA Astrophysics Data System (ADS)

    Bin, Xiao; Xiao, Tian-yuan

    2013-07-01

    In contrast with single HLA federation framework, hierarchical federation framework can improve the performance of large-scale simulation system in a certain degree by distributing load on several RTI. However, in hierarchical federation framework, RTI is still the center of message exchange of federation, and it is still the bottleneck of performance of federation, the data explosion in a large-scale HLA federation may cause overload on RTI, It may suffer HLA federation performance reduction or even fatal error. Towards this problem, this paper proposes a load balancing method for hierarchical federation simulation system based on queuing theory, which is comprised of three main module: queue length predicting, load controlling policy, and controller. The method promotes the usage of resources of federate nodes, and improves the performance of HLA simulation system with balancing load on RTIG and federates. Finally, the experiment results are presented to demonstrate the efficient control of the method.

  1. Hierarchical super-resolution-based inpainting.

    PubMed

    Le Meur, Olivier; Ebdelli, Mounira; Guillemot, Christine

    2013-10-01

    This paper introduces a novel framework for examplar-based inpainting. It consists in performing first the inpainting on a coarse version of the input image. A hierarchical super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of computational complexity and visual quality. However, to be less sensitive to the parameter setting of the inpainting method, the low-resolution input picture is inpainted several times with different configurations. Results are efficiently combined with a loopy belief propagation and details are recovered by a single-image super-resolution algorithm. Experimental results in a context of image editing and texture synthesis demonstrate the effectiveness of the proposed method. Results are compared to five state-of-the-art inpainting methods.

  2. 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

  3. 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.

  4. 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.

  5. Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images

    NASA Astrophysics Data System (ADS)

    Timchenko, Leonid I.; Kokryatskaya, Nataliya I.; Shpakovych, Viktoriya V.

    2013-12-01

    Principles necessary to develop a method and computational facilities for the parallel hierarchical transformation based on high-performance GPUs are discussed in the paper. Mathematic models of the parallel hierarchical (PH) network training for the transformation and a PH network training method for recognition of dynamic images are developed.

  6. A Coalescence-Guided Hierarchical Bayesian Method for Haplotype Inference

    PubMed Central

    Zhang, Yu; Niu, Tianhua; Liu, Jun S.

    2006-01-01

    Haplotype inference from phase-ambiguous multilocus genotype data is an important task for both disease-gene mapping and studies of human evolution. We report a novel haplotype-inference method based on a coalescence-guided hierarchical Bayes model. In this model, a hierarchical structure is imposed on the prior haplotype frequency distributions to capture the similarities among modern-day haplotypes attributable to their common ancestry. As a consequence, the model both allows distinct haplotypes to have different a priori probabilities according to the inferred hierarchical ancestral structure and results in a proper joint posterior distribution for all the parameters of interest. A Markov chain–Monte Carlo scheme is designed to draw from this posterior distribution. By using coalescence-based simulation and empirically generated data sets (Whitehead Institute’s inflammatory bowel disease data sets and HapMap data sets), we demonstrate the merits of the new method in comparison with HAPLOTYPER and PHASE, with or without the presence of recombination hotspots and missing genotypes. PMID:16826521

  7. Wavelet-based hierarchical surface approximation from height fields

    Treesearch

    Sang-Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

    2004-01-01

    This paper presents a novel hierarchical approach to triangular mesh generation from height fields. A wavelet-based multiresolution analysis technique is used to estimate local shape information at different levels of resolution. Using predefined templates at the coarsest level, the method constructs an initial triangulation in which underlying object shapes are well...

  8. Hierarchical model-based interferometric synthetic aperture radar image registration

    NASA Astrophysics Data System (ADS)

    Wang, Yang; Huang, Haifeng; Dong, Zhen; Wu, Manqing

    2014-01-01

    With the rapid development of spaceborne interferometric synthetic aperture radar technology, classical image registration methods are incompetent for high-efficiency and high-accuracy masses of real data processing. Based on this fact, we propose a new method. This method consists of two steps: coarse registration that is realized by cross-correlation algorithm and fine registration that is realized by hierarchical model-based algorithm. Hierarchical model-based algorithm is a high-efficiency optimization algorithm. The key features of this algorithm are a global model that constrains the overall structure of the motion estimated, a local model that is used in the estimation process, and a coarse-to-fine refinement strategy. Experimental results from different kinds of simulated and real data have confirmed that the proposed method is very fast and has high accuracy. Comparing with a conventional cross-correlation method, the proposed method provides markedly improved performance.

  9. Fingerprint analysis of Hibiscus mutabilis L. leaves based on ultra performance liquid chromatography with photodiode array detector combined with similarity analysis and hierarchical clustering analysis methods

    PubMed Central

    Liang, Xianrui; Ma, Meiling; Su, Weike

    2013-01-01

    Background: A method for chemical fingerprint analysis of Hibiscus mutabilis L. leaves was developed based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD) combined with similarity analysis (SA) and hierarchical clustering analysis (HCA). Materials and Methods: 10 batches of Hibiscus mutabilis L. leaves samples were collected from different regions of China. UPLC-PAD was employed to collect chemical fingerprints of Hibiscus mutabilis L. leaves. Results: The relative standard deviations (RSDs) of the relative retention times (RRT) and relative peak areas (RPA) of 10 characteristic peaks (one of them was identified as rutin) in precision, repeatability and stability test were less than 3%, and the method of fingerprint analysis was validated to be suitable for the Hibiscus mutabilis L. leaves. Conclusions: The chromatographic fingerprints showed abundant diversity of chemical constituents qualitatively in the 10 batches of Hibiscus mutabilis L. leaves samples from different locations by similarity analysis on basis of calculating the correlation coefficients between each two fingerprints. Moreover, the HCA method clustered the samples into four classes, and the HCA dendrogram showed the close or distant relations among the 10 samples, which was consistent to the SA result to some extent. PMID:23930008

  10. 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.

  11. 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...

  12. 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...

  13. Hierarchical graphs for rule-based modeling of biochemical systems

    PubMed Central

    2011-01-01

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

  14. 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.

  15. 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.

  16. A Comparision of Heuristic Methods Used in Hierarchical Production Planning.

    DTIC Science & Technology

    1979-03-01

    1965). ~~~. Golovin , J. J.; “Hierarchical Integration of Planning and Control”, M.I.T., Operations Research Center, Technical Report No. 116...Nostrand Reinhold , 1978. 9. flax, A. C. and J. J. Golovin ; “Computer Based Operations Management System (COMS)” , Studieä in Operations Management (A. C...flax , ed.), North Holland—American Elsevier, 1978. 10. flax, A. C. and J. J. Golovin ; “Hierarchical Production Planning Systems”, M.I.T

  17. 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

  18. 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.

  19. 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.

  20. Statistical benchmarks for health care provider performance assessment: a comparison of standard approaches to a hierarchical Bayesian histogram-based method.

    PubMed

    Paddock, Susan M

    2014-06-01

    Examine how widely used statistical benchmarks of health care provider performance compare with histogram-based statistical benchmarks obtained via hierarchical Bayesian modeling. Publicly available data from 3,240 hospitals during April 2009-March 2010 on two process-of-care measures reported on the Medicare Hospital Compare website. Secondary data analyses of two process-of-care measures comparing statistical benchmark estimates and threshold exceedance determinations under various combinations of hospital performance measure estimates and benchmarking approaches. Statistical benchmarking approaches for determining top 10 percent performance varied with respect to which hospitals exceeded the performance benchmark; such differences were not found at the 50 percent threshold. Benchmarks derived from the histogram of provider performance under hierarchical Bayesian modeling provide a compromise between benchmarks based on direct (raw) estimates, which are overdispersed relative to the true distribution of provider performance and prone to high variance for small providers, and posterior mean provider performance, for which over-shrinkage and under-dispersion relative to the true provider performance distribution is a concern. Given the rewards and penalties associated with characterizing top performance, the ability of statistical benchmarks to summarize key features of the provider performance distribution should be examined. © Published 2014. This article is a U.S. Government work and is in the public domain in the U.S.A.

  1. Statistical Benchmarks for Health Care Provider Performance Assessment: A Comparison of Standard Approaches to a Hierarchical Bayesian Histogram-Based Method

    PubMed Central

    Paddock, Susan M

    2014-01-01

    Objective Examine how widely used statistical benchmarks of health care provider performance compare with histogram-based statistical benchmarks obtained via hierarchical Bayesian modeling. Data Sources Publicly available data from 3,240 hospitals during April 2009–March 2010 on two process-of-care measures reported on the Medicare Hospital Compare website. Study Design Secondary data analyses of two process-of-care measures comparing statistical benchmark estimates and threshold exceedance determinations under various combinations of hospital performance measure estimates and benchmarking approaches. Principal Findings Statistical benchmarking approaches for determining top 10 percent performance varied with respect to which hospitals exceeded the performance benchmark; such differences were not found at the 50 percent threshold. Benchmarks derived from the histogram of provider performance under hierarchical Bayesian modeling provide a compromise between benchmarks based on direct (raw) estimates, which are overdispersed relative to the true distribution of provider performance and prone to high variance for small providers, and posterior mean provider performance, for which over-shrinkage and under-dispersion relative to the true provider performance distribution is a concern. Conclusions Given the rewards and penalties associated with characterizing top performance, the ability of statistical benchmarks to summarize key features of the provider performance distribution should be examined. PMID:24461071

  2. Cognitive-graphic method for constructing of hierarchical forms of basic functions of biquadratic finite element

    NASA Astrophysics Data System (ADS)

    Astionenko, I. O.; Litvinenko, O. I.; Osipova, N. V.; Tuluchenko, G. Ya.; Khomchenko, A. N.

    2016-10-01

    Recently the interpolation bases of the hierarchical type have been used for the problem solving of the approximation of multiple arguments functions (such as in the finite-element method). In this work the cognitive graphical method of constructing of the hierarchical form bases on the serendipity finite elements is suggested, which allowed to get the alternative bases on a biquadratic finite element from the serendipity family without internal knots' inclusion. The cognitive-graphic method allowed to improve the known interpolation procedure of Taylor and to get the modified elements with irregular arrangement of knots. The proposed procedures are universal and are spread in the area of finite-elements.

  3. A hierarchical network modeling method for railway tunnels safety assessment

    NASA Astrophysics Data System (ADS)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Liu, Xumin

    2017-02-01

    Using network theory to model risk-related knowledge on accidents is regarded as potential very helpful in risk management. A large amount of defects detection data for railway tunnels is collected in autumn every year in China. It is extremely important to discover the regularities knowledge in database. In this paper, based on network theories and by using data mining techniques, a new method is proposed for mining risk-related regularities to support risk management in railway tunnel projects. A hierarchical network (HN) model which takes into account the tunnel structures, tunnel defects, potential failures and accidents is established. An improved Apriori algorithm is designed to rapidly and effectively mine correlations between tunnel structures and tunnel defects. Then an algorithm is presented in order to mine the risk-related regularities table (RRT) from the frequent patterns. At last, a safety assessment method is proposed by consideration of actual defects and possible risks of defects gained from the RRT. This method cannot only generate the quantitative risk results but also reveal the key defects and critical risks of defects. This paper is further development on accident causation network modeling methods which can provide guidance for specific maintenance measure.

  4. Hierarchical coefficient of a multifractal based network

    NASA Astrophysics Data System (ADS)

    Moreira, Darlan A.; Lucena, Liacir dos Santos; Corso, Gilberto

    2014-02-01

    The hierarchical property for a general class of networks stands for a power-law relation between clustering coefficient, CC and connectivity k: CC∝kβ. This relation is empirically verified in several biologic and social networks, as well as in random and deterministic network models, in special for hierarchical networks. In this work we show that the hierarchical property is also present in a Lucena network. To create a Lucena network we use the dual of a multifractal lattice ML, the vertices are the sites of the ML and links are established between neighbouring lattices, therefore this network is space filling and planar. Besides a Lucena network shows a scale-free distribution of connectivity. We deduce a relation for the maximal local clustering coefficient CCimax of a vertex i in a planar graph. This condition expresses that the number of links among neighbour, N△, of a vertex i is equal to its connectivity ki, that means: N△=ki. The Lucena network fulfils the condition N△≃ki independent of ki and the anisotropy of ML. In addition, CCmax implies the threshold β=1 for the hierarchical property for any scale-free planar network.

  5. Gene function prediction based on the Gene Ontology hierarchical structure.

    PubMed

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  6. Groupwise Registration Based on Hierarchical Image Clustering and Atlas Synthesis

    PubMed Central

    Wang, Qian; Chen, Liya; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2010-01-01

    Groupwise registration has recently been proposed for simultaneous and consistent registration of all images in a group. Since many deformation parameters need to be optimized for each image under registration, the number of images that can be effectively handled by conventional groupwise registration methods is limited. Moreover, the robustness of registration is at stake due to significant intersubject variability. To overcome these problems, we present a groupwise registration framework, which is based on a hierarchical image clustering and atlas synthesis strategy. The basic idea is to decompose a large-scale groupwise registration problem into a series of small-scale problems, each of which is relatively easy to solve using a general computer. In particular, we employ a method called affinity propagation, which is designed for fast and robust clustering, to hierarchically cluster images into a pyramid of classes. Intraclass registration is then performed to register all images within individual classes, resulting in a representative center image for each class. These center images of different classes are further registered, from the bottom to the top in the pyramid. Once the registration reaches the summit of the pyramid, a single center image, or an atlas, is synthesized. Utilizing this strategy, we can efficiently and effectively register a large image group, construct their atlas, and, at the same time, establish shape correspondences between each image and the atlas. We have evaluated our framework using real and simulated data, and the results indicate that our framework achieves better robustness and registration accuracy compared to conventional methods. PMID:20063349

  7. Tree-Based Hierarchical Reinforcement Learning

    DTIC Science & Technology

    2002-08-01

    Lindsey and Krissie have all been wonderful friends. My Australian friends, Cameron, Sarah and Max gave sup- port from all corners of the world; maybe we’ll...229, 1998. BIBLIOGRAPHY 139 Bernhard Hengst. Generating hierarchical structure in reinforcement learning from state variables. In Riichiro Mizoguchi and...Computer Science. Springer, 2000. ISBN 3-540-67925-1. Bernhard Hengst. Discovering hierarchy in reinforcement learning with HEXQ. In Inter- national

  8. 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.

  9. Scene text detection based on probability map and hierarchical model

    NASA Astrophysics Data System (ADS)

    Zhou, Gang; Liu, Yuehu

    2012-06-01

    Scene text detection is an important step for the text-based information extraction system. This problem is challenging due to the variations of size, unknown colors, and background complexity. We present a novel algorithm to robustly detect text in scene images. To segment text candidate connected components (CC) from images, a text probability map consisting of the text position and scale information is estimated by a text region detector. To filter out the non-text CCs, a hierarchical model consisting of two classifiers in cascade is utilized. The first stage of the model estimates text probabilities with unary component features. The second stage classifier is trained with both probability features and similarity features. Since the proposed method is learning-based, there are very few manual parameters required. Experimental results on the public benchmark ICDAR dataset show that our algorithm outperforms other state-of-the-art methods.

  10. 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.

  11. 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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  12. The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

    NASA Astrophysics Data System (ADS)

    Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

    2016-09-01

    The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

  13. Optical hierarchical authentication based on interference and hash function.

    PubMed

    He, Wenqi; Peng, Xiang; Meng, Xiangfeng; Liu, Xiaoli

    2012-11-10

    We propose a method to achieve the purpose of hierarchical authentication on the basis of two beams' interference and the one-way hash function. For this security protection system, only if the "phase key" and the password-controlled "phase lock" of a user are verified simultaneously can one obtain a permission to visit the confidential resources of the system. Moreover, this scheme can not only check the legality of the users but also verify their identity levels so as to grant them corresponding hierarchical access permissions. The authentication process is straightforward; the phase key and the password-controlled phase lock of one user are loading on two spatial light modulators in advance, by which two coherent beams are modulated and then interfere with each other at the output plane leading to an output image. By comparing the output image with all the standard certification images in the database, the system can thus verify the user's identity. However, the system designing process involves an iterative modified phase retrieval algorithm. For an authorized user, a phase lock is first created based on a "digital fingerprint," which is the result of a hash function on a preselected user password. The corresponding phase key can then be determined by use of the phase lock and a designated standard certification image. Theoretical analysis and computer simulations both validate the effectiveness of our method.

  14. 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.

  15. Array-based Hierarchical Mesh Generation in Parallel

    DOE PAGES

    Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; ...

    2015-11-03

    In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. Inmore » conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.« less

  16. Array-based Hierarchical Mesh Generation in Parallel

    SciTech Connect

    Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; Mahadevan, Vijay; Jiao, Xiangmin

    2015-11-03

    In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. In conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.

  17. Fast pedestrian detection based on multiple instance hierarchical HOG matrices

    NASA Astrophysics Data System (ADS)

    Cheng, Guang; Meng, Long; Lin, Xinggang

    2013-12-01

    Many pedestrian detection research works focused on the improvement of detection performance, without considering the detection speed, making the detection algorithms not applicable for real-world requirement for real-time processing. To explore this problem, we first propose a pre-processing method Hierarchical HOG Matrices to replace the traditional integral histogram of gradients, which stores more data in the pre-processing phase to reduce computation time. A matrix-based detection computation structure is also proposed, which organize the massive data computations in the scanning detection process into matrix operations to optimize the overall speed. We then add multiple instance learning into the fast pedestrian detection algorithm to further enhance its accuracy. Experiments demonstrate that the proposed fast and robust pedestrian detection algorithm based on the multiple instance feature achieves an accuracy comparable to the latest algorithms, with the best speed among the algorithms with an accuracy of the same level.

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

    PubMed

    Botvinick, Matthew; Weinstein, Ari

    2014-11-05

    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.

  19. A 3D AgCl hierarchical superstructure synthesized by a wet chemical oxidation method.

    PubMed

    Lou, Zaizhu; Huang, Baibiao; Ma, Xiangchao; Zhang, Xiaoyang; Qin, Xiaoyan; Wang, Zeyan; Dai, Ying; Liu, Yuanyuan

    2012-12-07

    A novel 3D AgCl hierarchical superstructure, with fast growth along the 〈111〉 directions of cubic seeds, is synthesized by using a wet chemical oxidation method. The morphological structures and the growth process are investigated by scanning electron microscopy and X-ray diffraction. The crystal structures are analyzed by their crystallographic orientations. The surface energy of AgCl facets {100}, {110}, and {111} with absorbance of Cl(-) ions is studied by density functional theory calculations. Based on the experimental and computational results, a plausible mechanism is proposed to illustrate the formation of the 3D AgCl hierarchical superstructures. With more active sites, the photocatalytic activity of the 3D AgCl hierarchical superstructures is better than those of concave and cubic ones in oxygen evolution under irradiation by visible light.

  20. 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

  1. 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.

  2. Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

    NASA Astrophysics Data System (ADS)

    Tsai, F. T. C.; Elshall, A. S.

    2014-12-01

    Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

  3. 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.

  4. Breaking the hierarchy - a new cluster selection mechanism for hierarchical clustering methods

    PubMed Central

    Zahoránszky, László A; Katona, Gyula Y; Hári, Péter; Málnási-Csizmadia, András; Zweig, Katharina A; Zahoránszky-Köhalmi, Gergely

    2009-01-01

    Background Hierarchical clustering methods like Ward's method have been used since decades to understand biological and chemical data sets. In order to get a partition of the data set, it is necessary to choose an optimal level of the hierarchy by a so-called level selection algorithm. In 2005, a new kind of hierarchical clustering method was introduced by Palla et al. that differs in two ways from Ward's method: it can be used on data on which no full similarity matrix is defined and it can produce overlapping clusters, i.e., allow for multiple membership of items in clusters. These features are optimal for biological and chemical data sets but until now no level selection algorithm has been published for this method. Results In this article we provide a general selection scheme, the level independent clustering selection method, called LInCS. With it, clusters can be selected from any level in quadratic time with respect to the number of clusters. Since hierarchically clustered data is not necessarily associated with a similarity measure, the selection is based on a graph theoretic notion of cohesive clusters. We present results of our method on two data sets, a set of drug like molecules and set of protein-protein interaction (PPI) data. In both cases the method provides a clustering with very good sensitivity and specificity values according to a given reference clustering. Moreover, we can show for the PPI data set that our graph theoretic cohesiveness measure indeed chooses biologically homogeneous clusters and disregards inhomogeneous ones in most cases. We finally discuss how the method can be generalized to other hierarchical clustering methods to allow for a level independent cluster selection. Conclusion Using our new cluster selection method together with the method by Palla et al. provides a new interesting clustering mechanism that allows to compute overlapping clusters, which is especially valuable for biological and chemical data sets. PMID:19840391

  5. 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.

  6. A method of transition conflict resolving in hierarchical control

    NASA Astrophysics Data System (ADS)

    Łabiak, Grzegorz

    2016-09-01

    The paper concerns the problem of automatic solving of transition conflicts in hierarchical concurrent state machines (also known as UML state machine). Preparing by the designer a formal specification of a behaviour free from conflicts can be very complex. In this paper, it is proposed a method for solving conflicts through transition predicates modification. Partially specified predicates in the nondeterministic diagram are transformed into a symbolic Boolean space, whose points of the space code all possible valuations of transition predicates. Next, all valuations under partial specifications are logically multiplied by a function which represents all possible orthogonal predicate valuations. The result of this operation contains all possible collections of predicates, which under given partial specification make that the original diagram is conflict free and deterministic.

  7. Methods of hierarchical control for a segmented active mirror

    NASA Astrophysics Data System (ADS)

    Lazzarini, Albert; Ames, Gregory H.; Conklin, Edward K.

    1994-05-01

    The PAMELA segmented optical surface concept uses the cellular automata paradigm to build up an active surface of individually controlled elements that maintain edge-match by relying on electronically sensed nearest neighbor edge-to-edge errors. The segments are controlled in tilt directly from a wavefront sensor (e.g., of the Hartmann-Schack type) in a separate parallel loop. The approach obviates the matrix operations needed in a typical multiple-input, multiple- out (MIMO) servo control system. In this manner, the segmented optical system is extensible to arbitrary aperture diameter by gradually building up the active surface using identical elements. This paper addresses methods to improve the real-time adaptive control of such a surface using hierarchical control architectures.

  8. Methods of hierarchical control for a segmented active mirror

    SciTech Connect

    Lazzarini, A.; Ames, G.H.; Conklin, E.

    1994-12-31

    The PAMELA (Phased Array Mirror Extensible Large Aperture) segmented optical surface concept uses the cellular automata paradigm to build up an active surface of individually controlled elements that maintain edge-match by relying on electronically sensed nearest neighbor edge-to-edge errors. The segments are controlled in tilt directly from a wavefront sensor (e.g., of the Hartmann-Schack type) in a separate, parallel loop. The approach obviates the matrix operations needed in a typical multiple-input, multiple-out (MIMO) servo control system. In this manner, the segmented optical system is extensible to arbitrary aperture diameter by gradually building up the active surface using identical elements. This paper addresses methods to improve the real-time adaptive control of such a surface using hierarchical control architectures.

  9. 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.

  10. 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.

  11. Hierarchical trie packet classification algorithm based on expectation-maximization clustering

    PubMed Central

    Bi, Xia-an; Zhao, Junxia

    2017-01-01

    With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

  12. Hierarchical trie packet classification algorithm based on expectation-maximization clustering.

    PubMed

    Bi, Xia-An; Zhao, Junxia

    2017-01-01

    With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm.

  13. A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

    PubMed

    Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman

    2017-08-15

    Sibutramine may be illicitly included in herbal slimming foods and supplements marketed as "100% natural" to enhance weight loss. Considering public health and legal regulations, there is an urgent need for effective, rapid and reliable techniques to detect sibutramine in dietetic herbal foods, teas and dietary supplements. This research comprehensively explored, for the first time, detection of sibutramine in green tea, green coffee and mixed herbal tea using ATR-FTIR spectroscopic technique combined with chemometrics. Hierarchical cluster analysis and PCA principle component analysis techniques were employed in spectral range (2746-2656cm(-1)) for classification and discrimination through Euclidian distance and Ward's algorithm. Unadulterated and adulterated samples were classified and discriminated with respect to their sibutramine contents with perfect accuracy without any false prediction. The results suggest that existence of the active substance could be successfully determined at the levels in the range of 0.375-12mg in totally 1.75g of green tea, green coffee and mixed herbal tea by using FTIR-ATR technique combined with chemometrics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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.

  16. Local Approximation and Hierarchical Methods for Stochastic Optimization

    NASA Astrophysics Data System (ADS)

    Cheng, Bolong

    In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the

  17. 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.

  18. 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.

  19. Disturbance observer based hierarchical control of coaxial-rotor UAV.

    PubMed

    Mokhtari, M Rida; Cherki, Brahim; Braham, Amal Choukchou

    2017-03-01

    This paper propose an hierarchical controller based on a new disturbance observer with finite time convergence (FTDO) to solve the path tracking of a small coaxial-rotor-typs Unmanned Aerial Vehicles (UAVs) despite of unknown aerodynamic efforts. The hierarchical control technique is used to separate the flight control problem into an inner loop that controls attitude and an outer loop that controls the thrust force acting on the vehicle. The new disturbance observer with finite time convergence is intergated to online estimate the unknown uncertainties and disturbances and to actively compensate them in finite time.The analysis further extends to the design of a control law that takes the disturbance estimation procedure into account. Numerical simulations are carried out to demonstrate the efficiency of the proposed control strategy. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. 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.

  1. 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.

  2. A novel generic optimization method for irrigation scheduling under multiple objectives and multiple hierarchical layers in a canal network

    NASA Astrophysics Data System (ADS)

    Delgoda, Dilini; Malano, Hector; Saleem, Syed K.; Halgamuge, Malka N.

    2017-07-01

    This research proposes a novel generic method for irrigation scheduling in a canal network to optimize multiple objectives related to canal scheduling (e.g. maximizing water supply and minimizing imbalance of water distribution) within multiple hierarchical layers (e.g. the layers consisting of the main canal, distributaries) while utilizing traditional canal scheduling methods. It is based on modularizing the optimization process. The method is theoretically capable of optimizing an unlimited number of user-defined objectives within an unlimited number of hierarchical layers and only limited by resource availability (e.g. maximum canal capacity and water limitations) in the network. It allows flexible decision-making through quantification of the mutual effects of optimizing conflicting objectives and is adaptable to available multi-objective evolutionary algorithms. The method's application is demonstrated using a hypothetical canal network example with six objectives and three hierarchical layers, and a real scenario with four objectives and two layers.

  3. Guided compressive sensing single-pixel imaging technique based on hierarchical model

    NASA Astrophysics Data System (ADS)

    Peng, Yang; Liu, Yu; Ren, Weiya; Tan, Shuren; Zhang, Maojun

    2016-04-01

    Single-pixel imaging has emerged a decade ago as an imaging technique that exploits the theory of compressive sensing. In this research, the problem of optimizing the measurement matrix in compressive sensing framework was addressed. Thus far, random measurement matrices are widely used because they provide small coherence. However, recent reports claim that measurement matrix can be optimized, thereby improving its performance. Based on such proposition, this study proposed an alternative approach of optimizing the measurement matrix in a hierarchical model. In particular, this study constructed the hierarchical model based on an increasing resolution grade by exploiting the guided information and the adaptive step size method. An image with a demanded resolution was then obtained using the l1-norm method. Subsequently, the performance of the introduced method was verified and compared with those of existing approaches via several experiments. Results of the tests indicated that the reconstruction quality of optimizing the measurement matrix was improved when the proposed method was used.

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

    DTIC Science & Technology

    2012-01-22

    methods as a seamless isogeometric design -through-analysis procedure for complex engineering parts defined by T-spline CAD surfaces, specifically a ship...by Hughes and co-workers [1] to bridge the gap between computer aided design ( CAD ) and finite element analysis (FEA). Its core idea is to use the...the ordering of matrices was optimized by the symmetric reverse Cuthill-McKee algorithm [78]. The condition number of the matrix is improved by the

  5. Having It Both Ways: Hierarchical Focusing as Research Interview Method.

    ERIC Educational Resources Information Center

    Tomlinson, Peter

    1989-01-01

    Describes the increased acceptance of constructivism as a research paradigm in the social sciences and its applicability for interviewing in educational research. Notes major sources of this viewpoint and highlights a validity dilemma relative to the roles of interviewer and interviewee. Proposes the strategy of hierarchical focusing as a means to…

  6. Low energy isomers of (H2O)25 from a hierarchical method based on Monte Carlo Temperature Basin Paving and Molecular Tailoring Approaches benchmarked by full MP2 calculations

    SciTech Connect

    Sahu, Nityananda; Gadre, Shridhar R.; 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 (MCTBP) sampling of the cluster’s Potential Energy Surface (PES) with the Effective Fragment Potential (EFP), subsequent geometry optimization using the Molecular Tailoring fragmentation Approach (MTA) and final refinement at the second order Møller Plesset perturbation (MP2) level of theory. The MTA geometry optimizations used between 14 and 18 main fragments with maximum sizes between 11 and 14 water molecules and average size of 10 water molecules, whose energies and gradients were computed at the MP2 level. The MTA-MP2 optimized geometries were found to be quite close (within < 0.5 kcal/mol) to the ones obtained from the MP2 optimization of the whole cluster. The grafting of the MTA-MP2 energies yields electronic energies that are within < 5×10-4 a.u. from the MP2 results for the whole cluster while preserving their energy order. The MTA-MP2 method was also found to reproduce the MP2 harmonic vibrational frequencies in both the HOH bending and the OH stretching regions.

  7. MRI-based strain and strain rate analysis of left ventricle: a modified hierarchical transformation model

    PubMed Central

    2015-01-01

    Background Different from other indicators of cardiac function, such as ejection fraction and transmitral early diastolic velocity, myocardial strain is promising to capture subtle alterations that result from early diseases of the myocardium. In order to extract the left ventricle (LV) myocardial strain and strain rate from cardiac cine-MRI, a modified hierarchical transformation model was proposed. Methods A hierarchical transformation model including the global and local LV deformations was employed to analyze the strain and strain rate of the left ventricle by cine-MRI image registration. The endocardial and epicardial contour information was introduced to enhance the registration accuracy by combining the original hierarchical algorithm with an Iterative Closest Points using Invariant Features algorithm. The hierarchical model was validated by a normal volunteer first and then applied to two clinical cases (i.e., the normal volunteer and a diabetic patient) to evaluate their respective function. Results Based on the two clinical cases, by comparing the displacement fields of two selected landmarks in the normal volunteer, the proposed method showed a better performance than the original or unmodified model. Meanwhile, the comparison of the radial strain between the volunteer and patient demonstrated their apparent functional difference. Conclusions The present method could be used to estimate the LV myocardial strain and strain rate during a cardiac cycle and thus to quantify the analysis of the LV motion function. PMID:25602778

  8. The multiple outliers detection using agglomerative hierarchical methods in circular regression model

    NASA Astrophysics Data System (ADS)

    Zanariah Satari, Siti; Di, Nur Faraidah Muhammad; Zakaria, Roslinazairimah

    2017-09-01

    Two agglomerative hierarchical clustering algorithms for identifying multiple outliers in circular regression model have been developed in this study. The agglomerative hierarchical clustering algorithm starts with every single data in a single cluster and it continues to merge with the closest pair of clusters according to some similarity criterion until all the data are grouped in one cluster. The single-linkage method is one of the simplest agglomerative hierarchical methods that is commonly used to detect outlier. In this study, we compared the performance of single-linkage method with another agglomerative hierarchical method, namely average linkage for detecting outlier in circular regression model. The performances of both methods were examined via simulation studies by measuring their “success” probability, masking effect, and swamping effect with different number of sample sizes and level of contaminations. The results show that the single-linkage method performs very well in detecting the multiple outliers with lower masking and swamping effects.

  9. Hierarchical extreme learning machine based reinforcement learning for goal localization

    NASA Astrophysics Data System (ADS)

    AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini

    2017-03-01

    The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.

  10. 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.

  11. Hierarchically organized soft-materials based on fullerenes

    NASA Astrophysics Data System (ADS)

    Nakanishi, Takashi

    2009-04-01

    Simple chemical modifications of fullerene (C60) with long aliphatic chains provide novel type amphiphilic molecules playing in organic solvents due to the two different intermolecular interactions, namely π-π on C60 and van der Waals interactions on aliphatic chain moieties, respectively, and open a door developing supramolecular soft-materials having hierarchically organized architectures, various morphologies and functions based on fullerenes. By tuning the length and number of aliphatic chains on the derivatives as well as experimental conditions such as solvents, temperature, substrates for preparation of the assemblies, the assembled fullerenes showed various faces such as creating of many unique-shaped objects with controlled their dimensionality. For instance, nanowires and thin disks with single bilayer thickness in nanometer size, globular, fibrous, conical objects in mesoscopic (sub-micrometer) scale and flower-shaped and direction-controlled spiral objects in micrometer scale are obtained. As bulk states, thermotropic liquid crystals and room temperature (isotropic) liquid fullerenes are interestingly prepared from this molecular designs and showed not only their fluid natures and comparably high carrier mobility as fullerene-based organic-semiconductor phenomena. In addition, nano-carbon superhydrophobic surface with fractal morphology of the two-tier roughness on a nano- and microscopic scale was created from one of the supramolecular objects. The all of hierarchical supramolecular assemblies describing in this review is derived from fine-tuning intermolecular interactions of fullerene derivatives bearing long aliphatic chains.

  12. 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.

  13. 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.

  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. DNA sequence analysis using hierarchical ART-based classification networks

    SciTech Connect

    LeBlanc, C.; Hruska, S.I.; Katholi, C.R.; Unnasch, T.R.

    1994-12-31

    Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in real-time, and require no retraining to classify novel sequences. We have adapted ART networks to provide support to scientists attempting to categorize tandem repeat DNA fragments from Onchocerca volvulus. In this approach, sequences of DNA fragments are presented to multiple ART-based networks which are linked together into two (or more) tiers; the first provides coarse sequence classification while the sub- sequent tiers refine the classifications as needed. The overall rating of the resulting classification of fragments is measured using statistical techniques based on those introduced to validate results from traditional phylogenetic analysis. Tests of the Hierarchical ART-based Classification Network, or HABclass network, indicate its value as a fast, easy-to-use classification tool which adapts to new data without retraining on previously classified data.

  16. Stable-phase method for hierarchical annealing in the reconstruction of porous media images.

    PubMed

    Chen, Dongdong; Teng, Qizhi; He, Xiaohai; Xu, Zhi; Li, Zhengji

    2014-01-01

    In this paper, we introduce a stable-phase approach for hierarchical annealing which addresses the very large computational costs associated with simulated annealing for the reconstruction of large-scale binary porous media images. Our presented method, which uses the two-point correlation function as the morphological descriptor, involves the reconstruction of three-phase and two-phase structures. We consider reconstructing the three-phase structures based on standard annealing and the two-phase structures based on standard and hierarchical annealings. From the result of the two-dimensional (2D) reconstruction, we find that the 2D generation does not fully capture the morphological information of the original image, even though the two-point correlation function of the reconstruction is in excellent agreement with that of the reference image. For the reconstructed three-dimensional (3D) microstructure, we calculate its permeability and compare it to that of the reference 3D microstructure. The result indicates that the reconstructed structure has a lower degree of connectedness than that of the actual sandstone. We also compare the computation time of our presented method to that of the standard annealing, which shows that our presented method of orders of magnitude improves the convergence rate. That is because only a small part of the pixels in the overall hierarchy need to be considered for sampling by the annealer.

  17. Hierarchical CT to Ultrasound Registration of the Lumbar Spine: A Comparison with Other Registration Methods.

    PubMed

    Koo, Terry K; Kwok, Wingchi Edmund

    2016-10-01

    Three-dimensional (3D) measurement of the spine can provide important information for functional, developmental, diagnostic, and treatment-effect evaluations. However, existing measurement techniques are either 2-dimensional, highly invasive, or involve a high radiation dose, prohibiting their widespread and repeated use in both research and clinical settings. Non-invasive, non-ionizing, 3D measurement of the spine is still beyond the current state-of-the-art. Towards this goal, we developed an intensity-based hierarchical CT-ultrasound registration approach to quantify the 3D positions and orientations of lumbar vertebrae from 3D freehand ultrasound and one-time computed tomography. The method was validated using a human dry bone specimen (T12-L5) and a porcine cadaver (L2-L6) by comparing the registration results with a gold standard fiducial-based registration. Mean (SD) target registration error and percentage of successful registration were 1.2 (0.6) mm and 100% for the human dry bone specimen, and 2.18 (0.82) mm and 92% for the porcine cadaver, indicating that the method is accurate and robust under clinically realistic conditions. Given that the use of ultrasound eliminates ionizing radiation during pose measurements, we believe that the hierarchical CT-ultrasound registration method is an attractive option for quantifying 3D poses of individual vertebra and motion segment, and thus warrants further investigations.

  18. A top-down hierarchical spatio-temporal process description method and its data organization

    NASA Astrophysics Data System (ADS)

    Xie, Jiong; Xue, Cunjin

    2009-10-01

    Modeling and representing spatio-temporal process is the key foundation for analyzing geographic phenomenon and acquiring spatio-temporal high-level knowledge. Spatio-temporal representation methods with bottom-up approach based on object modeling view lack of explicit definition of geographic phenomenon and finer-grained representation of spatio-temporal causal relationships. Based on significant advances in data modeling of spatio-temporal object and event, aimed to represent discrete regional dynamic phenomenon composed with group of spatio-temporal objects, a regional spatio-temporal process description method using Top-Down Hierarchical approach (STP-TDH) is proposed and a data organization structure based on relational database is designed and implemented which builds up the data structure foundation for carrying out advanced data utilization and decision-making. The land use application case indicated that process modeling with top-down approach was proved to be good with the spatio-temporal cognition characteristic of our human, and its hierarchical representation framework can depict dynamic evolution characteristic of regional phenomenon with finer-grained level and can reduce complexity of process description.

  19. GENSCHED - A Real World Hierarchical Planning Knowledge-Based System

    NASA Astrophysics Data System (ADS)

    Semeco, Antonio C.; Williams, Bryan D.; Roth, Stefan; Gilmore, John F.

    1986-03-01

    This article describes the design and implementation of GENSCHED, a hierarchical planning system for scheduling production orders in manufacturing facilities.In a typical manufacturing application, orders for the production of certain items arrive continuously and must be scheduled to minimize tardiness, wait-in-process time, and early completion in addition to maximize throughput and resource utilization. In many cases, arriving orders generate manufacturing requirements beyond the capacity of the plant and compromises must be made. Manufacturing operations desire the capability to rearrange the backlog of orders to expedite higher priority ones, and to estimate the effect of newly arriving orders in the current backlog. GENSCHED features a hierarchical planner which takes advantage of the repetitive nature of the plans to efficiently generate valid schedules. A user interface allows manual and automatic scheduling and "what-if" processing of production orders. Finally, a rule-based subsystem for entering and maintaining domain-specific knowledge is exploited to improve schedules and minimize search.

  20. A fast quad-tree based two dimensional hierarchical clustering.

    PubMed

    Rajadurai, Priscilla; Sankaranarayanan, Swamynathan

    2012-01-01

    Recently, microarray technologies have become a robust technique in the area of genomics. An important step in the analysis of gene expression data is the identification of groups of genes disclosing analogous expression patterns. Cluster analysis partitions a given dataset into groups based on specified features. Euclidean distance is a widely used similarity measure for gene expression data that considers the amount of changes in gene expression. However, the huge number of genes and the intricacy of biological networks have highly increased the challenges of comprehending and interpreting the resulting group of data, increasing processing time. The proposed technique focuses on a QT based fast 2-dimensional hierarchical clustering algorithm to perform clustering. The construction of the closest pair data structure is an each level is an important time factor, which determines the processing time of clustering. The proposed model reduces the processing time and improves analysis of gene expression data.

  1. 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

  2. Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

    PubMed

    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.

  3. WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

    PubMed Central

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

    2014-01-01

    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. PMID:25207873

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

    PubMed

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

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

  5. Three-dimensional information hierarchical encryption based on computer-generated holograms

    NASA Astrophysics Data System (ADS)

    Kong, Dezhao; Shen, Xueju; Cao, Liangcai; Zhang, Hao; Zong, Song; Jin, Guofan

    2016-12-01

    A novel approach for encrypting three-dimensional (3-D) scene information hierarchically based on computer-generated holograms (CGHs) is proposed. The CGHs of the layer-oriented 3-D scene information are produced by angular-spectrum propagation algorithm at different depths. All the CGHs are then modulated by different chaotic random phase masks generated by the logistic map. Hierarchical encryption encoding is applied when all the CGHs are accumulated one by one, and the reconstructed volume of the 3-D scene information depends on permissions of different users. The chaotic random phase masks could be encoded into several parameters of the chaotic sequences to simplify the transmission and preservation of the keys. Optical experiments verify the proposed method and numerical simulations show the high key sensitivity, high security, and application flexibility of the method.

  6. Synthesis of Hierarchical Porous Metals Using Ionic-Liquid-Based Media as Solvent and Template.

    PubMed

    Kang, Xinchen; Sun, Xiaofu; Ma, Xiaoxue; Zhang, Pei; Zhang, Zhanrong; Meng, Qinglei; Han, Buxing

    2017-10-02

    It was found that nanodomains existed in the ionic liquid (IL)-based ternary system containing IL 1-ethyl-3-methylimidazole tetrafluoroborate (EmimBF4 ), IL 1-decyl-3-methylimidazole nitrate (DmimNO3 ) and water, and the size distribution of the domains varied continuously with the composition of the solution. A strategy to synthesize hierarchical porous metals using IL-based media as solvent and template is proposed, and the hierarchical porous Ru and Pt metals were prepared by the assembly of metal clusters of about 1.5 nm using this new method. It is demonstrated that the metals have micropores and mesopores, and the size distribution is tuned by controlling the composition of the solution. Porous Ru was used for a series of hydrogenation reactions. It has an outstanding catalytic performance owing to its special morphology and structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. A Model of Knowledge Based Information Retrieval with Hierarchical Concept Graph.

    ERIC Educational Resources Information Center

    Kim, Young Whan; Kim, Jin H.

    1990-01-01

    Proposes a model of knowledge-based information retrieval (KBIR) that is based on a hierarchical concept graph (HCG) which shows relationships between index terms and constitutes a hierarchical thesaurus as a knowledge base. Conceptual distance between a query and an object is discussed and the use of Boolean operators is described. (25…

  8. A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

    PubMed Central

    2014-01-01

    Background The inter-patient classification schema and the Association for the Advancement of Medical Instrumentation (AAMI) standards are important to the construction and evaluation of automated heartbeat classification systems. The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats. The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). Methods Based on the different characteristics of VEB and SVEB, a novel hierarchical heartbeat classification system was constructed. This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods. First, random projection and support vector machine (SVM) ensemble were used to detect VEB. Then, the ratio of the RR interval was compared to a predetermined threshold to detect SVEB. The optimal parameters for the classification models were selected on the training set and used in the independent testing set to assess the final performance of the classification system. Meanwhile, the effect of different lead configurations on the classification results was evaluated. Results Results showed that the performance of this classification system was notably superior to that of other methods. The VEB detection sensitivity was 93.9% with a positive predictive value of 90.9%, and the SVEB detection sensitivity was 91.1% with a positive predictive value of 42.2%. In addition, this classification process was relatively fast. Conclusions A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB. It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in

  9. Design and Fabrication of Hierarchically Porous Carbon with a Template-free Method

    PubMed Central

    Gong, Yutong; Wei, Zhongzhe; Wang, Jing; Zhang, Pengfei; Li, Haoran; Wang, Yong

    2014-01-01

    Fabrication of hierarchically porous carbon materials (HPCs) with high surface area and pore volume has always been pursued. However, the currently effective template methods and acid/base activation strategies suffer from the drawbacks of either high costs or tedious steps. Herein, HPCs with 3D macro-mesopores and short-range meso-micropores were fabricated via an easy and sustainable two-step method from biomass. Macro-mesopores were constructed by slightly accumulation/aggregation of carbon spheres ranging from 60 nm to 80 nm, providing efficient mass diffusion pathways. Short-range mesopores and micropores with high electrolyte accessibility were developed in these spheres by air activation. The obtained HPCs showed surface area values up to 1306 m2/g and high mesopore volume proportion (63.9%). They demonstrated excellent capacitance and low equivalent series resistance (ESR) as supercapacitor electrode materials, suggesting the efficient diffusion and adsorption of electrolyte ions in the designed hierarchically porous structure. PMID:25215549

  10. Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

    PubMed

    Stankov, L

    1979-07-01

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

  11. Pathway-based approach using hierarchical components of collapsed rare variants

    PubMed Central

    Lee, Sungyoung; Choi, Sungkyoung; Kim, Young Jin; Kim, Bong-Jo; Hwang, Heungsun; Park, Taesung

    2016-01-01

    Motivation: To address ‘missing heritability’ issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem. Results: Through simulation studies, the proposed method was shown to have higher statistical power than the existing pathway-based methods. In addition, our method was applied to the large-scale whole-exome sequencing data with levels of a liver enzyme using two well-known pathway databases Biocarta and KEGG. This application demonstrated that our method not only identified associated pathways but also successfully detected biologically plausible pathways for a phenotype of interest. These findings were successfully replicated by an independent large-scale exome chip study. Availability and Implementation: An implementation of PHARAOH is available at http://statgen.snu.ac.kr/software/pharaoh/. Contact: tspark@stats.snu.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27587678

  12. CdSe quantum dot sensitized solar cell based hierarchical branched ZnO nanoarrays

    NASA Astrophysics Data System (ADS)

    Xu, Gang; Deng, Jianping

    2015-05-01

    The hierarchical branched ZnO nanoarrays (NAs) photoanode was prepared by a two-step hydrothermal method. Vertically aligned long ZnO NWs were first synthesized using as the backbone of hierarchical branched ZnO NAs structure and high quality ZnO NAs branches were grown on the surface of backbone ZnO NAs. The structured films enhance the optical path length through the light scatting effect of branched ZnO NAs and prove the larger internal surface area in NAs film to increase quantum dots (QDs) sensitizer loadings, so the light absorption has an optimization. Compared with the cell based conventional 1D ZnO NAs, the efficiency of the new cells has a great improvement due to the increase of the short circuit current density.

  13. 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.

  14. 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.

  15. The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods

    NASA Astrophysics Data System (ADS)

    Kantar, Ersin; Keskin, Mustafa

    2013-11-01

    This study uses hierarchical structure methods (minimal spanning tree (MST) and hierarchical tree (HT)) to examine the relationship between energy consumption and economic growth in a sample of 30 Asian countries covering the period 1971-2008. These countries are categorized into four panels based on the World Bank income classification, namely high, upper middle, lower middle, and low income. In particular, we use the data of electricity consumption and real gross domestic product (GDP) per capita to detect the topological properties of the countries. We show a relationship between electricity consumption and economic growth by using the MST and HT. We also use the bootstrap technique 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. 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 relationship between energy consumption and economic growth for all income groups considered in this study and (iii) the results are in good agreement with the causal relationship between electricity consumption and economic growth.

  16. A modified hierarchical graph cut based video segmentation approach for high frame rate video

    NASA Astrophysics Data System (ADS)

    Hu, Xuezhang; Chakravarty, Sumit; She, Qi; Wang, Boyu

    2013-03-01

    Video object segmentation entails selecting and extracting objects of interest from a video sequence. Video Segmentation of Objects (VSO) is a critical task which has many applications, such as video edit, video decomposition and object recognition. The core of VSO system consists of two major problems of computer vision, namely object segmentation and object tracking. These two difficulties need to be solved in tandem in an efficient manner to handle variations in shape deformation, appearance alteration and background clutter. Along with segmentation efficiency computational expense is also a critical parameter for algorithm development. Most existing methods utilize advanced tracking algorithms such as mean shift and particle filter, applied together with object segmentation schemes like Level sets or graph methods. As video is a spatiotemporal data, it gives an extensive opportunity to focus on the regions of high spatiotemporal variation. We propose a new algorithm to concentrate on the high variations of the video data and use modified hierarchical processing to capture the spatiotemporal variation. The novelty of the research presented here is to utilize a fast object tracking algorithm conjoined with graph cut based segmentation in a hierarchical framework. This involves modifying both the object tracking algorithm and the graph cut segmentation algorithm to work in an optimized method in a local spatial region while also ensuring all relevant motion has been accounted for. Using an initial estimate of object and a hierarchical pyramid framework the proposed algorithm tracks and segments the object of interest in subsequent frames. Due to the modified hierarchal framework we can perform local processing of the video thereby enabling the proposed algorithm to target specific regions of the video where high spatiotemporal variations occur. Experiments performed with high frame rate video data shows the viability of the proposed approach.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

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

  19. A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

    NASA Astrophysics Data System (ADS)

    Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

    2017-05-01

    Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

  20. Fast shape-based nearest-neighbor search for brain MRIs using hierarchical feature matching.

    PubMed

    Zhu, Peihong; Awate, Suyash P; Gerber, Samuel; Whitaker, Ross

    2011-01-01

    This paper presents a fast method for quantifying shape differences/similarities between pairs of magnetic resonance (MR) brain images. Most shape comparisons in the literature require some kind of deformable registration or identification of exact correspondences. The proposed approach relies on an optimal matching of a large collection of features, using a very fast, hierarchical method from the literature, called spatial pyramid matching (SPM). This paper shows that edge-based image features in combination with SPM results in a fast similarity measure that captures relevant anatomical information in brain MRI. We present extensive comparisons against known methods for shape-based, k-nearest-neighbor lookup to evaluate the performance of the proposed method. Finally, we show that the method compares favorably with more computation-intensive methods in the construction of local atlases for use in brain MR image segmentation.

  1. The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods.

    PubMed

    Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

    2007-01-01

    Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

  2. 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.

  3. 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.

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

    PubMed Central

    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. PMID:27190534

  5. 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.

  6. Hierarchical Bayesian estimates of distributed MEG sources: theoretical aspects and comparison of variational and MCMC methods.

    PubMed

    Nummenmaa, Aapo; Auranen, Toni; Hämäläinen, Matti S; Jääskeläinen, Iiro P; Lampinen, Jouko; Sams, Mikko; Vehtari, Aki

    2007-04-01

    Magnetoencephalography (MEG) provides millisecond-scale temporal resolution for noninvasive mapping of human brain functions, but the problem of reconstructing the underlying source currents from the extracranial data has no unique solution. Several distributed source estimation methods based on different prior assumptions have been suggested for the resolution of this inverse problem. Recently, a hierarchical Bayesian generalization of the traditional minimum norm estimate (MNE) was proposed, in which the variance of distributed current at each cortical location is considered as a random variable and estimated from the data using the variational Bayesian (VB) framework. Here, we introduce an alternative scheme for performing Bayesian inference in the context of this hierarchical model by using Markov chain Monte Carlo (MCMC) strategies. In principle, the MCMC method is capable of numerically representing the true posterior distribution of the currents whereas the VB approach is inherently approximative. We point out some potential problems related to hyperprior selection in the previous work and study some possible solutions. A hyperprior sensitivity analysis is then performed, and the structure of the posterior distribution as revealed by the MCMC method is investigated. We show that the structure of the true posterior is rather complex with multiple modes corresponding to different possible solutions to the source reconstruction problem. We compare the results from the VB algorithm to those obtained from the MCMC simulation under different hyperparameter settings. The difficulties in using a unimodal variational distribution as a proxy for a truly multimodal distribution are also discussed. Simulated MEG data with realistic sensor and source geometries are used in performing the analyses.

  7. 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.

  8. 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.

  9. 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.

  10. A hierarchical voltage control method for multi-terminal AC/DC distribution system

    NASA Astrophysics Data System (ADS)

    Ma, Zhoujun; Zhu, Hong; Zhou, Dahong; Wang, Chunning; Tang, Renquan; Xu, Honghua

    2017-08-01

    A hierarchical control system is proposed in this paper to control the voltage of multi-terminal AC/DC distribution system. The hierarchical control system consists of PCC voltage control system, DG voltage control system and voltage regulator control system. The functions of three systems are to control the voltage of DC distribution network, AC bus voltage and area voltage. A method is proposed to deal with the whole control system. And a case study indicates that when voltage fluctuating, three layers of power flow control system is running orderly, and can maintain voltage stability.

  11. COCO-CL: hierarchical clustering of homology relations based on evolutionary correlations

    PubMed Central

    Zotenko, Elena; Tasneem, Asba

    2006-01-01

    Motivation Determining orthology relations among genes across multiple genomes is an important problem in the post-genomic era. Identifying orthologous genes can not only help predict functional annotations for newly sequenced or poorly characterized genomes, but can also help predict new protein–protein interactions. Unfortunately, determining orthology relation through computational methods is not straightforward due to the presence of paralogs. Traditional approaches have relied on pairwise sequence comparisons to construct graphs, which were then partitioned into putative clusters of orthologous groups. These methods do not attempt to preserve the non-transitivity and hierarchic nature of the orthology relation. Results We propose a new method, COCO-CL, for hierarchical clustering of homology relations and identification of orthologous groups of genes. Unlike previous approaches, which are based on pairwise sequence comparisons, our method explores the correlation of evolutionary histories of individual genes in a more global context. COCO-CL can be used as a semi-independent method to delineate the orthology/paralogy relation for a refined set of homologous proteins obtained using a less-conservative clustering approach, or as a refiner that removes putative out-paralogs from clusters computed using a more inclusive approach. We analyze our clustering results manually, with support from literature and functional annotations. Since our orthology determination procedure does not employ a species tree to infer duplication events, it can be used in situations when the species tree is unknown or uncertain. PMID:16434444

  12. An alterative method for hospital partition determination using hierarchical cluster analysis.

    PubMed

    Klastorin, T D

    1982-01-01

    The classification of short-term hospitals into homogeneous groups has become an integral part of many systems designed to abate continuing cost inflation in the hospital industry. This paper describes one approach which was developed to identify homogeneous groups of short-term hospitals. The approach, based on hierarchical cluster analysis, defines an objective measure (called expected distinctiveness) to evaluate any group of hospitals identified by a hierarchical grouping structure or dendrogram. Using this measure, an efficient algorithm is developed which finds the hospital partition from the identified groups which maximizes total expected distinctiveness. A numerical example illustrates the application and extensions.

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

    PubMed

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

    2016-09-22

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

  14. 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.

  15. Global vs. Localized Search: A Comparison of Database Selection Methods in a Hierarchical Environment.

    ERIC Educational Resources Information Center

    Conrad, Jack G.; Claussen, Joanne Smestad; Yang, Changwen

    2002-01-01

    Compares standard global information retrieval searching with more localized techniques to address the database selection problem that users often have when searching for the most relevant database, based on experiences with the Westlaw Directory. Findings indicate that a browse plus search approach in a hierarchical environment produces the most…

  16. Application of the fault diagnosis strategy based on hierarchical information fusion in motors fault diagnosis

    NASA Astrophysics Data System (ADS)

    Xia, Li; Fei, Qi

    2006-03-01

    This paper has analyzed merits and demerits of both neural network technique and of the information fusion methods based on the D-S (dempster-shafer evidence) Theory as well as their complementarity, proposed the hierarchical information fusion fault diagnosis strategy by combining the neural network technique and the fused decision diagnosis based on D-S Theory, and established a corresponding functional model. Thus, we can not only solve a series of problems caused by rapid growth in size and complexity of neural network structure with diagnosis parameters increasing, but also can provide effective method for basic probability assignment in D-S Theory. The application of the strategy to diagnosing faults of motor bearings has proved that this method is of fairly high accuracy and reliability in fault diagnosis.

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

    NASA Astrophysics Data System (ADS)

    Hu, Jinyan; Li, Li; Yang, Yunfeng

    2017-06-01

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

  18. 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.

  19. 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.

  20. Pathway-based approach using hierarchical components of collapsed rare variants.

    PubMed

    Lee, Sungyoung; Choi, Sungkyoung; Kim, Young Jin; Kim, Bong-Jo; Hwang, Heungsun; Park, Taesung

    2016-09-01

    To address 'missing heritability' issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem. Through simulation studies, the proposed method was shown to have higher statistical power than the existing pathway-based methods. In addition, our method was applied to the large-scale whole-exome sequencing data with levels of a liver enzyme using two well-known pathway databases Biocarta and KEGG. This application demonstrated that our method not only identified associated pathways but also successfully detected biologically plausible pathways for a phenotype of interest. These findings were successfully replicated by an independent large-scale exome chip study. An implementation of PHARAOH is available at http://statgen.snu.ac.kr/software/pharaoh/ tspark@stats.snu.ac.kr Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

    DTIC Science & Technology

    2014-03-27

    LARGE SCALE HIERARCHICAL K-MEANS BASED IMAGE RETRIEVAL WITH MAPREDUCE THESIS William E. Murphy, Second Lieutenant, USAF AFIT-ENG-14-M-56 DEPARTMENT...RELEASE; DISTRIBUTION UNLIMITED The views expressed in this thesis are those of the author and do not reflect the official policy or position of the...subject to copyright protection in the United States. AFIT-ENG-14-M-56 LARGE SCALE HIERARCHICAL K-MEANS BASED IMAGE RETRIEVAL WITH MAPREDUCE THESIS

  2. 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.

  3. 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.

  4. A multivariate hierarchical Bayesian approach to measuring agreement in repeated measurement method comparison studies

    PubMed Central

    2009-01-01

    Background Assessing agreement in method comparison studies depends on two fundamentally important components; validity (the between method agreement) and reproducibility (the within method agreement). The Bland-Altman limits of agreement technique is one of the favoured approaches in medical literature for assessing between method validity. However, few researchers have adopted this approach for the assessment of both validity and reproducibility. This may be partly due to a lack of a flexible, easily implemented and readily available statistical machinery to analyse repeated measurement method comparison data. Methods Adopting the Bland-Altman framework, but using Bayesian methods, we present this statistical machinery. Two multivariate hierarchical Bayesian models are advocated, one which assumes that the underlying values for subjects remain static (exchangeable replicates) and one which assumes that the underlying values can change between repeated measurements (non-exchangeable replicates). Results We illustrate the salient advantages of these models using two separate datasets that have been previously analysed and presented; (i) assuming static underlying values analysed using both multivariate hierarchical Bayesian models, and (ii) assuming each subject's underlying value is continually changing quantity and analysed using the non-exchangeable replicate multivariate hierarchical Bayesian model. Conclusion These easily implemented models allow for full parameter uncertainty, simultaneous method comparison, handle unbalanced or missing data, and provide estimates and credible regions for all the parameters of interest. Computer code for the analyses in also presented, provided in the freely available and currently cost free software package WinBUGS. PMID:19161599

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

    NASA Astrophysics Data System (ADS)

    Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

    2011-03-01

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

  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

    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.

  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

    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.

  8. Bioactive glass-based materials with hierarchical porosity for medical applications: Review of recent advances.

    PubMed

    Baino, Francesco; Fiorilli, Sonia; Vitale-Brovarone, Chiara

    2016-09-15

    Bioactive glasses have been traditionally used in the clinical practice to fill and restore osseous defects due to their unique ability to bond to host bone and stimulate new bone growth. In the last decade, a new set of bioactive glasses characterized by a highly ordered mesoporous texture has been developed and studied as a smart platform for the controlled release of biomolecules, in situ therapy and regenerative applications. This review points out the great potential carried by hierarchical bioactive glass scaffolds that exhibit pore scales from the meso- to the macro-range, and their impact in the broad field of tissue engineering, including the emerging applications in contact with soft tissues and diagnostics. Recent advances in the preparation methods of these multiscale constructs (e.g. mono- or multi-phase scaffolds, fibrous meshes, coated systems, porous nanospheres, and composites) are examined, along with their strengths and weaknesses. A bright future is expected for hierarchical systems based on biocompatible mesoporous materials as they can provide a unique set of functionalities, including enhanced bioactivity, local release of ions and drugs to elicit specific therapeutic effects (improved osteogenesis and angiogenesis, antibacterial properties), and implant/drug tracking, which were unthinkable when research on bioactive glasses began. The advent of mesoporous bioactive glasses led to the birth of a new class of multifunctional biomaterials that have been proposed as smart platforms for local drug release and bone regeneration. Furthermore, mesoporous materials have been recently employed in the development of hierarchical macro-mesoporous scaffolds, composites and implantable systems. This reviews summarizes the latest applications of these multiscale biomaterials in tissue engineering, including the emerging applications in contact with soft tissues and diagnostics. The preparation methods, current uses and potential of these constructs and

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

    NASA Astrophysics Data System (ADS)

    Maleki, Khatereh; Abdizadeh, Hossein; Golobostanfard, Mohammad Reza; Adelfar, Razieh

    2017-02-01

    The hierarchical porous photoanode of the dye sensitized solar cell (DSSC) is synthesized through non-aqueous sol-gel method based on H3BO3 as an acid catalyst and the efficiencies of the fabricated DSSC based on these photoanodes are compared. The sol parameters of 0.17 M, water mole ratio of 4.5, acid mole ratio of 0.45, and solvent type of ethanol are introduced as optimum parameters for photoanode formation without any detectable cracks. The optimized hierarchical photoanode mainly contains anatase phase with slight shift toward higher angles, confirming the doping of boron into titania structure. Moreover, the porous structure involves two ranges of average pore sizes of 20 and 635 nm. The diffuse reflectance spectroscopy (DRS) shows the proper scattering and blueshift in band gap. The paste parameters of solid:liquid, TiO2:ethyl cellulose, and terpineol:ethanol equal to 11:89, 3.5:7.5, and 25:64, respectively, are assigned as optimized parameters for this novel paste. The photovoltaic properties of short circuit current density, open circuit voltage, fill factor, and efficiency of 5.89 mA/cm2, 703 mV, 0.7, and 2.91% are obtained for the optimized sample, respectively. The relatively higher short circuit current of the main sample compared to other samples is mainly due to higher dye adsorption in this sample corresponding to its higher surface area and presumably higher charge transfer confirmed by low RS and Rct in electrochemical impedance spectroscopy data. Boric acid as a catalyst in titania sol not only forms hierarchical porous structure, but also dopes the titania lattice, which results in appreciated performance in this device.

  10. 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.

  11. 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.

  12. 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.

  13. 3D HUMAN MOTION RETRIEVAL BASED ON HUMAN HIERARCHICAL INDEX STRUCTURE

    PubMed Central

    Guo, X.

    2013-01-01

    With the development and wide application of motion capture technology, the captured motion data sets are becoming larger and larger. For this reason, an efficient retrieval method for the motion database is very important. The retrieval method needs an appropriate indexing scheme and an effective similarity measure that can organize the existing motion data well. In this paper, we represent a human motion hierarchical index structure and adopt a nonlinear method to segment motion sequences. Based on this, we extract motion patterns and then we employ a fast similarity measure algorithm for motion pattern similarity computation to efficiently retrieve motion sequences. The experiment results show that the approach proposed in our paper is effective and efficient. PMID:24744481

  14. An Elastic Transparent Conductor Based on Hierarchically Wrinkled Reduced Graphene Oxide for Artificial Muscles and Sensors.

    PubMed

    Mu, Jiuke; Hou, Chengyi; Wang, Gang; Wang, Xuemin; Zhang, Qinghong; Li, Yaogang; Wang, Hongzhi; Zhu, Meifang

    2016-11-01

    Using a 3D stretching method, a highly elastic reduced graphene oxide (rGO)/polyacrylic ester hierarchically wrinkled elastic transparent conductor (HWETC) is fabricated. Periodic hierarchical N-rGO layer wrinkling allows the HWETC to show high conductivity (100-457 Ω ◻(-1) ) and transmittance (67-85%) under substantial stretching (>400%) and bending deformation (≈180°), which enables electrothermal actuation and strain sensing.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  17. Y chromosome SNP analysis using the single-base extension: a hierarchical multiplex design.

    PubMed

    Brión, María

    2005-01-01

    Single nucleotide polymorphisms (SNPs) are the most frequent polymorphisms described in the human genome, and their analysis is becoming an extensive routine in molecular biology, not only in the forensic field, but also in population and clinical genetics. In particular, SNPs located on the Y chromosome have a specific utility as forensic tools, and based on this fact, we have designed a strategy that allows us to identify the most frequent haplogroups in European populations. We selected 29 markers among the 245 binary polymorphisms described in the Y-Chromosome Consortium tree. The whole set was grouped into four multiplexes in a hierarchical way, allowing us to determine the final haplogroup using only one or two multiplexes. In this way, we only type in the best-case nine SNPs, and in the worst possible combination 17 SNPs, to define the haplogroup. The selected strategy to type the SNPs was a single-base extension method using the SNaPshot multiplex kit from Applied Biosystems, and detailed practical procedures are described here. With this hierarchical strategy adapted for European populations the massive typing of SNPs was avoided, and therefore the time and money involved in the study was also reduced.

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

    PubMed

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

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

  19. Graphical Methods for Reducing, Visualizing and Analyzing Large Data Sets Using Hierarchical Terminologies

    PubMed Central

    Jing, Xia; Cimino, James J.

    2011-01-01

    Objective: To explore new graphical methods for reducing and analyzing large data sets in which the data are coded with a hierarchical terminology. Methods: We use a hierarchical terminology to organize a data set and display it in a graph. We reduce the size and complexity of the data set by considering the terminological structure and the data set itself (using a variety of thresholds) as well as contributions of child level nodes to parent level nodes. Results: We found that our methods can reduce large data sets to manageable size and highlight the differences among graphs. The thresholds used as filters to reduce the data set can be used alone or in combination. We applied our methods to two data sets containing information about how nurses and physicians query online knowledge resources. The reduced graphs make the differences between the two groups readily apparent. Conclusions: This is a new approach to reduce size and complexity of large data sets and to simplify visualization. This approach can be applied to any data sets that are coded with hierarchical terminologies. PMID:22195119

  20. Structural group-based auditing of missing hierarchical relationships in UMLS.

    PubMed

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

    2009-06-01

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

  1. Structural Group-based Auditing of Missing Hierarchical Relationships in UMLS

    PubMed Central

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

    2009-01-01

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

  2. 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

  3. 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.

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Kolekar, M. H.; Sengupta, S.

    2005-07-01

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

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

    PubMed Central

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

    2014-01-01

    Motivation: The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Method: Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. Results: The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Availability and implementation: Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/. Contact: lin.yang@uky.edu PMID:24215030

  8. 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…

  9. 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.

  10. A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening.

    PubMed

    Soares, Felipe; Becker, Karin; Anzanello, Michel J

    2017-09-19

    Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effective diagnosis methods are required. Blood fluorescence spectroscopy provides rich information that can be used for cancer identification. The main challenges in analyzing blood fluorescence data for CRC classification are related to its high dimensionality and inherent variability, especially when analyzing a small number of samples. In this paper, we present a hierarchical classification method based on plasma fluorescence to identify not only CRC, but also adenomas and other non-malignant colorectal findings that may require further medical investigation. A feature selection algorithm is proposed to deal with the high dimensionality and select discriminant fluorescence wavelengths. These are used to train a binary support vector machine (SVM) in the first level to identify the CRC samples. The remaining samples are then presented to a one-class SVM trained on healthy subjects to detect deviant samples, and thus non-malignant findings. This hierarchical design, together with the one class-SVM, aims to reduce the effects of small samples and high variability. Using a dataset analyzed in previous studies comprised of 12,341 wavelengths, we achieved much superior results. Sensitivity and specificity are 0.87 and 0.95 for CRC detection, and 0.60 and 0.79 for non-malignant findings, respectively. Compared to related work, the proposed method presented a better accuracy, required fewer features, and provides a unified approach that expands CRC detection to non-malignant findings. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Flexible Transparent Supercapacitors Based on Hierarchical Nanocomposite Films.

    PubMed

    Chen, Fanhong; Wan, Pengbo; Xu, Haijun; Sun, Xiaoming

    2017-05-31

    Flexible transparent electronic devices have recently gained immense popularity in smart wearable electronics and touch screen devices, which accelerates the development of the portable power sources with reliable flexibility, robust transparency and integration to couple these electronic devices. For potentially coupled as energy storage modules in various flexible, transparent and portable electronics, the flexible transparent supercapacitors are developed and assembled from hierarchical nanocomposite films of reduced graphene oxide (rGO) and aligned polyaniline (PANI) nanoarrays upon their synergistic advantages. The nanocomposite films are fabricated from in situ PANI nanoarrays preparation in a blended solution of aniline monomers and rGO onto the flexible, transparent, and stably conducting film (FTCF) substrate, which is obtained by coating silver nanowires (Ag NWs) layer with Meyer rod and then coating of rGO layer on polyethylene terephthalate (PET) substrate. Optimization of the transparency, the specific capacitance, and the flexibility resulted in the obtained all-solid state nanocomposite supercapacitors exhibiting enhanced capacitance performance, good cycling stability, excellent flexibility, and superior transparency. It provides promising application prospects for exploiting flexible, low-cost, transparent, and high-performance energy storage devices to be coupled into various flexible, transparent, and wearable electronic devices.

  12. 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).

  13. Influences on influenza transmission within terminal based on hierarchical structure of personal contact network.

    PubMed

    Shao, Quan; Jia, Meng

    2015-03-18

    Since the outbreak of pandemics, influenza has caused extensive attention in the field of public health. It is actually hard to distinguish what is the most effective method to control the influenza transmission within airport terminal. The purpose of this study was to quantitatively evaluate the influences of passenger source, immunity difference and social relation structure on the influenza transmission in terminal. A method combining hierarchical structure of personal contact network with agent-based SEIR model was proposed to analyze the characteristics of influenza diffusion within terminal. Based on the spatial distance between individuals, the hierarchical structure of personal contact network was defined to construct a complex relationship of passengers in the real world. Moreover, the agent-based SEIR model was improved by considering the individual level of influenza spread characteristics. To evaluate the method, this process was fused in simulation based on the constructed personal contact network. In the terminal we investigated, personal contact network was defined by following four layers: social relation structure, procedure partition, procedure area, and the whole terminal. With the growing of layer, the degree distribution curves move right. The value of degree distribution p(k) reached a peak at a specific value, and then back down. Besides, with the increase of layer α, the clustering coefficients presented a tendency to exponential decay. Based on the influenza transmission experiments, the main infected areas were concluded when considering different factors. Moreover, partition of passenger sources was found to impact a lot in departure, while social relation structure imposed a great influence in arrival. Besides, immunity difference exerted no obvious effect on the spread of influenza in the transmission process both in departure and arrival. The proposed method is efficient to reproduce the evolution process of influenza transmission

  14. High- and low-level hierarchical classification algorithm based on source separation process

    NASA Astrophysics Data System (ADS)

    Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

    2016-10-01

    High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance

  15. Hierarchical Segmentation Using Tree-Based Shape Spaces.

    PubMed

    Xu, Yongchao; Carlinet, Edwin; Geraud, Thierry; Najman, Laurent

    2017-03-01

    Current trends in image segmentation are to compute a hierarchy of image segmentations from fine to coarse. A classical approach to obtain a single meaningful image partition from a given hierarchy is to cut it in an optimal way, following the seminal approach of the scale-set theory. While interesting in many cases, the resulting segmentation, being a non-horizontal cut, is limited by the structure of the hierarchy. In this paper, we propose a novel approach that acts by transforming an input hierarchy into a new saliency map. It relies on the notion of shape space: a graph representation of a set of regions extracted from the image. Each region is characterized with an attribute describing it. We weigh the boundaries of a subset of meaningful regions (local minima) in the shape space by extinction values based on the attribute. This extinction-based saliency map represents a new hierarchy of segmentations highlighting regions having some specific characteristics. Each threshold of this map represents a segmentation which is generally different from any cut of the original hierarchy. This new approach thus enlarges the set of possible partition results that can be extracted from a given hierarchy. Qualitative and quantitative illustrations demonstrate the usefulness of the proposed method.

  16. Hierarchical Pore Development by Plasma Etching of Zr-Based Metal-Organic Frameworks.

    PubMed

    DeCoste, Jared B; Rossin, Joseph A; Peterson, Gregory W

    2015-12-07

    The typically stable Zr-based metal-organic frameworks (MOFs) UiO-66 and UiO-66-NH2 were treated with tetrafluoromethane (CF4 ) and hexafluoroethane (C2 F6 ) plasmas. Through interactions between fluoride radicals from the perfluoroalkane plasma and the zirconium-oxygen bonds of the MOF, the resulting materials showed the development of mesoporosity, creating a hierarchical pore structure. It is anticipated that this strategy can be used as a post-synthetic technique for developing hierarchical networks in a variety of MOFs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Method of forecasting energy center positions of laser beam spot images using a parallel hierarchical network for optical communication systems

    NASA Astrophysics Data System (ADS)

    Timchenko, Leonid I.; Kokryatskaya, Natalia I.; Melnikov, Viktor V.; Kosenko, Galina L.

    2013-05-01

    A forecasting method, based on the parallel-hierarchical (PH) network and hyperbolic smoothing of empirical data, is presented in this paper. Preceding values of the time series, hyperbolic smoothing, and PH network data are used for forecasting. To determine a position of the next route fragment in relation to X and Y axes, hyperbola parameters are sent to the route parameter forecasting system. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the PH network. An average prediction error is 0.55% for the developed method and 1.62% for neural networks. That is why, due to the use of the PH network and hyperbolic smoothing, the developed method is more efficient for real-time systems than traditional neural networks in forecasting energy center positions of laser beam spot images for optical communication systems.

  18. Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

    PubMed

    Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

    2017-07-01

    Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

  19. Risk Assessment and Hierarchical Risk Management of Enterprises in Chemical Industrial Parks Based on Catastrophe Theory

    PubMed Central

    Chen, Yu; Song, Guobao; Yang, Fenglin; Zhang, Shushen; Zhang, Yun; Liu, Zhenyu

    2012-01-01

    According to risk systems theory and the characteristics of the chemical industry, an index system was established for risk assessment of enterprises in chemical industrial parks (CIPs) based on the inherent risk of the source, effectiveness of the prevention and control mechanism, and vulnerability of the receptor. A comprehensive risk assessment method based on catastrophe theory was then proposed and used to analyze the risk levels of ten major chemical enterprises in the Songmu Island CIP, China. According to the principle of equal distribution function, the chemical enterprise risk level was divided into the following five levels: 1.0 (very safe), 0.8 (safe), 0.6 (generally recognized as safe, GRAS), 0.4 (unsafe), 0.2 (very unsafe). The results revealed five enterprises (50%) with an unsafe risk level, and another five enterprises (50%) at the generally recognized as safe risk level. This method solves the multi-objective evaluation and decision-making problem. Additionally, this method involves simple calculations and provides an effective technique for risk assessment and hierarchical risk management of enterprises in CIPs. PMID:23208298

  20. Risk assessment and hierarchical risk management of enterprises in chemical industrial parks based on catastrophe theory.

    PubMed

    Chen, Yu; Song, Guobao; Yang, Fenglin; Zhang, Shushen; Zhang, Yun; Liu, Zhenyu

    2012-12-03

    According to risk systems theory and the characteristics of the chemical industry, an index system was established for risk assessment of enterprises in chemical industrial parks (CIPs) based on the inherent risk of the source, effectiveness of the prevention and control mechanism, and vulnerability of the receptor. A comprehensive risk assessment method based on catastrophe theory was then proposed and used to analyze the risk levels of ten major chemical enterprises in the Songmu Island CIP, China. According to the principle of equal distribution function, the chemical enterprise risk level was divided into the following five levels: 1.0 (very safe), 0.8 (safe), 0.6 (generally recognized as safe, GRAS), 0.4 (unsafe), 0.2 (very unsafe). The results revealed five enterprises (50%) with an unsafe risk level, and another five enterprises (50%) at the generally recognized as safe risk level. This method solves the multi-objective evaluation and decision-making problem. Additionally, this method involves simple calculations and provides an effective technique for risk assessment and hierarchical risk management of enterprises in CIPs.

  1. Specification of hierarchical-model-based fast quarter-pixel motion estimation

    NASA Astrophysics Data System (ADS)

    Cho, Junsang; Suh, Jung W.; Jeon, Gwanggil; Jeong, Jechang

    2010-06-01

    We propose a robust and fast quarter-pixel motion estimation algorithm. This algorithm is an advanced version of the previously proposed model-based quarter-pixel motion estimation (MBQME). MBQME has many advantages in computational complexity, running speed, and hardware implementations. But it has the problem that it does not find the quarter-pixel positions that locate beyond the half-pixel positions. That is one of limitations of model-based motion estimation methods, and it leads to both peak-SNR degradation and bit-rate increase. To solve this problem, we propose a hierarchical mathematical model with minimum interpolations. Through this model, we can determine a motion vector at every quarter-pixel point, which is perfectly compatible with the quarter-pixel motion estimation method within international video coding standards such as MPEG-4 and H.264/AVC. The simulation results show that the proposed method yields almost the same or even better peak-SNR performance than that of full-search quarter-pixel motion estimation, with much lower computational complexity.

  2. 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.

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

    ERIC Educational Resources Information Center

    Bacon, Jessica; Ferri, Beth

    2013-01-01

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

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

    ERIC Educational Resources Information Center

    Bacon, Jessica; Ferri, Beth

    2013-01-01

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

  5. 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

  6. 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.

  7. 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.

  8. 3D hierarchical interface-enriched finite element method: Implementation and applications

    NASA Astrophysics Data System (ADS)

    Soghrati, Soheil; Ahmadian, Hossein

    2015-10-01

    A hierarchical interface-enriched finite element method (HIFEM) is proposed for the mesh-independent treatment of 3D problems with intricate morphologies. The HIFEM implements a recursive algorithm for creating enrichment functions that capture gradient discontinuities in nonconforming finite elements cut by arbitrary number and configuration of materials interfaces. The method enables the mesh-independent simulation of multiphase problems with materials interfaces that are in close proximity or contact while providing a straightforward general approach for evaluating the enrichments. In this manuscript, we present a detailed discussion on the implementation issues and required computational geometry considerations associated with the HIFEM approximation of thermal and mechanical responses of 3D problems. A convergence study is provided to investigate the accuracy and convergence rate of the HIFEM and compare them with standard FEM benchmark solutions. We will also demonstrate the application of this mesh-independent method for simulating the thermal and mechanical responses of two composite materials systems with complex microstructures.

  9. 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.

  10. A low latency and high efficient three-dimension Network-on-Chip based on hierarchical structure

    NASA Astrophysics Data System (ADS)

    Zhu, Chen; Zhao, Huatao; Chen, Tinghuan; Zhu, Tianbo

    2017-07-01

    Currently, the majority of the Network-on-Chip (NoC) researches are based on 2D algorithm or simple 3D structure. However, the congestion and faulty links in the topology can increase the latency and power consumption. In this paper, the authors try to build a novel 3D topology based on hierarchical structure and TSV links which can reduce the latency and power consumption by decreasing the hops during the process of passing the packets. We employ the C++ tool to test our method, and the results show that the performance can be improved about 21%-36% in throughput, also 3%-11% in latency.

  11. 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.

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

    PubMed

    Kwak, Wonshik; Hwang, Woonbong

    2016-02-05

    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.

  13. 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.

  14. Hierarchical content-based image retrieval by dynamic indexing and guided search

    NASA Astrophysics Data System (ADS)

    You, Jane; Cheung, King H.; Liu, James; Guo, Linong

    2003-12-01

    This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

  15. 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.

  16. Trust-based Hierarchical Role Enhanced Policy for Adaptive Availability of Confidential Information

    DTIC Science & Technology

    2009-03-31

    Trust-based Hierarchical Role Enhanced Policy for Adaptive Availability of Confidential Information 5b. GRANT NUMBER FA9550-04-1-0429 5c...techniques that preserve confidentiality and integrity of information in computer systems while providing dynamic trust-based updates so that information is...of Confidential Information Grant Number: FA9550-04-1-0429 Principal Investigator: Dr. Brajendra Panda Program Manager: Dr. Robert L. Herklotz

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

    PubMed

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

    2017-02-01

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

  18. Array-based, parallel hierarchical mesh refinement algorithms for unstructured meshes

    DOE PAGES

    Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; ...

    2016-08-18

    In this paper, we describe an array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements (by loading smaller meshes and in memory refinement). We also describe a high-order boundary reconstruction capability that can be used tomore » project the new points after refinement using high-order approximations instead of linear projection in order to minimize and provide more control on geometrical errors introduced by curved boundaries.The capability is developed under the parallel unstructured mesh framework "Mesh Oriented dAtaBase" (MOAB Tautges et al. (2004)). We describe the underlying data structures and algorithms to generate such hierarchies in parallel and present numerical results for computational efficiency and effect on mesh quality. Furthermore, we also present results to demonstrate the applicability of the developed capability to study convergence properties of different point projection schemes for various mesh hierarchies and to a multigrid finite-element solver for elliptic problems.« less

  19. Array-based, parallel hierarchical mesh refinement algorithms for unstructured meshes

    SciTech Connect

    Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; Mahadevan, Vijay; Jiao, Xiangmin

    2016-08-18

    In this paper, we describe an array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements (by loading smaller meshes and in memory refinement). We also describe a high-order boundary reconstruction capability that can be used to project the new points after refinement using high-order approximations instead of linear projection in order to minimize and provide more control on geometrical errors introduced by curved boundaries.The capability is developed under the parallel unstructured mesh framework "Mesh Oriented dAtaBase" (MOAB Tautges et al. (2004)). We describe the underlying data structures and algorithms to generate such hierarchies in parallel and present numerical results for computational efficiency and effect on mesh quality. Furthermore, we also present results to demonstrate the applicability of the developed capability to study convergence properties of different point projection schemes for various mesh hierarchies and to a multigrid finite-element solver for elliptic problems.

  20. 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

  1. 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.

  2. 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

  3. 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

  4. Bayesian hierarchical structured variable selection methods with application to MIP studies in breast cancer.

    PubMed

    Zhang, Lin; Baladandayuthapani, Veerabhadran; Mallick, Bani K; Manyam, Ganiraju C; Thompson, Patricia A; Bondy, Melissa L; Do, Kim-Anh

    2014-08-01

    The analysis of alterations that may occur in nature when segments of chromosomes are copied (known as copy number alterations) has been a focus of research to identify genetic markers of cancer. One high-throughput technique recently adopted is the use of molecular inversion probes (MIPs) to measure probe copy number changes. The resulting data consist of high-dimensional copy number profiles that can be used to ascertain probe-specific copy number alterations in correlative studies with patient outcomes to guide risk stratification and future treatment. We propose a novel Bayesian variable selection method, the hierarchical structured variable selection (HSVS) method, which accounts for the natural gene and probe-within-gene architecture to identify important genes and probes associated with clinically relevant outcomes. We propose the HSVS model for grouped variable selection, where simultaneous selection of both groups and within-group variables is of interest. The HSVS model utilizes a discrete mixture prior distribution for group selection and group-specific Bayesian lasso hierarchies for variable selection within groups. We provide methods for accounting for serial correlations within groups that incorporate Bayesian fused lasso methods for within-group selection. Through simulations we establish that our method results in lower model errors than other methods when a natural grouping structure exists. We apply our method to an MIP study of breast cancer and show that it identifies genes and probes that are significantly associated with clinically relevant subtypes of breast cancer.

  5. Bayesian hierarchical structured variable selection methods with application to molecular inversion probe studies in breast cancer

    PubMed Central

    Zhang, Lin; Baladandayuthapani, Veerabhadran; Mallick, Bani K.; Manyam, Ganiraju C.; Thompson, Patricia A.; Bondy, Melissa L.; Do, Kim-Anh

    2015-01-01

    Summary The analysis of alterations that may occur in nature when segments of chromosomes are copied (known as copy number alterations) has been a focus of research to identify genetic markers of cancer. One high-throughput technique recently adopted is the use of molecular inversion probes (MIPs) to measure probe copy number changes. The resulting data consist of high-dimensional copy number profiles that can be used to ascertain probe-specific copy number alterations in correlative studies with patient outcomes to guide risk stratification and future treatment. We propose a novel Bayesian variable selection method, the hierarchical structured variable selection (HSVS) method, which accounts for the natural gene and probe-within-gene architecture to identify important genes and probes associated with clinically relevant outcomes. We propose the HSVS model for grouped variable selection, where simultaneous selection of both groups and within-group variables is of interest. The HSVS model utilizes a discrete mixture prior distribution for group selection and group-specific Bayesian lasso hierarchies for variable selection within groups. We provide methods for accounting for serial correlations within groups that incorporate Bayesian fused lasso methods for within-group selection. Through simulations we establish that our method results in lower model errors than other methods when a natural grouping structure exists. We apply our method to an MIP study of breast cancer and show that it identifies genes and probes that are significantly associated with clinically relevant subtypes of breast cancer. PMID:25705056

  6. Evolution of platinum hierarchical microstructure amine - Assisted growth via solvothermal method

    NASA Astrophysics Data System (ADS)

    Ooi, Mahayatun Dayana Johan; Aziz, Azlan Abdul

    2015-04-01

    Here we studied the formation of Platinum hierarchical microstructure by varying the synthesis time using amine assisted growth via solvothermal method. A small cluster of particles was produced at a shorter synthesis time (5h) while fully grown flower-like microstructure were formed at 9h of reaction. The synthesized Pt particles exhibit high absorption peak at 230 nm corresponding to Pt absorption peak. The catalytic property of the synthesized Pt is greatly influenced by its geometrical shape. The fully grown flower-like particles exhibit large electrochemical surface area (4.88 cm-2 g-1) and catalytic stability at a longer period, which can serve as a potential catalyst for electro-oxidation of formic acid.

  7. A hierarchical method for removal of baseline drift from biomedical signals: application in ECG analysis.

    PubMed

    Luo, Yurong; Hargraves, Rosalyn H; Belle, Ashwin; Bai, Ou; Qi, Xuguang; Ward, Kevin R; Pfaffenberger, Michael Paul; Najarian, Kayvan

    2013-01-01

    Noise can compromise the extraction of some fundamental and important features from biomedical signals and hence prohibit accurate analysis of these signals. Baseline wander in electrocardiogram (ECG) signals is one such example, which can be caused by factors such as respiration, variations in electrode impedance, and excessive body movements. Unless baseline wander is effectively removed, the accuracy of any feature extracted from the ECG, such as timing and duration of the ST-segment, is compromised. This paper approaches this filtering task from a novel standpoint by assuming that the ECG baseline wander comes from an independent and unknown source. The technique utilizes a hierarchical method including a blind source separation (BSS) step, in particular independent component analysis, to eliminate the effect of the baseline wander. We examine the specifics of the components causing the baseline wander and the factors that affect the separation process. Experimental results reveal the superiority of the proposed algorithm in removing the baseline wander.

  8. Use of Hierarchical Linear Modeling and Curriculum-Based Measurement for Assessing Academic Growth and Instructional Factors for Students with Learning Difficulties

    ERIC Educational Resources Information Center

    Shin, Jongho; Espin, Christine A.; Deno, Stanley L.; McConnell, Scott

    2004-01-01

    The main purpose of this paper is to demonstrate how to apply the Hierarchical Linear Modeling (HLM) technique to multi-wave Curriculum-Based Measurement (CBM) measures in modeling academic growth and assessing its relations to student-and instruction-related variables. HLM has advantages over other statistical methods (e.g., repeated measures…

  9. 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.

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

    PubMed Central

    Lee, Jungsoo; Lim, Yongsub; Bae, Doo-Hwan; Park, Haesun; Kim, Dae-Shik; Jung, Kyomin

    2017-01-01

    Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches. PMID:28545042

  11. 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

  12. Inferring a district-based hierarchical structure of social contacts from census data.

    PubMed

    Yu, Z; Liu, J; Zhu, X

    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.

  13. An assembly process model based on object-oriented hierarchical time Petri Nets

    NASA Astrophysics Data System (ADS)

    Wang, Jiapeng; Liu, Shaoli; Liu, Jianhua; Du, Zenghui

    2017-04-01

    In order to improve the versatility, accuracy and integrity of the assembly process model of complex products, an assembly process model based on object-oriented hierarchical time Petri Nets is presented. A complete assembly process information model including assembly resources, assembly inspection, time, structure and flexible parts is established, and this model describes the static and dynamic data involved in the assembly process. Through the analysis of three-dimensional assembly process information, the assembly information is hierarchically divided from the whole, the local to the details and the subnet model of different levels of object-oriented Petri Nets is established. The communication problem between Petri subnets is solved by using message database, and it reduces the complexity of system modeling effectively. Finally, the modeling process is presented, and a five layer Petri Nets model is established based on the hoisting process of the engine compartment of a wheeled armored vehicle.

  14. 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.

  15. Analysis of the genetic divergence of soybean lines through hierarchical and Tocher optimization methods.

    PubMed

    Cantelli, D A V; Hamawaki, O T; Rocha, M R; Nogueira, A P O; Hamawaki, R L; Sousa, L B; Hamawaki, C D L

    2016-10-05

    This study aimed to evaluate the clustering pattern consistency of soybean (Glycine max) lines, using seven different clustering methods. Our aim was to evaluate the best method for the identification of promising genotypes to obtain segregating populations. We used 51 generations F5 and F6 soybean lines originating from different hybridizations and backcrosses obtained from the soybean breeding program of Universidade Federal de Uberlândia in addition to three controls (Emgopa 302, BRSGO Luziânia, and MG/BR46 Conquista). We evaluated the following agronomic traits: number of days to flowering, number of days to maturity, height of the plant at maturity, insertion height of the first pod, grain yield, and weight of 100 seeds. The data was submitted to analyses of variance followed by average Euclidean distance matrix estimation used as measure of dissimilarity. Subsequently, clusters were formed using the Tocher method and dendrograms were constructed using the hierarchical methods simple connection (nearest neighbor), complete connection (most distant neighbor), Ward, median, average within cluster connection. The nearest neighbor method presented the largest number of genotypes in group I and showed the greatest similarity with the Tocher optimization method. The joint use of these two methodologies allows for differentiation of the most genetically distant genotypes that may constitute the optimal parents in a breeding program.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. A Hierarchical Optimization Algorithm Based on GPU for Real-Time 3D Reconstruction

    NASA Astrophysics Data System (ADS)

    Lin, Jin-hua; Wang, Lu; Wang, Yan-jie

    2017-06-01

    In machine vision sensing system, it is important to realize high-quality real-time 3D reconstruction in large-scale scene. The recent online approach performed well, but scaling up the reconstruction, it causes pose estimation drift, resulting in the cumulative error, usually requiring a large number of off-line operation to completely correct the error, reducing the reconstruction performance. In order to optimize the traditional volume fusion method and improve the old frame-to-frame pose estimation strategy, this paper presents a real-time CPU to Graphic Processing Unit reconstruction system. Based on a robust camera pose estimation strategy, the algorithm fuses all the RGB-D input values into an effective hierarchical optimization framework, and optimizes each frame according to the global camera attitude, eliminating the serious dependence on the tracking timeliness and continuously tracking globally optimized frames. The system estimates the global optimization of gestures (bundling) in real-time, supports for robust tracking recovery (re-positioning), and re-estimation of large-scale 3D scenes to ensure global consistency. It uses a set of sparse corresponding features, geometric and ray matching functions in one of the parallel optimization systems. The experimental results show that the average reconstruction time is 415 ms per frame, the ICP pose is estimated 20 times in 100.0 ms. For large scale 3D reconstruction scene, the system performs well in online reconstruction area, keeping the reconstruction accuracy at the same time.

  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. Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

    PubMed Central

    2012-01-01

    Background The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches. Results Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day. Conclusions This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain

  3. Web page classification based on a binary hierarchical classifier for multi-class support vector machines

    NASA Astrophysics Data System (ADS)

    Li, Cunhe; Wang, Guangqing

    2013-03-01

    Web page classification is one of the essential techniques for Web mining. This paper proposes a binary hierarchical classifier for multi-class support vector machines for web page classification. This method applies truncated singular value decomposition on the training data that reduces its dimension and the noise data. After the truncated singular value decomposition on the training data, it uses the improved k-means algorithm design the binary hierarchical structure, the improved k-means algorithm makes the separability of one macro-class is the smallest, makes the separability of two macro-classes is the largest. The result of experiment performed on the training datasets shows that this algorithm can enhance precision of web page classification.

  4. Hierarchical cluster analysis of ignitable liquids based on the total ion spectrum.

    PubMed

    Waddell, Erin E; Frisch-Daiello, Jessica L; Williams, Mary R; Sigman, Michael E

    2014-09-01

    Gas chromatography-mass spectrometry (GC-MS) data of ignitable liquids in the Ignitable Liquids Reference Collection (ILRC) database were processed to obtain 445 total ion spectra (TIS), that is, average mass spectra across the chromatographic profile. Hierarchical cluster analysis, an unsupervised learning technique, was applied to find features useful for classification of ignitable liquids. A combination of the correlation distance and average linkage was utilized for grouping ignitable liquids with similar chemical composition. This study evaluated whether hierarchical cluster analysis of the TIS would cluster together ignitable liquids of the same ASTM class assignment, as designated in the ILRC database. The ignitable liquids clustered based on their chemical composition, and the ignitable liquids within each cluster were predominantly from one ASTM E1618-11 class. These results reinforce use of the TIS as a tool to aid in forensic fire debris analysis. © 2014 American Academy of Forensic Sciences.

  5. 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.

  6. 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.

  7. Hierarchical layered and semantic-based image segmentation using ergodicity map

    NASA Astrophysics Data System (ADS)

    Yadegar, Jacob; Liu, Xiaoqing

    2010-04-01

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

  8. 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.

  9. 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

  10. Fabrication of copper sulfide hierarchical architectures with tunable morphologies and sizes by microwave-biomolecular assistance method.

    PubMed

    Wang, Zeyun; Lou, Wenjing; Wang, Xiaobo; Liu, Weimin

    2011-03-01

    A facile microwave-biomolecular assistance method has been used to synthesize copper sulfide nanomaterials. In this process, the histidine as the directing and assembling agent plays an important role in the formation of the different hierarchical architectures. The morphologies and the sizes of the products can be tuned by adjusting the molar ratio of Cu2+/histidine and Cu2+/thiourea. The effect of other experiment parameters such as the reaction temperature, the power of microwave irradiation, and reaction time on the morphology and the size has been also discussed in detail. The possible reaction and growth mechanisms of the formation different hierarchical architectures are also discussed. In addition, the optical properties of these copper sulfides nanomaterials were investigated and the photocatalytic activity of different hierarchical architectures has been tested by the degradation of methyl orange (MO) under UV-light irradiation.

  11. Assessment of Preconditioner for a USM3D Hierarchical Adaptive Nonlinear Method (HANIM) (Invited)

    NASA Technical Reports Server (NTRS)

    Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frink, Neal T.

    2016-01-01

    Enhancements to the previously reported mixed-element USM3D Hierarchical Adaptive Nonlinear Iteration Method (HANIM) framework have been made to further improve robustness, efficiency, and accuracy of computational fluid dynamic simulations. The key enhancements include a multi-color line-implicit preconditioner, a discretely consistent symmetry boundary condition, and a line-mapping method for the turbulence source term discretization. The USM3D iterative convergence for the turbulent flows is assessed on four configurations. The configurations include a two-dimensional (2D) bump-in-channel, the 2D NACA 0012 airfoil, a three-dimensional (3D) bump-in-channel, and a 3D hemisphere cylinder. The Reynolds Averaged Navier Stokes (RANS) solutions have been obtained using a Spalart-Allmaras turbulence model and families of uniformly refined nested grids. Two types of HANIM solutions using line- and point-implicit preconditioners have been computed. Additional solutions using the point-implicit preconditioner alone (PA) method that broadly represents the baseline solver technology have also been computed. The line-implicit HANIM shows superior iterative convergence in most cases with progressively increasing benefits on finer grids.

  12. Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

    PubMed Central

    Sherrill, Delsey M; Moy, Marilyn L; Reilly, John J; Bonato, Paolo

    2005-01-01

    Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD) undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical clustering methods are relevant

  13. Bayesian Hierarchical Random Intercept Model Based on Three Parameter Gamma Distribution

    NASA Astrophysics Data System (ADS)

    Wirawati, Ika; Iriawan, Nur; Irhamah

    2017-06-01

    Hierarchical data structures are common throughout many areas of research. Beforehand, the existence of this type of data was less noticed in the analysis. The appropriate statistical analysis to handle this type of data is the hierarchical linear model (HLM). This article will focus only on random intercept model (RIM), as a subclass of HLM. This model assumes that the intercept of models in the lowest level are varied among those models, and their slopes are fixed. The differences of intercepts were suspected affected by some variables in the upper level. These intercepts, therefore, are regressed against those upper level variables as predictors. The purpose of this paper would demonstrate a proven work of the proposed two level RIM of the modeling on per capita household expenditure in Maluku Utara, which has five characteristics in the first level and three characteristics of districts/cities in the second level. The per capita household expenditure data in the first level were captured by the three parameters Gamma distribution. The model, therefore, would be more complex due to interaction of many parameters for representing the hierarchical structure and distribution pattern of the data. To simplify the estimation processes of parameters, the computational Bayesian method couple with Markov Chain Monte Carlo (MCMC) algorithm and its Gibbs Sampling are employed.

  14. Hierarchical starch-based fibrous scaffold for bone tissue engineering applications.

    PubMed

    Martins, Albino; Chung, Sangwon; Pedro, Adriano J; Sousa, Rui A; Marques, Alexandra P; Reis, Rui L; Neves, Nuno M

    2009-01-01

    Fibrous structures mimicking the morphology of the natural extracellular matrix are considered promising scaffolds for tissue engineering. This work aims to develop a novel hierarchical starch-based scaffold. Such scaffolds were obtained by a combination of starch-polycaprolactone micro- and polycaprolactone nano-motifs, respectively produced by rapid prototyping (RP) and electrospinning techniques. Scanning electron microscopy (SEM) and micro-computed tomography analysis showed the successful fabrication of a multilayer scaffold composed of parallel aligned microfibres in a grid-like arrangement, intercalated by a mesh-like structure with randomly distributed nanofibres (NFM). Human osteoblast-like cells were dynamically seeded on the scaffolds, using spinner flasks, and cultured for 7 days under static conditions. SEM analysis showed predominant cell attachment and spreading on the nanofibre meshes, which enhanced cell retention at the bulk of the composed/hierarchical scaffolds. A significant increment in cell proliferation and osteoblastic activity, assessed by alkaline phosphatase quantification, was observed on the hierarchical fibrous scaffolds. These results support our hypothesis that the integration of nanoscale fibres into 3D rapid prototype scaffolds substantially improves their biological performance in bone tissue-engineering strategies.

  15. 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.

  16. 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.

  17. Transition metal ions regulated oxygen evolution reaction performance of Ni-based hydroxides hierarchical nanoarrays

    PubMed Central

    Zhou, Tingting; Cao, Zhen; Zhang, Pan; Ma, Houyi; Gao, Zhen; Wang, Heng; Lu, Yue; He, Jia; Zhao, Yunfeng

    2017-01-01

    Nickel-based hydroxide hierarchical nanoarrays (NiyM(OH)x HNAs M = Fe or Zn) are doped with non-noble transition metals to create nanostructures and regulate their activities for the oxygen evolution reaction. Catalytic performance in these materials depends on their chemical composition and the presence of nanostructures. These novel hierarchical nanostructures contain small secondary nanosheets that are grown on the primary nanowire arrays, providing a higher surface area and more efficient mass transport for electrochemical reactions. The activities of the NiyM(OH)x HNAs for the oxygen evolution reaction (OER) followed the order of Ni2.2Fe(OH)x > Ni(OH)2 > Ni2.1Zn(OH)x, and these trends are supported by density functional theory (DFT) calculations. The Fe-doped nickel hydroxide hierarchical nanoarrays (Ni2.2Fe(OH)x HNAs), which had an appropriate elemental composition and hierarchical nanostructures, achieve the lowest onset overpotential of 234 mV and the smallest Tafel slope of 64.3 mV dec−1. The specific activity, which is normalized to the Brunauer–Emmett–Teller (BET) surface area of the catalyst, of the Ni2.2Fe(OH)x HNAs is 1.15 mA cm−2BET at an overpotential of 350 mV. This is ~4-times higher than that of Ni(OH)2. These values are also superior to those of a commercial IrOx electrocatalyst. PMID:28383065

  18. Transition metal ions regulated oxygen evolution reaction performance of Ni-based hydroxides hierarchical nanoarrays

    NASA Astrophysics Data System (ADS)

    Zhou, Tingting; Cao, Zhen; Zhang, Pan; Ma, Houyi; Gao, Zhen; Wang, Heng; Lu, Yue; He, Jia; Zhao, Yunfeng

    2017-04-01

    Nickel-based hydroxide hierarchical nanoarrays (NiyM(OH)x HNAs M = Fe or Zn) are doped with non-noble transition metals to create nanostructures and regulate their activities for the oxygen evolution reaction. Catalytic performance in these materials depends on their chemical composition and the presence of nanostructures. These novel hierarchical nanostructures contain small secondary nanosheets that are grown on the primary nanowire arrays, providing a higher surface area and more efficient mass transport for electrochemical reactions. The activities of the NiyM(OH)x HNAs for the oxygen evolution reaction (OER) followed the order of Ni2.2Fe(OH)x > Ni(OH)2 > Ni2.1Zn(OH)x, and these trends are supported by density functional theory (DFT) calculations. The Fe-doped nickel hydroxide hierarchical nanoarrays (Ni2.2Fe(OH)x HNAs), which had an appropriate elemental composition and hierarchical nanostructures, achieve the lowest onset overpotential of 234 mV and the smallest Tafel slope of 64.3 mV dec-1. The specific activity, which is normalized to the Brunauer-Emmett-Teller (BET) surface area of the catalyst, of the Ni2.2Fe(OH)x HNAs is 1.15 mA cm-2BET at an overpotential of 350 mV. This is ~4-times higher than that of Ni(OH)2. These values are also superior to those of a commercial IrOx electrocatalyst.

  19. A new hierarchical parallelization scheme: generalized distributed data interface (GDDI), and an application to the fragment molecular orbital method (FMO).

    PubMed

    Fedorov, Dmitri G; Olson, Ryan M; Kitaura, Kazuo; Gordon, Mark S; Koseki, Shiro

    2004-04-30

    A two-level hierarchical scheme, generalized distributed data interface (GDDI), implemented into GAMESS is presented. Parallelization is accomplished first at the upper level by assigning computational tasks to groups. Then each group does parallelization at the lower level, by dividing its task into smaller work loads. The types of computations that can be used with this scheme are limited to those for which nearly independent tasks and subtasks can be assigned. Typical examples implemented, tested, and analyzed in this work are numeric derivatives and the fragment molecular orbital method (FMO) that is used to compute large molecules quantum mechanically by dividing them into fragments. Numeric derivatives can be used for algorithms based on them, such as geometry optimizations, saddle-point searches, frequency analyses, etc. This new hierarchical scheme is found to be a flexible tool easily utilizing network topology and delivering excellent performance even on slow networks. In one of the typical tests, on 16 nodes the scalability of GDDI is 1.7 times better than that of the standard parallelization scheme DDI and on 128 nodes GDDI is 93 times faster than DDI (on a multihub Fast Ethernet network). FMO delivered scalability of 80-90% on 128 nodes, depending on the molecular system (water clusters and a protein). A numerical gradient calculation for a water cluster achieved a scalability of 70% on 128 nodes. It is expected that GDDI will become a preferred tool on massively parallel computers for appropriate computational tasks. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 872-880, 2004

  20. An Adaptive Algebra Test: A Testlet-Based, Hierarchically-Structured Test with Validity-Based Scoring. Technical Report No. 90-92.

    ERIC Educational Resources Information Center

    Wainer, Howard; And Others

    The initial development of a testlet-based algebra test was previously reported (Wainer and Lewis, 1990). This account provides the details of this excursion into the use of hierarchical testlets and validity-based scoring. A pretest of two 15-item hierarchical testlets was carried out in which examinees' performance on a 4-item subset of each…

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. Accurate lithography hotspot detection based on PCA-SVM classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Gao, Jhih-Rong; Yu, Bei; Pan, David Z.

    2014-03-01

    As technology nodes continues shrinking, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. In this paper, we propose an accurate hotspot detection approach based on PCA (principle component analysis)-SVM (sup- port vector machine) classifier. Several techniques, including hierarchical data clustering, data balancing, and multi-level training, are provided to enhance performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation; in the meanwhile, provides high flexibility to adapt to new lithography processes and rules.

  9. 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.

  10. 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

  11. Identifying potential clinical syndromes of hepatocellular carcinoma using PSO-based hierarchical feature selection algorithm.

    PubMed

    Ji, Zhiwei; Wang, Bing

    2014-01-01

    Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. Clinical symptoms attributable to HCC are usually absent, thus often miss the best therapeutic opportunities. Traditional Chinese Medicine (TCM) plays an active role in diagnosis and treatment of HCC. In this paper, we proposed a particle swarm optimization-based hierarchical feature selection (PSOHFS) model to infer potential syndromes for diagnosis of HCC. Firstly, the hierarchical feature representation is developed by a three-layer tree. The clinical symptoms and positive score of patient are leaf nodes and root in the tree, respectively, while each syndrome feature on the middle layer is extracted from a group of symptoms. Secondly, an improved PSO-based algorithm is applied in a new reduced feature space to search an optimal syndrome subset. Based on the result of feature selection, the causal relationships of symptoms and syndromes are inferred via Bayesian networks. In our experiment, 147 symptoms were aggregated into 27 groups and 27 syndrome features were extracted. The proposed approach discovered 24 syndromes which obviously improved the diagnosis accuracy. Finally, the Bayesian approach was applied to represent the causal relationships both at symptom and syndrome levels. The results show that our computational model can facilitate the clinical diagnosis of HCC.

  12. 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

  13. A hierarchical visualization model of the global terrain based on QTM

    NASA Astrophysics Data System (ADS)

    Bai, Jian-jun; Yan, Chao-de; Zhao, Xue-sheng

    2008-10-01

    A global multi-resolution digital elevation model (DEM) and a feasible solution for its visualization and management remains a challenging vision. In this paper a multi-resolution DEM based on the ellipsoidal triangular meshes is made to approximate to the earth surface. It was built through quaternary triangular mesh (QTM) hierarchical tessellation of the ellipsoidal surface. In order to achieve fast access, we organize the global DEM data as a hierarchy of Diamonds and indexing them based on the linear quadtree. Furthermore, a LOD is built through recursive subdivision of each Diamond, and an approach of viewpoints-based data extraction based on the neighbor-Diamond searching from the global DEM data is implemented for visualization. All this is backed with an implementation of a prototype computer system.

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

    NASA Astrophysics Data System (ADS)

    Wang, Fang-Fang; Su, Chao-Ton

    2014-11-01

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

  15. Unconventional lithography for hierarchical micro-/nanostructure arrays with well-aligned 1D crystalline nanostructures: design and creation based on the colloidal monolayer.

    PubMed

    Li, Yue; Koshizaki, Naoto; Shimizu, Yoshiki; Li, Liang; Gao, Shuyan; Sasaki, Takeshi

    2009-11-01

    We have developed a strategy for designing and fabricating hierarchical micro-/nanostructured arrays based on the combination of a colloidal monolayer substrate and the pulsed laser deposition (PLD) process. In this approach, microstructures are provided by the colloidal monolayer and can be tuned by changing colloidal monolayer periodicities, while crystalline nanostructures are supplied by PLD and can be controlled by PLD experiment parameters (e.g., ambient gas pressure). In comparison with the traditional lithography techniques, the proposed method has the obvious advantage of low cost. More importantly, the complicated hierarchical micro-/nanostructure arrays obtained by the present strategy cannot easily be designed and synthesized by traditional lithography techniques. This fact suggests that the proposed method can be a quite powerful alternative to fabricate complicated hierarchical arrays by complementing the weakness of traditional lithographic routes. In addition to these, the strategy also features uniform surface morphology, room-temperature reaction, and pure sample surfaces that are highly valuable to build a new generation of microdevices or nanodevices in nanophotonics, energy storage, etc. on the basis of these special hierarchical micro-/nanostructured arrays.

  16. An Amperometric Acetylcholinesterase Sensor Based on the Bio-templated Synthesis of Hierarchical Mesoporous Bioactive Glass Microspheres

    NASA Astrophysics Data System (ADS)

    Lv, Zhuo; Luo, Ruiping; Xi, Lijuan; Chen, Yang; Wang, Hongsu

    2017-07-01

    This work describes the synthesis of three-dimensional hollow hierarchical mesoporous bioactive glass (HMBG) microspheres based on Herba leonuri pollen grains via a hydrothermal method. The HMBG microspheres perfectly copied the hierarchical porous structure and inner hollow structure constituting the double-layer surface of the natural Herba leonuri pollen grains. This structural mimicry of the pollen grains resulted in a higher degree of adsorption of acetylcholinesterase (AChE) on HMBG microspheres in comparison with mesoporous bioactive glass. Subsequently, an amperometric biosensor for the detection of Malathion was fabricated by immobilizing AChE onto an HMBG microspheres-modified carbon paste electrode. The biosensor response exhibited two good linear ranges during an incubation time of 10 min in the malathion concentration ranges of 0.02-50 ppb and 50-600 ppb, with a detection limit of 0.0135 ppb (S/N = 3). Overall, the prepared enzymatic biosensor showed high sensitivity in the rapid detection of Malathion and could be applied to detect pesticide residues in vegetable matter.

  17. Object class recognition based on compressive sensing with sparse features inspired by hierarchical model in visual cortex

    NASA Astrophysics Data System (ADS)

    Lu, Pei; Xu, Zhiyong; Yu, Huapeng; Chang, Yongxin; Fu, Chengyu; Shao, Jianxin

    2012-11-01

    According to models of object recognition in cortex, the brain uses a hierarchical approach in which simple, low-level features having high position and scale specificity are pooled and combined into more complex, higher-level features having greater location invariance. At higher levels, spatial structure becomes implicitly encoded into the features themselves, which may overlap, while explicit spatial information is coded more coarsely. In this paper, the importance of sparsity and localized patch features in a hierarchical model inspired by visual cortex is investigated. As in the model of Serre, Wolf, and Poggio, we first apply Gabor filters at all positions and scales; feature complexity and position/scale invariance are then built up by alternating template matching and max pooling operations. In order to improve generalization performance, the sparsity is proposed and data dimension is reduced by means of compressive sensing theory and sparse representation algorithm. Similarly, within computational neuroscience, adding the sparsity on the number of feature inputs and feature selection is critical for learning biologically model from the statistics of natural images. Then, a redundancy dictionary of patch-based features that could distinguish object class from other categories is designed and then object recognition is implemented by the process of iterative optimization. The method is test on the UIUC car database. The success of this approach suggests a proof for the object class recognition in visual cortex.

  18. Staging of Fatty Liver Diseases Based on Hierarchical Classification and Feature Fusion for Back-Scan-Converted Ultrasound Images.

    PubMed

    Owjimehr, Mehri; Danyali, Habibollah; Helfroush, Mohammad Sadegh; Shakibafard, Alireza

    2017-03-01

    Fatty liver disease is progressive and may not cause any symptoms at early stages. This disease is potentially fatal and can cause liver cancer in severe stages. Therefore, diagnosing and staging fatty liver disease in early stages is necessary. In this paper, a novel method is presented to classify normal and fatty liver, as well as discriminate three stages of fatty liver in ultrasound images. This study is performed with 129 subjects including 28 normal, 47 steatosis, 42 fibrosis, and 12 cirrhosis images. The proposed approach uses back-scan conversion of ultrasound sector images and is based on a hierarchical classification. The proposed algorithm is performed in two parts. The first part selects the optimum regions of interest from the focal zone of the back-scan-converted ultrasound images. In the second part, discrimination between normal and fatty liver is performed and then steatosis, fibrosis, and cirrhosis are classified in a hierarchical basis. The wavelet packet transform and gray-level co-occurrence matrix are used to obtain a number of statistical features. A support vector machine classifier is used to discriminate between normal and fatty liver, and stage fatty cases. The results of the proposed scheme clearly illustrate the efficiency of this system with overall accuracy of 94.91% and also specificity of more than 90%.

  19. An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps.

    PubMed

    Papageorgiou, Elpiniki I; Stylios, Chrysostomos D; Groumpos, Peter P

    2003-12-01

    The radiation therapy decision-making is a complex process that has to take into consideration a variety of interrelated functions. Many fuzzy factors that must be considered in the calculation of the appropriate dose increase the complexity of the decision-making problem. A novel approach introduces fuzzy cognitive maps (FCMs) as the computational modeling method, which tackles the complexity and allows the analysis and simulation of the clinical radiation procedure. Specifically this approach is used to determine the success of radiation therapy process estimating the final dose delivered to the target volume, based on the soft computing technique of FCMs. Furthermore a two-level integrated hierarchical structure is proposed to supervise and evaluate the radiotherapy process prior to treatment execution. The supervisor determines the treatment variables of cancer therapy and the acceptance level of final radiation dose to the target volume. Two clinical case studies are used to test the proposed methodology and evaluate the simulation results. The usefulness of this two-level hierarchical structure discussed and future research directions are suggested for the clinical use of this methodology.

  20. Hierarchical calibration and validation of computational fluid dynamics models for solid sorbent-based carbon capture

    SciTech Connect

    Lai, Canhai; Xu, Zhijie; Pan, Wenxiao; Sun, Xin; Storlie, Curtis; Marcy, Peter; Dietiker, Jean-François; Li, Tingwen; Spenik, James

    2016-01-01

    To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesian calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.

  1. Hierarchical searching in model-based LADAR ATR using statistical separability tests

    NASA Astrophysics Data System (ADS)

    DelMarco, Stephen; Sobel, Erik; Douglas, Joel

    2006-05-01

    In this work we investigate simultaneous object identification improvement and efficient library search for model-based object recognition applications. We develop an algorithm to provide efficient, prioritized, hierarchical searching of the object model database. A common approach to model-based object recognition chooses the object label corresponding to the best match score. However, due to corrupting effects the best match score does not always correspond to the correct object model. To address this problem, we propose a search strategy which exploits information contained in a number of representative elements of the library to drill down to a small class with high probability of containing the object. We first optimally partition the library into a hierarchic taxonomy of disjoint classes. A small number of representative elements are used to characterize each object model class. At each hierarchy level, the observed object is matched against the representative elements of each class to generate score sets. A hypothesis testing problem, using a distribution-free statistical test, is defined on the score sets and used to choose the appropriate class for a prioritized search. We conduct a probabilistic analysis of the computational cost savings, and provide a formula measuring the computational advantage of the proposed approach. We generate numerical results using match scores derived from matching highly-detailed CAD models of civilian ground vehicles used in 3-D LADAR ATR. We present numerical results showing effects on classification performance of significance level and representative element number in the score set hypothesis testing problem.

  2. Agglomerative hierarchical cluster method to analyze landslide displacements and assess risk scenarios

    NASA Astrophysics Data System (ADS)

    Bossi, Giulia; Crema, Stefano; Mantovani, Matteo; Schenato, Luca; Cavalli, Marco; Marcato, Gianluca; Frigerio, Simone; Pasuto, Alessandro

    2017-04-01

    In the Rotolon catchment (eastern Italian Alps) a large Deep-seated Gravitational Slope Deformation (DGSD) induces secondary phenomena that are threatening the local population. In 2010 a mass of 340.000 m3 detached from the frontal part of the DGSD and then flow into the draining channel in the form of a debris flow, damaging a bridge and almost over-flooding, endangering the houses located 3 km downstream. For this reason, an Automated Total Station (ATS) has been installed in 2012 to monitor surface displacements so as to identify the most active regions of the slope in order to estimate the volume of material that could be mobilized in the next paroxysmal event and to assess the related risk. 42 benchmarks (5 stable control points and 37 on the active slope) have been monitored for two periods: the first one of 22 months between 2012 and 2014 and the second one for 12 months between 2015 and 2016. Analyzing the time series of displacements with the agglomerative hierarchical cluster method calculated with a simple single linkage algorithm, groups of similarly moving benchmarks have been clustered. For these groups the trend of acceleration and deceleration of displacements follows similar patterns. Even though the methodology does not take into account the position of the benchmarks, matching patterns are found in contiguous benchmarks within the groups, thus confirming the effectiveness of the approach. The possibility to identify areas with homogeneous behavior is fundamental to delineate the volume of possible new debris flow phenomena and therefore to produce reliable risk scenarios.

  3. Compressed-sensing-based content-driven hierarchical reconstruction: Theory and application to C-arm cone-beam tomography

    SciTech Connect

    Langet, Hélène; Riddell, Cyril Reshef, Aymeric; Trousset, Yves; Tenenhaus, Arthur; Lahalle, Elisabeth; Fleury, Gilles; Paragios, Nikos

    2015-09-15

    Purpose: This paper addresses the reconstruction of x-ray cone-beam computed tomography (CBCT) for interventional C-arm systems. Subsampling of CBCT is a significant issue with C-arms due to their slow rotation and to the low frame rate of their flat panel x-ray detectors. The aim of this work is to propose a novel method able to handle the subsampling artifacts generally observed with analytical reconstruction, through a content-driven hierarchical reconstruction based on compressed sensing. Methods: The central idea is to proceed with a hierarchical method where the most salient features (high intensities or gradients) are reconstructed first to reduce the artifacts these features induce. These artifacts are addressed first because their presence contaminates less salient features. Several hierarchical schemes aiming at streak artifacts reduction are introduced for C-arm CBCT: the empirical orthogonal matching pursuit approach with the ℓ{sub 0} pseudonorm for reconstructing sparse vessels; a convex variant using homotopy with the ℓ{sub 1}-norm constraint of compressed sensing, for reconstructing sparse vessels over a nonsparse background; homotopy with total variation (TV); and a novel empirical extension to nonlinear diffusion (NLD). Such principles are implemented with penalized iterative filtered backprojection algorithms. For soft-tissue imaging, the authors compare the use of TV and NLD filters as sparsity constraints, both optimized with the alternating direction method of multipliers, using a threshold for TV and a nonlinear weighting for NLD. Results: The authors show on simulated data that their approach provides fast convergence to good approximations of the solution of the TV-constrained minimization problem introduced by the compressed sensing theory. Using C-arm CBCT clinical data, the authors show that both TV and NLD can deliver improved image quality by reducing streaks. Conclusions: A flexible compressed-sensing-based algorithmic approach is

  4. Hierarchical rule-based monitoring and fuzzy logic control for neuromuscular block.

    PubMed

    Shieh, J S; Fan, S Z; Chang, L W; Liu, C C

    2000-01-01

    activity. The results showed that a hierarchical rule-based monitoring and fuzzy logic control architecture can provide stable control of neuromuscular block despite the considerable individual variation in neuromuscular block required among patients. Also, there was less variation in T1% error compared with that of previous study on mivacurium. Meanwhile, the consistent medium CV of the MIR of both rocuronium and mivacurium indicated a good controller activity which is able to withstand noise, diathermy effect, artifacts and surgical disturbances.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. Isogeometric Collocation: Cost Comparison with Galerkin Methods and Extension to Adaptive Hierarchical NURBS Discretizations (Preprint)

    DTIC Science & Technology

    2013-02-06

    levels, the ratio saturates to an asymptotic value acceptably “close” to its optimum reff=1.0. Second, we focus on the 2D advection benchmark discussed in...112] D. Forsey and R.H. Bartels. Hierarchical B-spline refinement. Computer Graphics (SIGGRAPH ’88 Proceedings), 22(4):205–212, 1988. [113] R. Kraft

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

    PubMed

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

    2014-04-09

    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.

  11. 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.

  12. Compressed-sensing-based content-driven hierarchical reconstruction: Theory and application to C-arm cone-beam tomography.

    PubMed

    Langet, Hélène; Riddell, Cyril; Reshef, Aymeric; Trousset, Yves; Tenenhaus, Arthur; Lahalle, Elisabeth; Fleury, Gilles; Paragios, Nikos

    2015-09-01

    This paper addresses the reconstruction of x-ray cone-beam computed tomography (CBCT) for interventional C-arm systems. Subsampling of CBCT is a significant issue with C-arms due to their slow rotation and to the low frame rate of their flat panel x-ray detectors. The aim of this work is to propose a novel method able to handle the subsampling artifacts generally observed with analytical reconstruction, through a content-driven hierarchical reconstruction based on compressed sensing. The central idea is to proceed with a hierarchical method where the most salient features (high intensities or gradients) are reconstructed first to reduce the artifacts these features induce. These artifacts are addressed first because their presence contaminates less salient features. Several hierarchical schemes aiming at streak artifacts reduction are introduced for C-arm CBCT: the empirical orthogonal matching pursuit approach with the ℓ0 pseudonorm for reconstructing sparse vessels; a convex variant using homotopy with the ℓ1-norm constraint of compressed sensing, for reconstructing sparse vessels over a nonsparse background; homotopy with total variation (TV); and a novel empirical extension to nonlinear diffusion (NLD). Such principles are implemented with penalized iterative filtered backprojection algorithms. For soft-tissue imaging, the authors compare the use of TV and NLD filters as sparsity constraints, both optimized with the alternating direction method of multipliers, using a threshold for TV and a nonlinear weighting for NLD. The authors show on simulated data that their approach provides fast convergence to good approximations of the solution of the TV-constrained minimization problem introduced by the compressed sensing theory. Using C-arm CBCT clinical data, the authors show that both TV and NLD can deliver improved image quality by reducing streaks. A flexible compressed-sensing-based algorithmic approach is proposed that is able to accommodate for a wide

  13. Classification of cancer cell lines using an automated two-dimensional liquid mapping method with hierarchical clustering techniques.

    PubMed

    Wang, Yanfei; Wu, Rong; Cho, Kathleen R; Shedden, Kerby A; Barder, Timothy J; Lubman, David M

    2006-01-01

    A two-dimensional liquid mapping method was used to map the protein expression of eight ovarian serous carcinoma cell lines and three immortalized ovarian surface epithelial cell lines. Maps were produced using pI as the separation parameter in the first dimension and hydrophobicity based upon reversed-phase HPLC separation in the second dimension. The method can be reproducibly used to produce protein expression maps over a pH range from 4.0 to 8.5. A dynamic programming method was used to correct for minor shifts in peaks during the HPLC gradient between sample runs. The resulting corrected maps can then be compared using hierarchical clustering to produce dendrograms indicating the relationship between different cell lines. It was found that several of the ovarian surface epithelial cell lines clustered together, whereas specific groups of serous carcinoma cell lines clustered with each other. Although there is limited information on the current biology of these cell lines, it was shown that the protein expression of certain cell lines is closely related to each other. Other cell lines, including one ovarian clear cell carcinoma cell line, two endometrioid carcinoma cell lines, and three breast epithelial cell lines, were also mapped for comparison to show that their protein profiles cluster differently than the serous samples and to study how they cluster relative to each other. In addition, comparisons can be made between proteins differentially expressed between cell lines that may serve as markers of ovarian serous carcinomas. The automation of the method allows reproducible comparison of many samples, and the use of differential analysis limits the number of proteins that might require further analysis by mass spectrometry techniques.

  14. 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.

  15. A hierarchical P2P overlay network for interest-based media contents lookup

    NASA Astrophysics Data System (ADS)

    Lee, HyunRyong; Kim, JongWon

    2006-10-01

    We propose a P2P (peer-to-peer) overlay architecture, called IGN (interest grouping network), for contents lookup in the DHC (digital home community), which aims to provide a formalized home-network-extended construction of current P2P file sharing community. The IGN utilizes the Chord and de Bruijn graph for its hierarchical overlay network construction. By combining two schemes and by inheriting its features, the IGN efficiently supports contents lookup. More specifically, by introducing metadata-based lookup keyword, the IGN offers detailed contents lookup that can reflect the user interests. Moreover, the IGN tries to reflect home network environments of DHC by utilizing HG (home gateway) of each home network as a participating node of the IGN. Through experimental and analysis results, we show that the IGN is more efficient than Chord, a well-known DHT (distributed hash table)-based lookup protocol.

  16. 3D face recognition based on the hierarchical score-level fusion classifiers

    NASA Astrophysics Data System (ADS)

    Mráček, Štěpán.; Váša, Jan; Lankašová, Karolína; Drahanský, Martin; Doležel, Michal

    2014-05-01

    This paper describes the 3D face recognition algorithm that is based on the hierarchical score-level fusion clas-sifiers. In a simple (unimodal) biometric pipeline, the feature vector is extracted from the input data and subsequently compared with the template stored in the database. In our approachm, we utilize several feature extraction algorithms. We use 6 different image representations of the input 3D face data. Moreover, we are using Gabor and Gauss-Laguerre filter banks applied on the input image data that yield to 12 resulting feature vectors. Each representation is compared with corresponding counterpart from the biometric database. We also add the recognition based on the iso-geodesic curves. The final score-level fusion is performed on 13 comparison scores using the Support Vector Machine (SVM) classifier.

  17. Hierarchical Corannulene-Based Materials: Energy Transfer and Solid-State Photophysics.

    PubMed

    Rice, Allison M; Fellows, W Brett; Dolgopolova, Ekaterina A; Greytak, Andrew B; Vannucci, Aaron K; Smith, Mark D; Karakalos, Stavros G; Krause, Jeanette A; Avdoshenko, Stanislav M; Popov, Alexey A; Shustova, Natalia B

    2017-04-10

    We report the first example of a donor-acceptor corannulene-containing hybrid material with rapid ligand-to-ligand energy transfer (ET). Additionally, we provide the first time-resolved photoluminescence (PL) data for any corannulene-based compounds in the solid state. Comprehensive analysis of PL data in combination with theoretical calculations of donor-acceptor exciton coupling was employed to estimate ET rate and efficiency in the prepared material. The ligand-to-ligand ET rate calculated using two models is comparable with that observed in fullerene-containing materials, which are generally considered for molecular electronics development. Thus, the presented studies not only demonstrate the possibility of merging the intrinsic properties of π-bowls, specifically corannulene derivatives, with the versatility of crystalline hybrid scaffolds, but could also foreshadow the engineering of a novel class of hierarchical corannulene-based hybrid materials for optoelectronic devices.

  18. 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.

  19. Hierarchical expansion of the kinetic energy operator in curvilinear coordinates for the vibrational self-consistent field method.

    PubMed

    Strobusch, D; Scheurer, Ch

    2011-09-28

    A new hierarchical expansion of the kinetic energy operator in curvilinear coordinates is presented and modified vibrational self-consistent field (VSCF) equations are derived including all kinematic effects within the mean field approximation. The new concept for the kinetic energy operator is based on many-body expansions for all G matrix elements and its determinant. As a test application VSCF computations were performed on the H(2)O(2) molecule using an analytic potential (PCPSDE) and different hierarchical approximations for the kinetic energy operator. The results indicate that coordinate-dependent reduced masses account for the largest part of the kinetic energy. Neither kinematic couplings nor derivatives of the G matrix nor its determinant had significant effects on the VSCF energies. Only the zero-point value of the pseudopotential yields an offset to absolute energies which, however, is irrelevant for spectroscopic problems.

  20. 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

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

    DOE PAGES

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-08-31

    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 ofmore » 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

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

    SciTech Connect

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-08-31

    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

  3. Ultrametric Hierarchical Clustering Algorithms.

    ERIC Educational Resources Information Center

    Milligan, Glenn W.

    1979-01-01

    Johnson has shown that the single linkage and complete linkage hierarchical clustering algorithms induce a metric on the data known as the ultrametric. Johnson's proof is extended to four other common clustering algorithms. Two additional methods also produce hierarchical structures which can violate the ultrametric inequality. (Author/CTM)

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

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

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

  5. 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

  6. 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

  7. Carbon-based hierarchical scaffolds for myoblast differentiation: Synergy between nano-functionalization and alignment.

    PubMed

    Patel, Akhil; Mukundan, Shilpaa; Wang, Wenhu; Karumuri, Anil; Sant, Vinayak; Mukhopadhyay, Sharmila M; Sant, Shilpa

    2016-03-01

    While several scaffolds have been proposed for skeletal muscle regeneration, multiscale hierarchical scaffolds with the complexity of extracellular matrix (ECM) haven't been engineered successfully. By precise control over nano- and microscale features, comprehensive understanding of the effect of multiple factors on skeletal muscle regeneration can be derived. In this study, we engineered carbon-based scaffolds with hierarchical nano- and microscale architecture with controlled physico-chemical properties. More specifically, we built multiscale hierarchy by growing carbon nanotube (CNT) carpets on two types of scaffolds, namely, interconnected microporous carbon foams and aligned carbon fiber mats. Nanostructured CNT carpets offered fine control over nano-roughness and wettability facilitating myoblast adhesion, growth and differentiation into myocytes. However, microporous foam architecture failed to promote their fusion into multinucleated myotubes. On the other hand, aligned fibrous architecture stimulated formation of multinucleated myotubes. Most importantly, nanostructured CNT carpets interfaced with microscale aligned fibrous architecture significantly enhanced myocyte fusion into multinucleated mature myotubes highlighting synergy between nanoscale surface features and micro-/macroscale aligned fibrous architecture in the process of myogenesis. Due to limited regenerative potential of skeletal muscle, strategies stimulating regeneration of functional muscles are important. These strategies are aimed at promoting differentiation of progenitor cells (myoblasts) into multinucleated myotubes, a key initial step in functional muscle regeneration. Recent tissue engineering approaches utilize various scaffolds ranging from decellularized matrices to aligned biomaterial scaffolds. Although, majority of them have focused on nano- or microscale organization, a systematic approach to build the multiscale hierarchy into these scaffolds is lacking. Here, we engineered

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  9. [Study of the accidental thymus involution during the formation of hierarchic communities by a novel physical method for recording the social stress].

    PubMed

    Kulikov, A V; Arkhipova, L V; Kulikov, D A; Smirnova, G N; Kulikova, P A

    2013-01-01

    A novel method for recording the aggressive behavior in newly formed hierarchic communities has been developed. A temporal and age-related dynamics of the accidental thymus involution in mammals has been studied.

  10. 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.

  11. 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

  12. Hierarchical PEG-Based 3D Patterns Grafting from Polymer Substrate by Surface Initiated Visible Light Photolithography.

    PubMed

    Zhao, Changwen; He, Bin; Wang, Guan; Ma, Yuhong; Yang, Wantai

    2016-10-01

    The precise construction of a hierarchical complex pattern on substrates is required for numerous applications. Here, a strategy to fabricate well-defined hierarchical three dimensional (3D) patterns on polymer substrate is developed. This technique, which combines photolithography and visible light-induced surface initiated living graft crosslinking polymerization (VSLGCP), can effectively graft 3D patterns onto polymer substrate with high fidelity and controllable height. Owing to the living nature of VSLGCP, hierarchical 3D patterns can be prepared when a sequential living graft crosslinking process is performed on the first formed patterns. As a proof-of-concept, a reactive two layer 3D pattern with a morphology of lateral stripe on vertical stripe is prepared and employed to separately immobilize model biomolecules, e.g., biotin and IgG. This two component pattern can specifically interact with corresponding target proteins successfully, indicating that this strategy has potential applications in the fabrication of polymer-based multicomponent biomolecule microarrays.

  13. How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

    PubMed

    Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

    2015-01-01

    The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy.

  14. Hierarchical MnO2 nanosheets synthesized via electrodeposition-hydrothermal method for supercapacitor electrodes

    NASA Astrophysics Data System (ADS)

    Zheng, Dongdong; Qiang, Yujie; Xu, Shenying; Li, Wenpo; Yu, Shanshan; Zhang, Shengtao

    2017-02-01

    Metal oxides have emerged as one kind of important supercapacitor electrode materials. Herein, we report hierarchical MnO2 nanosheets prepared of indium tin oxide (ITO) coated glass substrates via a hybrid two-step protocol, including a cathodic electrodeposition technique and a hydrothermal process. The samples are characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM) with energy dispersive X-ray spectroscopy (EDX), and transmission electron microscope (TEM). SEM and TEM images show that the as-synthesized MnO2 nanosheets are hierarchical and porous, which could increase the active surface and short paths for fast ion diffusion. The results of nitrogen adsorption-desorption analysis indicate that the BET surface area of the MnO2 nanosheets is 53.031 m2 g-1. Furthermore, the electrochemical properties of the MnO2 are elucidated by cyclic voltammograms (CV), galvanostatic charge-discharge (GCD) tests, and electrochemical impedance spectroscopy (EIS) in 0.1 M Na2SO4 electrolyte. The electrochemical results demonstrate that the as-grown MnO2 nanosheet exhibits an excellent specific capacitance of 335 F g-1 at 0.5 A g-1 when it is applied as a potential electrode material for an electrochemical supercapacitor. Additionally, the MnO2 nanosheet electrode also presents high rate capability and good cycling stability with 91.8% retention after 1000 cycles. These excellent properties indicate that the hierarchical MnO2 nanosheets are a potential electrode material for electrochemical supercapacitors.

  15. 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.

  16. 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.

  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. 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.

  19. 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.

  20. 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.

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

    PubMed

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

    2014-01-01

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

  2. Temporal segmentation of video objects for hierarchical object-based motion description.

    PubMed

    Fu, Yue; Ekin, Ahmet; Tekalp, A Murat; Mehrotra, Rajiv

    2002-01-01

    This paper describes a hierarchical approach for object-based motion description of video in terms of object motions and object-to-object interactions. We present a temporal hierarchy for object motion description, which consists of low-level elementary motion units (EMU) and high-level action units (AU). Likewise, object-to-object interactions are decomposed into a hierarchy of low-level elementary reaction units (ERU) and high-level interaction units (IU). We then propose an algorithm for temporal segmentation of video objects into EMUs, whose dominant motion can be described by a single representative parametric model. The algorithm also computes a representative (dominant) affine model for each EMU. We also provide algorithms for identification of ERUs and for classification of the type of ERUs. Experimental results demonstrate that segmenting the life-span of video objects into EMUS and ERUs facilitates the generation of high-level visual summaries for fast browsing and navigation. At present, the formation of high-level action and interaction units is done interactively. We also provide a set of query-by-example results for low-level EMU retrieval from a database based on similarity of the representative dominant affine models.

  3. Humic acids-based hierarchical porous carbons as high-rate performance electrodes for symmetric supercapacitors.

    PubMed

    Qiao, Zhi-jun; Chen, Ming-ming; Wang, Cheng-yang; Yuan, Yun-cai

    2014-07-01

    Two kinds of hierarchical porous carbons (HPCs) with specific surface areas of 2000 m(2)g(-1) were synthesized using leonardite humic acids (LHA) or biotechnology humic acids (BHA) precursors via a KOH activation process. Humic acids have a high content of oxygen-containing groups which enabled them to dissolve in aqueous KOH and facilitated the homogeneous KOH activation. The LHA-based HPC is made up of abundant micro-, meso-, and macropores and in 6M KOH it has a specific capacitance of 178 F g(-1) at 100 Ag(-1) and its capacitance retention on going from 0.05 to 100 A g(-1) is 64%. In contrast, the BHA-based HPC exhibits a lower capacitance retention of 54% and a specific capacitance of 157 F g(-1) at 100 A g(-1) which is due to the excessive micropores in the BHA-HPC. Moreover, LHA-HPC is produced in a higher yield than BHA-HPC (51 vs. 17 wt%). Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Using hierarchical tree-based regression model to predict train-vehicle crashes at passive highway-rail grade crossings.

    PubMed

    Yan, Xuedong; Richards, Stephen; Su, Xiaogang

    2010-01-01

    This paper applies a nonparametric statistical method, hierarchical tree-based regression (HTBR), to explore train-vehicle crash prediction and analysis at passive highway-rail grade crossings. Using the Federal Railroad Administration (FRA) database, the research focuses on 27 years of train-vehicle accident history in the United States from 1980 through 2006. A cross-sectional statistical analysis based on HTBR is conducted for public highway-rail grade crossings that were upgraded from crossbuck-only to stop signs without involvement of other traffic-control devices or automatic countermeasures. In this study, HTBR models are developed to predict train-vehicle crash frequencies for passive grade crossings controlled by crossbucks only and crossbucks combined with stop signs respectively, and assess how the crash frequencies change after the stop-sign treatment is applied at the crossbuck-only-controlled crossings. The study results indicate that stop-sign treatment is an effective engineering countermeasure to improve safety at the passive grade crossings. Decision makers and traffic engineers can use the HTBR models to examine train-vehicle crash frequency at passive crossings and assess the potential effectiveness of stop-sign treatment based on specific attributes of the given crossings.

  6. Hierarchical Bayesian method for mapping biogeochemical hot spots using induced polarization imaging

    NASA Astrophysics Data System (ADS)

    Wainwright, Haruko M.; Flores Orozco, Adrian; Bücker, Matthias; Dafflon, Baptiste; Chen, Jinsong; Hubbard, Susan S.; Williams, Kenneth H.

    2016-01-01

    In floodplain environments, a naturally reduced zone (NRZ) is considered to be a common biogeochemical hot spot, having distinct microbial and geochemical characteristics. Although important for understanding their role in mediating floodplain biogeochemical processes, mapping the subsurface distribution of NRZs over the dimensions of a floodplain is challenging, as conventional wellbore data are typically spatially limited and the distribution of NRZs is heterogeneous. In this study, we present an innovative methodology for the probabilistic mapping of NRZs within a three-dimensional (3-D) subsurface domain using induced polarization imaging, which is a noninvasive geophysical technique. Measurements consist of surface geophysical surveys and drilling-recovered sediments at the U.S. Department of Energy field site near Rifle, CO (USA). Inversion of surface time domain-induced polarization (TDIP) data yielded 3-D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. By extracting the TDIP data values colocated with wellbore lithological logs, we found that the NRZs have a different distribution of resistivity and polarization from the other aquifer sediments. To estimate the spatial distribution of NRZs, we developed a Bayesian hierarchical model to integrate the geophysical and wellbore data. In addition, the resistivity images were used to estimate hydrostratigraphic interfaces under the floodplain. Validation results showed that the integration of electrical imaging and wellbore data using a Bayesian hierarchical model was capable of mapping spatially heterogeneous interfaces and NRZ distributions thereby providing a minimally invasive means to parameterize a hydrobiogeochemical model of the floodplain.

  7. 3 D Hierarchical Porous Carbon for Supercapacitors Prepared from Lignin through a Facile Template-Free Method.

    PubMed

    Zhang, Wenli; Lin, Haibo; Lin, Zheqi; Yin, Jian; Lu, Haiyan; Liu, Dechen; Zhao, Mingzhu

    2015-06-22

    Lignin-derived hierarchical porous carbon (LHPC) was prepared through a facile template-free method. Solidification of the lignin-KOH solution resulted in KOH crystalizing within lignin. The crystalized KOH particles in solid lignin acted both as template and activating agent in the heat-treatment process. The obtained LHPC, exhibiting a 3D network, consisted of macroporous cores, mesoporous channels, and micropores. The LHPC comprised 12.27 at % oxygen-containing groups, which resulted in pseudocapacitance. The LHPC displayed a capacitance of 165.0 F g(-1) in 1 M H2 SO4 at 0.05 A g(-1) , and the capacitance was still 123.5 F g(-1) even at 10 A g(-1) . The LHPC also displayed excellent cycling stability with capacitance retention of 97.3 % after 5000 galvanostatic charge-discharge cycles. On account of the facile preparation of LHPC, this paper offers a facile alternative method for the preparation of hierarchical porous carbon for electrochemical energy storage devices.

  8. Hierarchical Acceleration of Multilevel Monte Carlo Methods for Computationally Expensive Simulations in Reservoir Modeling

    NASA Astrophysics Data System (ADS)

    Zhang, G.; Lu, D.; Webster, C.

    2014-12-01

    The rational management of oil and gas reservoir requires an understanding of its response to existing and planned schemes of exploitation and operation. Such understanding requires analyzing and quantifying the influence of the subsurface uncertainties on predictions of oil and gas production. As the subsurface properties are typically heterogeneous causing a large number of model parameters, the dimension independent Monte Carlo (MC) method is usually used for uncertainty quantification (UQ). Recently, multilevel Monte Carlo (MLMC) methods were proposed, as a variance reduction technique, in order to improve computational efficiency of MC methods in UQ. In this effort, we propose a new acceleration approach for MLMC method to further reduce the total computational cost by exploiting model hierarchies. Specifically, for each model simulation on a new added level of MLMC, we take advantage of the approximation of the model outputs constructed based on simulations on previous levels to provide better initial states of new simulations, which will help improve efficiency by, e.g. reducing the number of iterations in linear system solving or the number of needed time-steps. This is achieved by using mesh-free interpolation methods, such as Shepard interpolation and radial basis approximation. Our approach is applied to a highly heterogeneous reservoir model from the tenth SPE project. The results indicate that the accelerated MLMC can achieve the same accuracy as standard MLMC with a significantly reduced cost.

  9. 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

  10. A new method for the level set equation using a hierarchical-gradient truncation and remapping technique

    NASA Astrophysics Data System (ADS)

    Kohno, Haruhiko; Nave, Jean-Christophe

    2013-06-01

    We present a novel numerical method for solving the advection equation for a level set function. The new method uses hierarchical-gradient truncation and remapping (H-GTaR) of the original partial differential equation (PDE). Our strategy reduces the original PDE to a set of decoupled linear ordinary differential equations with constant coefficients. Additionally, we introduce a remapping strategy to periodically guarantee solution accuracy for a deformation problem. The proposed scheme yields nearly an exact solution for a rigid body motion with a smooth function that possesses vanishingly small higher derivatives and calculates the gradient of the advected function in a straightforward way. We will evaluate our method in one- and two-dimensional domains and present results to several classical benchmark problems.

  11. 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

  12. HIGEDA: a hierarchical gene-set genetics based algorithm for finding subtle motifs in biological sequences.

    PubMed

    Le, Thanh; Altman, Tom; Gardiner, Katheleen

    2010-02-01

    Identification of motifs in biological sequences is a challenging problem because such motifs are often short, degenerate, and may contain gaps. Most algorithms that have been developed for motif-finding use the expectation-maximization (EM) algorithm iteratively. Although EM algorithms can converge quickly, they depend strongly on initialization parameters and can converge to local sub-optimal solutions. In addition, they cannot generate gapped motifs. The effectiveness of EM algorithms in motif finding can be improved by incorporating methods that choose different sets of initial parameters to enable escape from local optima, and that allow gapped alignments within motif models. We have developed HIGEDA, an algorithm that uses the hierarchical gene-set genetic algorithm (HGA) with EM to initiate and search for the best parameters for the motif model. In addition, HIGEDA can identify gapped motifs using a position weight matrix and dynamic programming to generate an optimal gapped alignment of the motif model with sequences from the dataset. We show that HIGEDA outperforms MEME and other motif-finding algorithms on both DNA and protein sequences. Source code and test datasets are available for download at http://ouray.cudenver.edu/~tnle/, implemented in C++ and supported on Linux and MS Windows.

  13. 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.

  14. Hierarchical modeling of heat transfer in silicon-based electronic devices

    NASA Astrophysics Data System (ADS)

    Goicochea Pineda, Javier V.

    In this work a methodology for the hierarchical modeling of heat transfer in silicon-based electronic devices is presented. The methodology includes three steps to integrate the different scales involved in the thermal analysis of these devices. The steps correspond to: (i) the estimation of input parameters and thermal properties required to solve the Boltzmann transport equation (BTE) for phonons by means of molecular dynamics (MD) simulations, (ii) the quantum correction of some of the properties estimated with MD to make them suitable for BTE and (iii) the numerical solution of the BTE using the lattice Boltzmann method (LBM) under the single mode relaxation time approximation subject to different initial and boundary conditions, including non-linear dispersion relations and different polarizations in the [100] direction. Each step of the methodology is validated with numerical, analytical or experimental reported data. In the first step of the methodology, properties such as, phonon relaxation times, dispersion relations, group and phase velocities and specific heat are obtained with MD at of 300 and 1000 K (i.e. molecular temperatures). The estimation of the properties considers the anhamonic nature of the potential energy function, including the thermal expansion of the crystal. Both effects are found to modify the dispersion relations with temperature. The behavior of the phonon relaxation times for each mode (i.e. longitudinal and transverse, acoustic and optical phonons) is identified using power functions. The exponents of the acoustic modes are agree with those predicted theoretically perturbation theory at high temperatures, while those for the optical modes are higher. All properties estimated with MD are validated with values for the thermal conductivity obtained from the Green-Kubo method. It is found that the relative contribution of acoustic modes to the overall thermal conductivity is approximately 90% at both temperatures. In the second step

  15. Hierarchical Organization and Disassortative Mixing of Correlation-Based Weighted Financial Networks

    NASA Astrophysics Data System (ADS)

    Cai, Shi-Min; Zhou, Yan-Bo; Zhou, Tao; Zhou, Pei-Ling

    Correlation-based weighted financial networks are analyzed to present cumulative distribution of strength with a power-law tail, which suggests that a small number of hub-like stocks have greater influence on the whole fluctuation of financial market than others. The relationship between clustering and connectivity of vertices emphasizes hierarchical organization, which has been depicted by minimal span tree in previous work. These results urge us to further study the mixing patter of financial network to understand the tendency for vertices to be connected to vertices that are like (or unlike) them in some way. The measurement of average nearest-neighbor degree running over classes of vertices with degree k shows a descending trend when k increases. This interesting result is first uncovered in our work, and suggests the disassortative mixing of financial network which refers to a bias in favor of connections between dissimilar vertices. All the results in weighted complex network aspect may provide some insights to deeper understand the underlying mechanism of financial market and model the evolution of financial market.

  16. Hierarchical densification and negative thermal expansion in Ce-based metallic glass under high pressure.

    PubMed

    Luo, Qiang; Garbarino, Gaston; Sun, Baoan; Fan, Dawei; Zhang, Yue; Wang, Zhi; Sun, Yajuan; Jiao, Jin; Li, Xiaodong; Li, Pengshan; Mattern, Norbert; Eckert, Jürgen; Shen, Jun

    2015-02-02

    The polyamorphsim in amorphous materials is one of the most fascinating topics in condensed matter physics. In amorphous metals, the nature of polyamorphic transformation is poorly understood. Here we investigate the structural evolution of a Ce-based metallic glass (MG) with pressure at room temperature (RT) and near the glass transition temperature by synchrotron X-ray diffraction, uncovering novel behaviours. The MG shows hierarchical densification processes at both temperatures, arising from the hierarchy of interatomic interactions. In contrast with a continuous and smooth process for the low- to medium-density amorphous state transformation at RT, a relatively abrupt and discontinuous transformation around 5.5 GPa is observed at 390 K, suggesting a possible weak first-order nature. Furthermore, both positive and abnormal-negative thermal expansion behaviours on medium-range order are observed in different pressure windows, which could be related to the low-energy vibrational motions and relaxation of the weakly linked solute-centred clusters.

  17. 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.

  18. Hierarchical patch-based co-registration of differently stained histopathology slides

    NASA Astrophysics Data System (ADS)

    Yigitsoy, Mehmet; Schmidt, Günter

    2017-03-01

    Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

  19. 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."

  20. [Social representations of vaccination among patients and general practitioners: a study based on hierarchized evocation].

    PubMed

    Sardy, Romain; Ecochard, René; Lasserre, Evelyne; Dubois, Jean-Pierre; Floret, Daniel; Letrilliart, Laurent

    2012-01-01

    In France, there is a discrepancy between perceptions and practices related to vaccination, the causes of which are poorly understood. The purpose of this study was to examine and compare patients' and physicians' social representations of vaccination. A qualitative study based on hierarchized evocation was conducted on a sample of 30 patients and 30 general practitioners. The participants were asked to write down seven words or word groups (word associations) induced by the concept of "vaccination" and to rank them in order of importance. The associations were grouped by theme and sub-theme. Their frequency, connotations and importance were compared between the two groups. The results show that, overall, the physicians had a positive view of vaccination, while the patients had a more neutral view (polarity index: + 0.38 vs + 0.07, p < 0.01). Among both patients and general practitioners, vaccination tends to be perceived as a form of medical care mainly targeting children and aimed at prevention, and its effectiveness is considered to be implicit. However, the patients appeared to be more concerned about the potential side effects of certain vaccinations, while the GPs emphasized the harmlessness of vaccination. The participating GPs also tended to take a collective view of vaccination, while some patients criticized the lack of targeted vaccinations. Better communication on these key aspects of representations may help to increase confidence in vaccination and to close the gap between perception and practice.

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

    SciTech Connect

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

    2016-11-01

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

  2. 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

  3. Prolonging the lifetime of wireless sensor networks interconnected to fixed network using hierarchical energy tree based routing algorithm.

    PubMed

    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.

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

    PubMed

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

    2013-08-21

    Superposed cobalt(II)-cobalt(III) layered double hydroxide (Co(II)-Co(III)-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.

  5. 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.

  6. 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.

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

    PubMed

    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.

  8. 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.

  9. Aggregation of polymer-grafted nanoparticles in good solvents: A hierarchical modeling method

    NASA Astrophysics Data System (ADS)

    Cheng, Lisheng; Cao, Dapeng

    2011-09-01

    Brownian dynamics simulations are carried out to study the aggregation behavior of polymer-grafted nanoparticles (NPs) in good solvents by using the coarse-grained model derived from the all-atom force field, according to the hierarchical modeling strategy, and here PEG-grafted gold nanoparticles (GNPs) were taken as an example. Generally, grafting PEG to the surface of GNPs is to protect them from aggregation in the solution. However, our results reveal that PEG-grafted GNPs may also aggregate when concentration increases. Our simulations indicate that there exists a critical aggregating concentration (CAC), beyond which the PEG-grafted GNPs will aggregate. We further check the effects of grafting density and the length of grafted chains on the aggregation behavior of the grafted GNPs, and find that there exists an optimized length of grafted chain, at which the system has the maximal CAC. Furthermore, the aggregate size of self-assembled mesostructures formed by the grafted GNPs increases with the concentration. Interestingly, it is observed that the aggregation favors to form linear gold nanowires rather than compact gold nanoclusters, and the corresponding mechanism is also addressed. It is expected that this work would provide useful information for the fabrication of metal nanowires and the surface modification of metal nanoparticles.

  10. Co3O4-ZnO hierarchical nanostructures by electrospinning and hydrothermal methods

    NASA Astrophysics Data System (ADS)

    Kanjwal, Muzafar A.; Sheikh, Faheem A.; Barakat, Nasser A. M.; Chronakis, Ioannis S.; Kim, Hak Yong

    2011-07-01

    A new hierarchical nanostructure that consists of cobalt oxide (Co3O4) and zinc oxide (ZnO) was produced by the electrospinning process followed by a hydrothermal technique. First, electrospinning of a colloidal solution that consisted of zinc nanoparticles, cobalt acetate tetrahydrate and poly(vinyl alcohol) was performed to produce polymeric nanofibers embedding solid nanoparticles. Calcination of the obtained electrospun nanofiber mats in air at 600 °C for 1 h, produced Co3O4 nanofibers with rough surfaces containing ZnO nanoparticles (i.e., ZnO-doped Co3O4 nanofibers). The rough surfaced nanofibers, containing ZnO nanoparticles (ZnNPs), were then exploited as seeds to produce ZnO nanobranches using a specific hydrothermal technique. Scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were employed to characterize the as-spun nanofibers and the calcined product. X-ray powder diffractometery (XRD) analysis was used to study the chemical composition and the crystallographic structure.

  11. Aggregation of polymer-grafted nanoparticles in good solvents: a hierarchical modeling method.

    PubMed

    Cheng, Lisheng; Cao, Dapeng

    2011-09-28

    Brownian dynamics simulations are carried out to study the aggregation behavior of polymer-grafted nanoparticles (NPs) in good solvents by using the coarse-grained model derived from the all-atom force field, according to the hierarchical modeling strategy, and here PEG-grafted gold nanoparticles (GNPs) were taken as an example. Generally, grafting PEG to the surface of GNPs is to protect them from aggregation in the solution. However, our results reveal that PEG-grafted GNPs may also aggregate when concentration increases. Our simulations indicate that there exists a critical aggregating concentration (CAC), beyond which the PEG-grafted GNPs will aggregate. We further check the effects of grafting density and the length of grafted chains on the aggregation behavior of the grafted GNPs, and find that there exists an optimized length of grafted chain, at which the system has the maximal CAC. Furthermore, the aggregate size of self-assembled mesostructures formed by the grafted GNPs increases with the concentration. Interestingly, it is observed that the aggregation favors to form linear gold nanowires rather than compact gold nanoclusters, and the corresponding mechanism is also addressed. It is expected that this work would provide useful information for the fabrication of metal nanowires and the surface modification of metal nanoparticles. © 2011 American Institute of Physics

  12. Hierarchical QSAR technology based on the Simplex representation of molecular structure

    NASA Astrophysics Data System (ADS)

    Kuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.

    2008-06-01

    This article is about the hierarchical quantitative structure-activity relationship technology (HiT QSAR) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solutions. 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 detailing increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach reported here are the absence of "molecular alignment" problems, consideration of different physical-chemical properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of the HiT QSAR approach is demonstrated by comparing it 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 predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biological experiments, among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a number of useful utilities.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  15. Dry-adhesives based on hierarchical poly(methyl methacrylate) electrospun fibers

    NASA Astrophysics Data System (ADS)

    Sahay, Rahul; Baji, Avinash; Parveen, Hashina; Ranganath, Anupama Sargur

    2017-03-01

    Here, we combine electrospinning and replica-molding to produce hierarchical poly(methyl methacrylate) structures and investigate its adhesion behavior. Normal and shear adhesion of these biomimetic hierarchical structures was measured using nanoindentaton and a custom-built apparatus attached to Zwick tensile testing machine, respectively. Shear adhesion was measured by sliding the samples along the glass slide under a predefined normal preload. Normal adhesion was measured by indenting the surface of the sample with the help of a diamond indenter tip and retracting it back to determine the pull-off force needed to detach it from the sample. These experiments were also conducted on neat PMMA fibers to investigate the effect of hierarchy on the adhesion performance of the samples. Our results show that the shear adhesion strength and pull-off forces recorded for the hierarchical samples are higher than those recorded for neat fibers.

  16. Hierarchical nanosheet-based MoS2/graphene nanobelts with high electrochemical energy storage performance

    NASA Astrophysics Data System (ADS)

    Jia, Yulong; Wan, Hongqi; Chen, Lei; Zhou, Huidi; Chen, Jianmin

    2017-06-01

    Novel hierarchical MoS2/graphene (MoS2/G) nanobelts were synthesized through a facile hydrothermal reaction. In this work, the MoO3 nanobelts and graphene nanosheets played the important roles in the preparation of the nanosheet-built nanobelt architecture. Ascribed to the ordered porous hierarchical nanobelt structure and introduction of graphene, the hybrid electrode exhibits much higher electrochemical capacity than pure MoS2 particles. Moreover, the unique ordered hierarchical architecture could greatly relieve the volume change and stack during the electrochemical process, resulting in the excellent cycling stability. Specifically, the hybrid electrode possesses a capacitance of 445.71 F g-1 at 0.8 A g-1 with a high capacity retention of 96.75% at 2 A g-1 after 1000 cycles.

  17. Durable polyorganosiloxane superhydrophobic films with a hierarchical structure by sol-gel and heat treatment method

    NASA Astrophysics Data System (ADS)

    Jiang, Zhenlin; Fang, Shuying; Wang, Chaosheng; Wang, Huaping; Ji, Chengchang

    2016-12-01

    For a surface to be superhydrophobic a combination of surface roughness and low surface energy is required. In this study, polyorganosiloxane superhydrophobic surfaces were fabricated using a sol-gel and heat treatment process followed by coating with a nanosilica (SiO2) sol and organosiloxane 1, 1, 1, 3, 5, 5, 5-heptamethyl-3-[2-(trimethoxysilyl)ethyl]-trisiloxane (β-HPEOs). The nano-structure was superimposed using self-assembled, surface-modified silica nanoparticles, forming two-dimensional hierarchical structures. The water contact angle (WCA) of polyorganosiloxane superhydrophobic surface was 143.7 ± 0.6°, which was further increased to 156.7 ± 1.1° with water angle hysteresis of 2.5 ± 0.6° by superimposing nanoparticles using a heat treatment process. An analytical characterization of the surface revealed that the nano-silica and polyorganosiloxane formed a micro/nano structure on the films and the wetting behaviour of the films changed from hydrophilic to superhydrophobic. The WCA of these films were 143.7 ± 0.6° and at heat treatment temperatures of less than 400 °C, the WCA increased from 144.5 ± 0.7° to 156.7 ± 1.1°. The prepared superhydrophobic films were stable even after heat treatment at 430 °C for 30 min and their superhydrophobicity was durable for more than 120 days. The effects of heat treatment process on the surface chemistry structure, wettability and morphology of the polyorganosiloxane superhydrophobic films were investigated in detail. The results indicated that the stability of the chemical structure was required to yield a thermally-stable superhydrophobic surface.

  18. Hierarchical Nyström methods for constructing Markov state models for conformational dynamics.

    PubMed

    Yao, Yuan; Cui, Raymond Z; Bowman, Gregory R; Silva, Daniel-Adriano; Sun, Jian; Huang, Xuhui

    2013-05-07

    Markov state models (MSMs) have become a popular approach for investigating the conformational dynamics of proteins and other biomolecules. MSMs are typically built from numerous molecular dynamics simulations by dividing the sampled configurations into a large number of microstates based on geometric criteria. The resulting microstate model can then be coarse-grained into a more understandable macrostate model by lumping together rapidly mixing microstates into larger, metastable aggregates. However, finite sampling often results in the creation of many poorly sampled microstates. During coarse-graining, these states are mistakenly identified as being kinetically important because transitions to/from them appear to be slow. In this paper, we propose a formalism based on an algebraic principle for matrix approximation, i.e., the Nyström method, to deal with such poorly sampled microstates. Our scheme builds a hierarchy of microstates from high to low populations and progressively applies spectral clustering on sets of microstates within each level of the hierarchy. It helps spectral clustering identify metastable aggregates with highly populated microstates rather than being distracted by lowly populated states. We demonstrate the ability of this algorithm to discover the major metastable states on two model systems, the alanine dipeptide and trpzip2 peptide.

  19. Adaptive hierarchical fuzzy controller

    SciTech Connect

    Raju, G.V.S.; Jun Zhou

    1993-07-01

    A methodology for designing adaptive hierarchical fuzzy controllers is presented. In order to evaluate this concept, several suitable performance indices were developed and converted to linguistic fuzzy variables. Based on those variables, a supervisory fuzzy rule set was constructed and used to change the parameters of a hierarchical fuzzy controller to accommodate the variations of system parameters. The proposed algorithm was used in feedwater flow control to a steam generator. Simulation studies are presented that illustrate the effectiveness of the approach

  20. Hierarchical virtual screening approaches in small molecule drug discovery.

    PubMed

    Kumar, Ashutosh; Zhang, Kam Y J

    2015-01-01

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

  1. 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.

  2. 3-D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization.

    PubMed

    Noblet, Vincent; Heinrich, Christian; Heitz, Fabrice; Armspach, Jean-Paul

    2005-05-01

    This paper deals with topology preservation in three-dimensional (3-D) deformable image registration. This work is a nontrivial extension of, which addresses the case of two-dimensional (2-D) topology preserving mappings. In both cases, the deformation map is modeled as a hierarchical displacement field, decomposed on a multiresolution B-spline basis. Topology preservation is enforced by controlling the Jacobian of the transformation. Finding the optimal displacement parameters amounts to solving a constrained optimization problem: The residual energy between the target image and the deformed source image is minimized under constraints on the Jacobian. Unlike the 2-D case, in which simple linear constraints are derived, the 3-D B-spline-based deformable mapping yields a difficult (until now, unsolved) optimization problem. In this paper, we tackle the problem by resorting to interval analysis optimization techniques. Care is taken to keep the computational burden as low as possible. Results on multipatient 3-D MRI registration illustrate the ability of the method to preserve topology on the continuous image domain.

  3. Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

    PubMed

    Pagni, Marco; Niculita-Hirzel, Hélène; Pellissier, Loïc; Dubuis, Anne; Xenarios, Ioannis; Guisan, Antoine; Sanders, Ian R; Goudet, Jérôme; Guex, Nicolas

    2013-05-15

    Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.

  4. 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...

  5. 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...

  6. 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.

  7. 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.

  8. Template-directed hierarchical self-assembly of graphene based hybrid structure for electrochemical biosensing.

    PubMed

    Parlak, Onur; Tiwari, Atul; Turner, Anthony P F; Tiwari, Ashutosh

    2013-11-15

    A template-directed self-assembly approach, using functionalised graphene as a fundamental building block to obtain a hierarchically ordered graphene-enzyme-nanoparticle bioelectrode for electrochemical biosensing, is reported. An anionic surfactant was used to prepare a responsive, functional interface and direct the assembly on the surface of the graphene template. The surfactant molecules altered the electrostatic charges of graphene, thereby providing a convenient template-directed assembly approach to a free-standing planar sheet of sp(2) carbons. Cholesterol oxidase and cholesterol esterase were assembled on the surface of graphene by intermolecular attractive forces while gold nanoparticles are incorporated into the hetero-assembly to enhance the electro-bio-catalytic activity. Hydrogen peroxide and cholesterol were used as two representative analytes to demonstrate the electrochemical sensing performance of the graphene-based hybrid structure. The bioelectrode exhibited a linear response to H2O2 from 0.01 to 14 mM, with a detection limit of 25 nM (S/N=3). The amperometric response with cholesterol had a linear range from 0.05 to 0.35 mM, sensitivity of 3.14 µA/µM/cm(2) and a detection limit of 0.05 µM. The apparent Michaelis-Menten constant (Km(app)) was calculated to be 1.22 mM. This promising approach provides a novel methodology for template-directed bio-self-assembly over planar sp(2) carbons of a graphene sheet and furnishes the basis for fabrication of ultra-sensitive and efficient electrochemical biosensors. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. 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.

  10. Reliability optimization design of distribution systems via multi-level hierarchical procedures and generalized reduced gradient method

    SciTech Connect

    Su, C.T.; Lii, G.R.

    1995-12-31

    The purpose of this paper is to develop an optimization method for reliable design of substations. Reliability indices used are failure rate and interruption duration, which are commonly used in the distribution systems. Through applying the proposed method, the optimal reliability indices of apparatus are obtained, which minimize the total cost comprising apparatus investment cost and interruption cost, and also satisfy reliability constraints of load point. Three kinds of interruption cost including initial interruption cost, outage frequency cost and interruption duration cost are considered. The optimization technique employed in this paper to solve the nonlinear programming problems is the Generalized Reduced Gradient (GRG) method. For simplification of computation of large or complex systems, the multi-level hierarchical optimization is applied. It starts by dividing the system into several subsystems, and finds the optimal reliability indices for subsystems. Then by repeatedly taking the previous subsystem as the following system and the previous constituent as the following subsystem, and applying the GRG method, the authors can finally find the desired reliability indices for components of the primitive system. To demonstrate the application of the method, a secondary substation of the Taiwan Power Company is taken as an example, computation results of the application example show that the interruption cost is effectively reduced. The proposed method is applicable to existing substation expansion and new substation establishment.

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

    Treesearch

    Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

    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...

  12. 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…

  13. 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…

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

    ERIC Educational Resources Information Center

    Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

    1998-01-01

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

  15. Aspects Of Multicriterial Mathematical Modeling And Of The Fuzzy Formalism For The Hierarchization Of Study Programs Based On Several Quality Characteristics

    NASA Astrophysics Data System (ADS)

    Bucur, Amelia

    2015-09-01

    The aim of this paper is to present aspects of mathematical modeling for the hierarchization of study programs from universities, based on several quality characteristics. The tools used pertain to multicriterial optimization, to the different methods of assessing importance coefficients, to the utility theory, the fuzzy formalism, and to the fuzzy simple additive weighting method. The conclusion is that multicriterial decision-making methods can be efficiently used in assessing the quality of study programs, noting that, just like other methods from the decision theory, the multicriterial decision-making methods highlight aspects of problems differently, therefore, there can be no comparison or competitiveness between them, and choosing one over the other is up to the decision-maker.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  17. 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.

  18. Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams.

    PubMed

    Adams, Roy J; Saleheen, Nazir; Thomaz, Edison; Parate, Abhinav; Kumar, Santosh; Marlin, Benjamin M

    2016-06-01

    The field of mobile health (mHealth) has the potential to yield new insights into health and behavior through the analysis of continuously recorded data from wearable health and activity sensors. In this paper, we present a hierarchical span-based conditional random field model for the key problem of jointly detecting discrete events in such sensor data streams and segmenting these events into high-level activity sessions. Our model includes higher-order cardinality factors and inter-event duration factors to capture domain-specific structure in the label space. We show that our model supports exact MAP inference in quadratic time via dynamic programming, which we leverage to perform learning in the structured support vector machine framework. We apply the model to the problems of smoking and eating detection using four real data sets. Our results show statistically significant improvements in segmentation performance relative to a hierarchical pairwise CRF.

  19. Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams

    PubMed Central

    Adams, Roy J.; Saleheen, Nazir; Thomaz, Edison; Parate, Abhinav; Kumar, Santosh; Marlin, Benjamin M.

    2016-01-01

    The field of mobile health (mHealth) has the potential to yield new insights into health and behavior through the analysis of continuously recorded data from wearable health and activity sensors. In this paper, we present a hierarchical span-based conditional random field model for the key problem of jointly detecting discrete events in such sensor data streams and segmenting these events into high-level activity sessions. Our model includes higher-order cardinality factors and inter-event duration factors to capture domain-specific structure in the label space. We show that our model supports exact MAP inference in quadratic time via dynamic programming, which we leverage to perform learning in the structured support vector machine framework. We apply the model to the problems of smoking and eating detection using four real data sets. Our results show statistically significant improvements in segmentation performance relative to a hierarchical pairwise CRF. PMID:28090606

  20. Carbon nanotube-based polymer nanocomposites: Fractal network to hierarchical morphology

    NASA Astrophysics Data System (ADS)

    Chatterjee, Tirtha

    scales related to the process are independent of it. For fully grown network in a viscous polymer, cluster dynamics under external shear controls the non-linear behavior of the system. Significant changes in the melting and crystallization behavior of poly(ethylene oxide) along with a decrease in fractional crystallinity has been observed, in these nanocomposites. The observed changes in the SWNT-based nanocomposites far exceed those observed for an equivalent Li+ ion concentration mixture. The identification of the nature of nanotube-polymer interactions and the nanotube's role during polymer crystallization provide the possibility of developing hierarchical materials with controlled multifunctional properties whose directionality can be easily manipulated. For the case where the nanotubes disturb the formation of polymer crystals, the oriented nanotubes, because of the short inter-tube distances even at low nanotube concentrations, cause a templating of the polymer crystals with the lamellar---normals oriented orthogonal to the nanotube axes. On the other hand for the case where nanotubes nucleate the polymer crystals, a "shish---kebab" structure is realized, with the nanotubes and polymer crystals acting as the shish and kebab, respectively.

  1. 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

  2. Hierarchical auxetic mechanical metamaterials.

    PubMed

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

    2015-02-11

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

  3. Hierarchical Auxetic Mechanical Metamaterials

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  4. 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

  5. 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.

  6. 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

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

    PubMed

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

    2014-06-01

    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

  8. Modified distance in average linkage based on M-estimator and MADn criteria in hierarchical cluster analysis

    NASA Astrophysics Data System (ADS)

    Muda, Nora; Othman, Abdul Rahman

    2015-10-01

    The process of grouping a set of objects into classes of similar objects is called clustering. It divides a large group of observations into smaller groups so that the observations within each group are relatively similar and the observations in different groups are relatively dissimilar. In this study, an agglomerative method in hierarchical cluster analysis is chosen and clusters were constructed by using an average linkage technique. An average linkage technique requires distance between clusters, which is calculated based on the average distance between all pairs of points, one group with another group. In calculating the average distance, the distance will not be robust when there is an outlier. Therefore, the average distance in average linkage needs to be modified in order to overcome the problem of outlier. Therefore, the criteria of outlier detection based on MADn criteria is used and the average distance is recalculated without the outlier. Next, the distance in average linkage is calculated based on a modified one step M-estimator (MOM). The groups of cluster are presented in dendrogram graph. To evaluate the goodness of a modified distance in the average linkage clustering, the bootstrap analysis is conducted on the dendrogram graph and the bootstrap value (BP) are assessed for each branch in dendrogram that formed the group, to ensure the reliability of the branches constructed. This study found that the average linkage technique with modified distance is significantly superior than the usual average linkage technique, if there is an outlier. Both of these techniques are said to be similar if there is no outlier.

  9. Bayesian system identification based on hierarchical sparse Bayesian learning and Gibbs sampling with application to structural damage assessment

    NASA Astrophysics Data System (ADS)

    Huang, Yong; Beck, James L.; Li, Hui

    2017-05-01

    The focus in this paper is Bayesian system identification based on noisy incomplete modal data where we can impose spatially-sparse stiffness changes when updating a structural model. To this end, based on a similar hierarchical sparse Bayesian learning model from our previous work, we propose two Gibbs sampling algorithms. The algorithms differ in their strategies to deal with the posterior uncertainty of the equation-error precision parameter, but both sample from the conditional posterior probability density functions (PDFs) for the structural stiffness parameters and system modal parameters. The effective dimension for the Gibbs sampling is low because iterative sampling is done from only three conditional posterior PDFs that correspond to three parameter groups, along with sampling of the equation-error precision parameter from another conditional posterior PDF in one of the algorithms where it is not integrated out as a "nuisance" parameter. A nice feature from a computational perspective is that it is not necessary to solve a nonlinear eigenvalue problem of a structural model. The effectiveness and robustness of the proposed algorithms are illustrated by applying them to the IASE-ASCE Phase II simulated and experimental benchmark studies. The goal is to use incomplete modal data identified before and after possible damage to detect and assess spatially-sparse stiffness reductions induced by any damage. Our past and current focus on meeting challenges arising from Bayesian inference of structural stiffness serve to strengthen the capability of vibration-based structural system identification but our methods also have much broader applicability for inverse problems in science and technology where system matrices are to be inferred from noisy partial information about their eigenquantities.

  10. Population trends for North American winter birds based on hierarchical models

    USGS Publications Warehouse

    Soykan, Candan U.; Sauer, John; Schuetz, Justin G.; LeBaron, Geoffrey S.; Dale, Kathy; Langham, Gary M.

    2016-01-01

    Managing widespread and persistent threats to birds requires knowledge of population dynamics at large spatial and temporal scales. For over 100 yrs, the Audubon Christmas Bird Count (CBC) has enlisted volunteers in bird monitoring efforts that span the Americas, especially southern Canada and the United States. We employed a Bayesian hierarchical model to control for variation in survey effort among CBC circles and, using CBC data from 1966 to 2013, generated early-winter population trend estimates for 551 species of birds. Selecting a subset of species that do not frequent bird feeders and have ≥25% range overlap with the distribution of CBC circles (228 species) we further estimated aggregate (i.e., across species) trends for the entire study region and at the level of states/provinces, Bird Conservation Regions, and Landscape Conservation Cooperatives. Moreover, we examined the relationship between ten biological traits—range size, population size, migratory strategy, habitat affiliation, body size, diet, number of eggs per clutch, age at sexual maturity, lifespan, and tolerance of urban/suburban settings—and CBC trend estimates. Our results indicate that 68% of the 551 species had increasing trends within the study area over the interval 1966–2013. When trends were examined across the subset of 228 species, the median population trend for the group was 0.9% per year at the continental level. At the regional level, aggregate trends were positive in all but a few areas. Negative population trends were evident in lower latitudes, whereas the largest increases were at higher latitudes, a pattern consistent with range shifts due to climate change. Nine of 10 biological traits were significantly associated with median population trend; however, none of the traits explained >34% of the deviance in the data, reflecting the indirect relationships between population trend estimates and species traits. Trend estimates based on the CBC are broadly congruent with

  11. Accounting hierarchical heterogeneity of rock during its working off by explosive methods

    NASA Astrophysics Data System (ADS)

    Hachay, Olga; Khachay, Oleg

    2017-04-01

    . Because the information about the structure and state of the environment can be obtained from the geophysical data by interpreting them in frames of the model, which is an approximation to the real environment, therefore you must select it from the class of physically and geologically reasonable. For a description of the geological environment in the form of a rock massif with its natural and technogenic heterogeneity we should use more adequate description as is a discrete model of the environment in the form of a piece wise non-homogeneous block media with embedded heterogeneities of lower rank than the block size . This nesting can be traced back several times, ie, changing the scale of the study, we see that the heterogeneity of lower rank now appear as blocks for the irregularities of the next rank. The simple average of the measured geophysical parameters can lead to a distorted view of the structure of the environment and its evolution. The Institute of Geophysics, UB RAS has developed a hardware-methodological and interpretative system for studying the structure and state of complex geological environment, which has the potential instability and the ability to rebuild the hierarchy structure with significant external influence. The basis of this complex is the developed 3-D technique planshet electromagnetic induction studies in frequency geometrical variant, resting on one side on the interpretation software system for 3-D alternating electromagnetic fields, and on the other hand on developed by Ph.D. A.I.Chelovechkov device for carrying out the inductive research. On the basis of this technology the active monitoring of the structure and state of the rock massif inside the mines of different material composition can be provided, it can be carried out to detect short-term precursors of strong dynamic phenomena according to the electromagnetic induction monitoring. There are developed algorithms for modeling of electromagnetic fields in hierarchic heterogeneous

  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. 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.

  15. The Effects of Method of Hierarchical Organization and Sequence on Children's Learning.

    ERIC Educational Resources Information Center

    Parker, DeAnsin Goodson

    This study focused on Robert Gagne's method for curricular development, which consists of structuring a knowledge domain into a learning hierarchy. Two methods of generating learning hierarchies and two different sequencings of these hierarchies were compared and their effects were measured. Four programmed texts were developed from two different…

  16. 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

  17. 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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  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. Parallel hierarchical radiosity rendering

    SciTech Connect

    Carter, Michael

    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.

  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. 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.

  2. 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.

  3. 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…

  4. 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…

  5. Microparticles with hierarchical porosity

    DOEpatents

    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.

  6. Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset

    PubMed Central

    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. PMID:24130686

  7. 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.

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

    SciTech Connect

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

    2014-02-15

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

  9. Hierarchical assembly of BiOCl nanosheets onto bicrystalline TiO2 nanofiber: enhanced photocatalytic activity based on photoinduced interfacial charge transfer.

    PubMed

    Li, Lu; Zhang, Mingyi; Liu, Ying; Zhang, Xitian

    2014-12-01

    One-dimensional ternary hierarchical heterostructures based on BiOCl nanosheets and bicrystalline TiO2 nanofiber frameworks that consist of anatase-rutile (AR) mixed phase TiO2 nanoparticles were successfully designed by combining the electrospinning technique and solvothermal method. The BiOCl nanosheets were uniformly grown onto the electrospun TiO2 nanofibers, and the density of the secondary BiOCl nanosheets could be controlled by adjusting the precursor concentration. Photocatalytic tests displayed that the ternary BiOCl/TiO2 (AR) hierarchical heterostructures possessed a much higher degradation rate than the bare bicrystalline TiO2 (AR) nanofibers, BiOCl/TiO2 (A) or BiOCl/TiO2 (R) composite. It is mainly attributed to the photogenerated interfacial charge transfer based on the photosynergistic effect of the heterojunctions, which results in the high separation efficiency of photogenerated electron-hole pairs. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Hierarchical Theoretical Methods for Understanding and Predicting Anisotropic Thermal Transport Release in Rocket Propellant Formulations

    DTIC Science & Technology

    2016-12-08

    on intelligently designed polymer nanocomposite formulations augmented by non-traditional additives or passivation agents, possibly coupled to...Fundamental information from atomic-scale simulations o Nanoparticles and bulk o Interfaces • Detailed continuum-based mesoscopic models of interfaces and...a) Electric on Diffusion Flames: Matalon and his collaborators [2] carried out a precursor study where they analyze ionic transport through the non

  11. 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.

  12. 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.

  13. Mapping Rule-Based And Stochastic Constraints To Connection Architectures: Implication For Hierarchical Image Processing

    NASA Astrophysics Data System (ADS)

    Miller, Michael I.; Roysam, Badrinath; Smith, Kurt R.

    1988-10-01

    Essential to the solution of ill posed problems in vision and image processing is the need to use object constraints in the reconstruction. While Bayesian methods have shown the greatest promise, a fundamental difficulty has persisted in that many of the available constraints are in the form of deterministic rules rather than as probability distributions and are thus not readily incorporated as Bayesian priors. In this paper, we propose a general method for mapping a large class of rule-based constraints to their equivalent stochastic Gibbs' distribution representation. This mapping allows us to solve stochastic estimation problems over rule-generated constraint spaces within a Bayesian framework. As part of this approach we derive a method based on Langevin's stochastic differential equation and a regularization technique based on the classical autologistic transfer function that allows us to update every site simultaneously regardless of the neighbourhood structure. This allows us to implement a completely parallel method for generating the constraint sets corresponding to the regular grammar languages on massively parallel networks. We illustrate these ideas by formulating the image reconstruction problem based on a hierarchy of rule-based and stochastic constraints, and derive a fully parallelestimator structure. We also present results computed on the AMT DAP500 massively parallel digital computer, a mesh-connected 32x32 array of processing elements which are configured in a Single-Instruction, Multiple Data stream architecture.

  14. SAR-based terrain classification using weakly supervised hierarchical Markov aspect models.

    PubMed

    Yang, Wen; Dai, Dengxin; Triggs, Bill; Xia, Gui-Song

    2012-09-01

    We introduce the hierarchical Markov aspect model (HMAM), a computationally efficient graphical model for densely labeling large remote sensing images with their underlying terrain classes. HMAM resolves local ambiguities efficiently by combining the benefits of quadtree representations and aspect models-the former incorporate multiscale visual features and hierarchical smoothing to provide improved local label consistency, while the latter sharpen the labelings by focusing them on the classes that are most relevant for the broader local image context. The full HMAM model takes a grid of local hierarchical Markov quadtrees over image patches and augments it by incorporating a probabilistic latent semantic analysis aspect model over a larger local image tile at each level of the quadtree forest. Bag-of-word visual features are extracted for each level and patch, and given these, the parent-child transition probabilities from the quadtree and the label probabilities from the tile-level aspect models, an efficient forwards-backwards inference pass allows local posteriors for the class labels to be obtained for each patch. Variational expectation-maximization is then used to train the complete model from either pixel-level or tile-keyword-level labelings. Experiments on a complete TerraSAR-X synthetic aperture radar terrain map with pixel-level ground truth show that HMAM is both accurate and efficient, providing significantly better results than comparable single-scale aspect models with only a modest increase in training and test complexity. Keyword-level training greatly reduces the cost of providing training data with little loss of accuracy relative to pixel-level training.

  15. Hierarchical modelling of elastic behaviour of human enamel based on synchrotron diffraction characterisation.

    PubMed

    Sui, Tan; Sandholzer, Michael A; Baimpas, Nikolaos; Dolbnya, Igor P; Landini, Gabriel; Korsunsky, Alexander M

    2013-11-01

    Human enamel is a hierarchical mineralized tissue with a two-level composite structure. Few studies have focused on the structure-mechanical property relationship and its link to the multi-scale architecture of human enamel, whereby the response to mechanical loading is affected not only by the rod distribution at micro-scale, but also strongly influenced by the mineral crystallite shape, and spatial arrangement and orientation. In this study, two complementary synchrotron X-ray diffraction techniques, wide and small angle X-ray scattering (WAXS/SAXS) were used to obtain multi-scale quantitative information about the structure and deformation response of human enamel to in situ uniaxial compressive loading. The apparent modulus was determined linking the external load and the internal strain in hydroxyapatite (HAp) crystallites. An improved multi-scale Eshelby model is proposed taking into account the two-level hierarchical structure of enamel. This framework has been used to analyse the experimental data for the elastic lattice strain evolution within the HAp crystals. The achieved agreement between the model prediction and experiment along the loading direction validates the model and suggests that the new multi-scale approach reasonably captures the structure-property relationship for the human enamel. The ability of the model to predict multi-directional strain components is also evaluated by comparison with the measurements. The results are useful for understanding the intricate relationship between the hierarchical structure and the mechanical properties of enamel, and for making predictions of the effect of structural alterations that may occur due to the disease or treatment on the performance of dental tissues and their artificial replacements.

  16. 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

    2015-02-03

    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.

  17. Biomimetic hydrophobic surface fabricated by chemical etching method from hierarchically structured magnesium alloy substrate

    NASA Astrophysics Data System (ADS)

    Liu, Yan; Yin, Xiaoming; Zhang, Jijia; Wang, Yaming; Han, Zhiwu; Ren, Luquan

    2013-09-01

    As one of the lightest metal materials, magnesium alloy plays an important role in industry such as automobile, airplane and electronic product. However, magnesium alloy is hindered due to its high chemical activity and easily corroded. Here, inspired by typical plant surfaces such as lotus leaves and petals of red rose with super-hydrophobic character, the new hydrophobic surface is fabricated on magnesium alloy to improve anti-corrosion by two-step methodology. The procedure is that the samples are processed by laser first and then immersed and etched in the aqueous AgNO3 solution concentrations of 0.1 mol/L, 0.3 mol/L and 0.5 mol/L for different times of 15 s, 40 s and 60 s, respectively, finally modified by DTS (CH3(CH2)11Si(OCH3)3). The microstructure, chemical composition, wettability and anti-corrosion are characterized by means of SEM, XPS, water contact angle measurement and electrochemical method. The hydrophobic surfaces with microscale crater-like and nanoscale flower-like binary structure are obtained. The low-energy material is contained in surface after DTS treatment. The contact angles could reach up to 138.4 ± 2°, which hydrophobic property is both related to the micro-nano binary structure and chemical composition. The results of electrochemical measurements show that anti-corrosion property of magnesium alloy is improved. Furthermore, our research is expected to create some ideas from natural enlightenment to improve anti-corrosion property of magnesium alloy while this method can be easily extended to other metal materials.

  18. 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

  19. High-resolution numerical methods for compressible multi-phase flow in hierarchical porous media. Progress report

    SciTech Connect

    Trangenstein, J.A.

    1993-03-15

    This is the first year in the proposed three-year effort to develop high-resolution numerical methods for multi-phase flow in hierarchical porous media. The issues being addressed in this research are: Computational efficiency: Field-scale simulation of enhanced oil recovery, whether for energy production or aquifer remediation, is typically highly under-resolved. This is because rock transport properties vary on many scales, and because current numerical methods have low resolution. Effective media properties: Since porous media are formed through complex geologic processes, they involve significant uncertainty and scale-dependence. Given this uncertainty, knowledge of ensemble averages of flow in porous media can be preferable to knowledge of flow in specific realizations of the reservoir. However, current models of effective properties do not represent the observed behavior very well. Relative permeability models present a good example of this problem. In practice, these models seldom provide realistic representations of hysteresis, interfacial tension effects or three-phase flow; there are no models that represent well all three effects simultaneously. Wave propagation: It is common in the petroleum industry to assume that the models have the same well-posedness properties as the physical system. An example of this fallacy is given by the three-phase relative permeability models; they were widely assumed by the petroleum community to produce hyperbolic systems for the Buckley-Leverett equations, but later the mathematics community proved that these models inherently produce local elliptic regions. Since numerical methods must use the models for computations, oscillations that develop could erroneously be attributed to numerical error rather than modeling difficulties. During this year, we have made significant progress on several tasks aimed at addressing these issues.

  20. 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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. 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.

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

    PubMed

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

    2017-05-01

    With the rapid development of stretchable electronics, functional textiles, and flexible sensors, water-proof protection materials are required to be built on various highly flexible substrates. However, maintaining the antiwetting of superhydrophobic surface under stretching is still a big challenge since the hierarchical structures at hybridized micro-nanoscales are easily damaged following large deformation of the substrates. This study reports a highly stretchable and mechanically stable superhydrophobic surface prepared by a facile spray coating of carbon black/polybutadiene elastomeric composite on a rubber substrate followed by thermal curing. The resulting composite coating can maintain its superhydrophobic property (water contact angle ≈170° and sliding angle <4°) at an extremely large stretching strain of up to 1000% and can withstand 1000 stretching-releasing cycles without losing its superhydrophobic property. Furthermore, the experimental observation and modeling analysis reveal that the stable superhydrophobic properties of the composite coating are attributed to the unique self-adaptive deformation ability of 3D hierarchical roughness of the composite coating, which delays the Cassie-Wenzel transition of surface wetting. In addition, it is first observed that the damaged coating can automatically recover its superhydrophobicity via a simple stretching treatment without incorporating additional hydrophobic materials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Polymer nanocomposites with graphene-based hierarchical fillers as materials for multifunctional water treatment membranes.

    PubMed

    Crock, Christopher A; Rogensues, Adam R; Shan, Wenqian; Tarabara, Volodymyr V

    2013-08-01

    Phase inversion of polymer casting mixtures filled with hierarchical functional nanostructures is proposed as a synthetic route for the design of multifunctional membranes. The study tested the hypothesis that by regulating the relative content of components representing different levels in the nanofiller hierarchy, the structure and additional functions of such membranes could be controlled separately. Exfoliated graphite nanoplatelets (xGnPs) decorated by Au nanoparticles (Au NPs), used as a model hierarchical nanofiller, were added to the casting mixture of polysulfone, N-Methyl-2-pyrrolidone and polyethylene glycol prior to forming the membrane by phase inversion. The resulting porous asymmetric nanocomposites were shown to be permselective and catalytically active ultrafiltration membranes that were more resistant to compaction, more permeable than xGnP-free membranes and at least as selective. By designing membrane compositions with different relative amounts of Au-decorated xGnPs and Au-free xGnPs, the structure (controlled by the loading of xGnPs) and catalytic activity (controlled by the loading of Au NPs) could be controlled largely independently. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Associative Hierarchical Random Fields.

    PubMed

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

    2014-06-01

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

  6. 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…

  7. 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.

  8. 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

  9. 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

    2015-06-07

    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.

  10. 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.

  11. Poisson-based self-organizing feature maps and hierarchical clustering for serial analysis of gene expression data.

    PubMed

    Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

    2007-01-01

    Serial analysis of gene expression (SAGE) is a powerful technique for global gene expression profiling, allowing simultaneous analysis of thousands of transcripts without prior structural and functional knowledge. Pattern discovery and visualization have become fundamental approaches to analyzing such large-scale gene expression data. From the pattern discovery perspective, clustering techniques have received great attention. However, due to the statistical nature of SAGE data (i.e., underlying distribution), traditional clustering techniques may not be suitable for SAGE data analysis. Based on the adaptation and improvement of Self-Organizing Maps and hierarchical clustering techniques, this paper presents two new clustering algorithms, namely, PoissonS and PoissonHC, for SAGE data analysis. Tested on synthetic and experimental SAGE data, these algorithms demonstrate several advantages over traditional pattern discovery techniques. The results indicate that, by incorporating statistical properties of SAGE data, PoissonS and PoissonHC, as well as a hybrid approach (neuro-hierarchical approach) based on the combination of PoissonS and PoissonHC, offer significant improvements in pattern discovery and visualization for SAGE data. Moreover, a user-friendly platform, which may improve and accelerate SAGE data mining, was implemented. The system is freely available on request from the authors for nonprofit use.

  12. 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.

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

    PubMed Central

    2015-01-01

    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

  14. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    PubMed

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM2.5 is a promising way to fill the areas that are not covered by ground PM2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R(2) = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM2.5 estimates.

  15. Fast lithium intercalation chemistry of the hierarchically porous Li2FeP2O7/C composite prepared by an iron-reduction method

    NASA Astrophysics Data System (ADS)

    Tan, L.; Zhang, S.; Deng, C.

    2015-02-01

    Lithium iron pyrophosphate has drawn great attention because of its interesting physical and electrochemical properties, whereas its high rate capability is far from satisfactory. We synthesize nano-Li2FeP2O7/C with hierarchical pore via a low cost method which uses iron powder instead of Vitamin C as the reducing agent. The hierarchical pore is constructed through a "combustion" mechanism according to the thermogravimetric and morphological characterizations. The phase-pure nanoparticles of Li2FeP2O7 are embedded in the three-dimensional network of amorphous carbon. The hierarchical pore together with the two-dimensional diffusion channel of lithium in Li2FeP2O7 is beneficial to lithium diffusion capability which is evaluated by the lithium diffusion coefficients calculated from the results of GITT measurements. The fast lithium intercalation chemistry facilitates the reversible de/intercalation of lithium, resulting in the high cycling stability and rate-capability. After 100 cycles at the current density of 1C, 93.8% of the initial capacity is retained. The discharge capacity is 62.1 mAh g-1 at the current density of 4C. Therefore, the hierarchically porous nano-Li2FeP2O7/C is a promising cathode material for advanced rechargeable lithium ion battery.

  16. Hierarchical optimization for neutron scattering problems

    SciTech Connect

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

    2016-06-15

    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.

  17. Hierarchical optimization for neutron scattering problems

    SciTech Connect

    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.

  18. Hierarchical optimization for neutron scattering problems

    DOE PAGES

    Bao, Feng; Archibald, Rick; Bansal, Dipanshu; ...

    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.

  19. Hierarchical Porous Structures

    SciTech Connect

    Grote, Christopher John

    2016-06-07

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

  20. 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.

  1. 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.

    2013-09-01

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

  2. 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.

  3. 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

  4. 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

  5. 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

    2016-07-07

    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.

  6. A hierarchical preconditioner for the electric field integral equation on unstructured meshes based on primal and dual Haar bases

    NASA Astrophysics Data System (ADS)

    Adrian, S. B.; Andriulli, F. P.; Eibert, T. F.

    2017-02-01

    A new hierarchical basis preconditioner for the electric field integral equation (EFIE) operator is introduced. In contrast to existing hierarchical basis preconditioners, it works on arbitrary meshes and preconditions both the vector and the scalar potential within the EFIE operator. This is obtained by taking into account that the vector and the scalar potential discretized with loop-star basis functions are related to the hypersingular and the single layer operator (i.e., the well known integral operators from acoustics). For the single layer operator discretized with piecewise constant functions, a hierarchical preconditioner can easily be constructed. Thus the strategy we propose in this work for preconditioning the EFIE is the transformation of the scalar and the vector potential into operators equivalent to the single layer operator and to its inverse. More specifically, when the scalar potential is discretized with star functions as source and testing functions, the resulting matrix is a single layer operator discretized with piecewise constant functions and multiplied left and right with two additional graph Laplacian matrices. By inverting these graph Laplacian matrices, the discretized single layer operator is obtained, which can be preconditioned with the hierarchical basis. Dually, when the vector potential is discretized with loop functions, the resulting matrix can be interpreted as a hypersingular operator discretized with piecewise linear functions. By leveraging on a scalar Calderón identity, we can interpret this operator as spectrally equivalent to the inverse single layer operator. Then we use a linear-in-complexity, closed-form inverse of the dual hierarchical basis to precondition the hypersingular operator. The numerical results show the effectiveness of the proposed preconditioner and the practical impact of theoretical developments in real case scenarios.

  7. 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

  8. Analysis of various factors affecting the non-Markovian dynamics associated with a hierarchical environment based on collision model

    NASA Astrophysics Data System (ADS)

    Wang, Chao-Quan; Zou, Jian; Shao, Bin

    2017-06-01

    We propose a quantum collision model in which the environment is abstractively divided into two hierarchies including "environment-bus" that has direct interactions with the system and "environment-stations" that has not. Based on the model, we investigate the effects of initial system-environment correlations, initial states of environment, and various interactions on the dynamics of open quantum systems associated genuinely with such a hierarchical environment. We illustrate that the initial quantum correlation between the system and environment leads to a transition from Markovian to non-Markovian dynamics, while for initial classical correlation the transition can only be confirmed to happen when the couplings rather than the correlations in environment are present. In addition, we investigate the degree of non-Markovianity varying with environment initial states and reveal that the interaction strength between two environmental hierarchies plays an important role in it. In particular, we show that in such a hierarchically structured environment the degree of non-Markovianity is not equivalent to memory effects of the environment-stations as a reservoir due to the presence of the environment-bus.

  9. Clinical, laboratory, and demographic determinants of hospitalization due to dengue in 7613 patients: A retrospective study based on hierarchical models.

    PubMed

    da Silva, Natal Santos; Undurraga, Eduardo A; da Silva Ferreira, Elis Regina; Estofolete, Cássia Fernanda; Nogueira, Maurício Lacerda

    2017-09-28

    In Brazil, the incidence of hospitalization due to dengue, as an indicator of severity, has drastically increased since 1998. The objective of our study was to identify risk factors associated with subsequent hospitalization related to dengue. We analyzed 7613 dengue confirmed via serology (ELISA), non-structural protein 1, or polymerase chain reaction amplification. We used a hierarchical framework to generate a multivariate logistic regression based on a variety of risk variables. This was followed by multiple statistical analyses to assess hierarchical model accuracy, variance, goodness of fit, and whether or not this model reliably represented the population. The final model, which included age, sex, ethnicity, previous dengue infection, hemorrhagic manifestations, plasma leakage, and organ failure, showed that all measured parameters, with the exception of previous dengue, were statistically significant. The presence of organ failure was associated with the highest risk of subsequent dengue hospitalization (OR=5·75; CI=3·53-9·37). Therefore, plasma leakage and organ failure were the main indicators of hospitalization due to dengue, although other variables of minor importance should also be considered to refer dengue patients to hospital treatment, which may lead to a reduction in avoidable deaths as well as costs related to dengue. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

    PubMed Central

    Freitas, Tracey Allen K.; Li, Po-E; Scholz, Matthew B.; Chain, Patrick S. G.

    2015-01-01

    A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. PMID:25765641

  11. Forming Simulations of MMC Components by a Micromechanics Based Hierarchical FEM Approach

    SciTech Connect

    Huber, C. O.; Pettermann, H. E.; Nogales, S.; Boehm, H. J.

    2007-05-17

    The present work deals with computational simulations of an elastoplastic particulate metal matrix composite undergoing finite strains. Two different approaches are utilized for homogenization and localization; an analytical constitutive material law based on a mean field approach, and a periodic unit cell method. Investigations are performed on different length scales. The Finite Element Method is employed to predict the macroscopic response of a component made from a metal matrix composite. Its constitutive material law, based on the incremental Mori Tanaka approach, has been implemented into an Finite Element Method package, and is extended to the finite strain regime. This approach gives access to the mesoscale fields as well as to approximations for the microscale fields in the individual phases of the composite. Selected locations within the macroscopic model are chosen and their entire mesoscopic deformation history is applied to unit cells using the periodic microfield approach. As a result, mesoscopic responses as well as highly resolved microfields are available. A Gleeble-type experiment employing a metal matrix composite with 20vol% of particles is investigated as an example. Comparison of the composite's effective response exhibits excellent agreement in the deformation as well as stress and strain fields, which qualifies the incremental Mori Tanaka approach as appropriate constitutive law for the studied application. For detailed predictions of the fluctuating fields in the matrix and the particles the unit cell approach is employed.

  12. Hierarchical Model Predictive Image-Based Visual Servoing of Underwater Vehicles With Adaptive Neural Network Dynamic Control.

    PubMed

    Gao, Jian; Proctor, Alison A; Shi, Yang; Bradley, Colin

    2016-10-01

    This paper proposes a hierarchical image-based visual servoing (IBVS) strategy for dynamic positioning of a fully actuated underwater vehicle. In the kinematic loop, the desired velocity is generated by a nonlinear model predictive controller, which optimizes a cost function of the predicted image trajectories under the constraints of visibility and velocity. A velocity reference model, representing the desired closed-loop vehicle dynamics, is integrated with an IBVS kinematic model to predict the future trajectories. In the dynamic velocity tracking loop, a neural-network-based model reference adaptive controller is designed to ensure the convergence of the velocity tracking error in the presence of uncertainties associated with vehicle dynamic parameters, water velocity, and thrust forces. Comparative simulations with different control and system configurations are performed to verify the effectiveness of the proposed scheme and to illustrate the influences of the prediction horizon, cost function, closed-loop vehicle dynamics, and predictive velocity reference model on the IBVS system performance.

  13. Superfast-response and ultrahigh-power-density electromechanical actuators based on hierarchal carbon nanotube electrodes and chitosan.

    PubMed

    Li, Jinzhu; Ma, Wenjun; Song, Li; Niu, Zhiqiang; Cai, Le; Zeng, Qingsheng; Zhang, Xiaoxian; Dong, Haibo; Zhao, Duan; Zhou, Weiya; Xie, Sishen

    2011-11-09

    Here we report a novel single-walled carbon nanotube (SWNT) based bimorph electromechanical actuator, which consists of unique as-grown SWNT films as double electrode layers separated by a chitosan electrolyte layer consisting of an ionic liquid. By taking advantage of the special hierarchical structure and the outstanding electrical and mechanical properties of the SWNT film electrodes, our actuators show orders-of-magnitude improvements in many aspects compared to previous ionic electroactive polymer (i-EAP) actuators, including superfast response (19 ms), quite wide available frequency range (dozens to hundreds of Hz), incredible large stress generating rate (1080 MPa/s), and ultrahigh mechanical output power density (244 W/kg). These remarkable achievements together with their facile fabrication, low driving voltage, flexibility, and long durability enable the SWNT-based actuators many applications such as artificial muscles for biomimetic flying insects or robots and flexible deployable reflectors.

  14. 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…

  15. 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…

  16. 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…

  17. 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

  18. 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.

  19. 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.

  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.

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

    PubMed

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

    2012-12-01

    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.

  3. Attribute-Based Methods

    Treesearch

    Thomas P. Holmes; Wiktor L. Adamowicz

    2003-01-01

    Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a class of stated preference...

  4. Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri Net modelling and simulation.

    PubMed

    Marwan, Wolfgang; Sujatha, Arumugam; Starostzik, Christine

    2005-10-21

    We reconstruct the regulatory network controlling commitment and sporulation of Physarum polycephalum from experimental results using a hierarchical Petri Net-based modelling and simulation framework. The stochastic Petri Net consistently describes the structure and simulates the dynamics of the molecular network as analysed by genetic, biochemical and physiological experiments within a single coherent model. The Petri Net then is extended to simulate time-resolved somatic complementation experiments performed by mixing the cytoplasms of mutants altered in the sporulation response, to systematically explore the network structure and to probe its dynamics. This reverse engineering approach presumably can be employed to explore other molecular or genetic signalling systems where the activity of genes or their products can be experimentally controlled in a time-resolved manner.

  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. Morphologically tuned 3D/1D rutile TiO2 hierarchical hybrid microarchitectures engineered by one-step surfactant free hydrothermal method

    NASA Astrophysics Data System (ADS)

    Maria John, Maria Angelin Sinthiya; Ramamurthi, K.; Sethuraman, K.; Ramesh Babu, R.

    2017-05-01

    Present investigation reports on the surfactant free hydrothermal synthesize of the morphologically tuned hierarchical hybrid rutile titanium oxide (TiO2) microarchitectures showing three dimensional microflower structures and cook pine tree like structures on the one dimensional nanorods formed over TiO2 seed layer coated glass substrates by tuning growth temperature. TiO2 seed layer of ∼100 nm thick was coated on the glass substrates employing sol-gel spin coating method and then rutile TiO2 microarchitectures were synthesized on the TiO2 seed layer by one-step surfactant free hydrothermal method. Deposited samples were characterized by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, UV-vis spectroscopy and photoluminescence spectroscopy techniques. Influence of the growth temperature on the crystallinity, morphology and optical properties along with the growth mechanism to achieve hierarchical microarchitectures was investigated. Present work revealed that the structural, morphological and optical properties of the TiO2 hierarchical microarchitectures strongly depend on the growth temperature. Further we proposed a model for the cause to effect possible morphological changes of rutile TiO2 microarchitectures as a function of growth temperatures on the TiO2 seeded glass substrates.

  7. Amyloid-like hierarchical helical fibrils and conformational reversibility in functional polyesters based on L-amino acids.

    PubMed

    Anantharaj, Santhanaraj; Jayakannan, Manickam

    2015-03-09

    The present investigation reports one of the first examples of synthetic polymers that capable of undergoing reversible conformation transformation and also self-assembled to hierarchical helical amyloid-like fibrils. A new temperature selective melt polycondensation reaction was developed for amino acid monomers L-aspartic acid and L-glutamic acid to produce high molecular weight linear functional polyesters. These new polyesters have hydrogen bonded urethane (or carbamate) units that are in-built in each repeating unit. The polymer chains have adapted expanded chain conformation through β-sheet hydrogen bonding interactions and produced twisted ribbon-like assemblies. These twisted ribbons have subsequently undergone interchain folding for making double helical structures. The double helical fibrils aligned together to produce amyloid-like fibrils of few micrometer in length. Upon chemical deprotection of the pendent urethane units; the resultant cationic functional polyester adapted coil-like conformation and exhibited spherical charged nanoparticles of 200 ± 20 nm in size. Dynamic light scattering and zeta potential measurements revealed that both the charge and size of the spherical structures could be varied by altering the diol segment length in the polymer backbone. The coil-like chains in the charged spherical particles could be reversibly expanded into amyloid-like fibrils via fluorophore chemical substitution using dansyl chloride. The dansyl-substituted polymer exhibited helical fibrils and strong fluorescence. Thus, the L-amino acid based polyesters exhibited complete reversible conformational changes from hierarchical helical amyloid-like fibrils to charged nanoparticles in a single polymer system. These new nonpeptide polyester analogues, their amyloid fibrils, cationic polymer assemblies and fluorescent fibrils are very new based on l-amino acids, which may be useful for a wide range of biomedical applications.

  8. Fmoc-RGDS based fibrils: atomistic details of their hierarchical assembly.

    PubMed

    Zanuy, David; Poater, Jordi; Solà, Miquel; Hamley, Ian W; Alemán, Carlos

    2016-01-14

    We describe the 3D supramolecular structure of Fmoc-RGDS fibrils, where Fmoc and RGDS refer to the hydrophobic N-(fluorenyl-9-methoxycarbonyl) group and the hydrophilic Arg-Gly-Asp-Ser peptide sequence, respectively. For this purpose, we performed atomistic all-atom molecular dynamics simulations of a wide variety of packing modes derived from both parallel and antiparallel β-sheet configurations. The proposed model, which closely resembles the cross-β core structure of amyloids, is stabilized by π-π stacking interactions between hydrophobic Fmoc groups. More specifically, in this organization, the Fmoc-groups of β-strands belonging to the same β-sheet form columns of π-stacked aromatic rings arranged in a parallel fashion. Eight of such columns pack laterally forming a compact and dense hydrophobic core, in which two central columns are surrounded by three adjacent columns on each side. In addition to such Fmoc···Fmoc interactions, the hierarchical assembly of the constituent β-strands involves a rich variety of intra- and inter-strand interactions. Accordingly, hydrogen bonding, salt bridges and π-π stacking interactions coexist in the highly ordered packing network proposed for the Fmoc-RGDS amphiphile. Quantum mechanical calculations, which have been performed to quantify the above referred interactions, confirm the decisive role played by the π-π stacking interactions between the rings of the Fmoc groups, even though both inter-strand and intra-strand hydrogen bonds and salt bridges also play a non-negligible role. Overall, these results provide a solid reference to complement the available experimental data, which are not precise enough to determine the fibril structure, and reconcile previous independent observations.

  9. Broadband acoustic energy confinement in hierarchical sonic crystals composed of rotated square inclusions

    NASA Astrophysics Data System (ADS)

    Shakouri, Amir; Xu, Feifei; Fan, Zheng

    2017-07-01

    The propagation of acoustic waves in hierarchical sonic crystals is studied computationally and experimentally. These sonic crystals are composed of a hierarchical order of square inclusions rotated 45° with respect to the square lattice structure. It is shown that these hierarchical sonic crystals are capable of confining acoustic energy over a broad frequency range and at multiple lattice points inside the sonic crystal based on Bragg's scattering effect. Fused deposition modeling additive manufacturing is applied to prepare a finite-sized sample of the hierarchical sonic crystal. Acoustic measurements are conducted on the hierarchical sonic crystal sample in a direct and closely plane-wave field inside an anechoic room. The experimental measurements are in good agreement with the band structure calculated using the finite element method. Potential applications of the hierarchical sonic crystals for acoustic energy harvesting and noise measurements are discussed.

  10. Use of urchin-like NixCo3-xO4 hierarchical nanostructures based on non-precious metals as bifunctional electrocatalysts for anion-exchange membrane alkaline alcohol fuel cells

    NASA Astrophysics Data System (ADS)

    Manivasakan, Palanisamy; Ramasamy, Parthiban; Kim, Jinkwon

    2014-07-01

    Bifunctional electrocatalysts based on non-precious metals were developed for the dioxygen reduction and methanol oxidation reactions. These electrocatalysts can be considered as candidate cathode and anode materials for anion-exchange membrane (AEM) alkaline alcohol fuel cells. A series of Ni-doped cobalt oxide (NixCo3-xO4) hierarchical nanostructures composed of one-dimensional nanorods was prepared by an inexpensive hydrothermal method. X-ray diffraction patterns showed that the NixCo3-xO4 crystallized in a cubic spinel phase. The electrochemical performance of the catalysts was investigated using a conventional cyclic voltammetry technique. The electrocatalytic behaviour of the NixCo3-xO4 hierarchical nanostructures was compared with the behaviour of Co3O4 and Co0.33Ni0.67O. The synergistic behaviour of the Ni in the NixCo3-xO4 nanostructures was established with respect to the Ni content. NixCo3-xO4 hierarchical nanostructures show a better catalytic behaviour than Co3O4 and Co0.33Ni0.67O. Although the NixCo3-xO4 compositions all showed good catalytic behaviour, Ni1Co2O4 was identified as a superior bifunctional electrocatalyst for the oxygen reduction and methanol oxidation reactions in alkaline media. The effect of the Ni content on the electrocatalytic properties of the NixCo3-xO4 hierarchical nanostructures was clearly shown. The use of these electrocatalysts based on non-precious metals could have a commercial impact on the development of non-platinum electrocatalysts for application in AEM alkaline alcohol fuel cells.Bifunctional electrocatalysts based on non-precious metals were developed for the dioxygen reduction and methanol oxidation reactions. These electrocatalysts can be considered as candidate cathode and anode materials for anion-exchange membrane (AEM) alkaline alcohol fuel cells. A series of Ni-doped cobalt oxide (NixCo3-xO4) hierarchical nanostructures composed of one-dimensional nanorods was prepared by an inexpensive hydrothermal method. X

  11. Novel classification based on immunohistochemistry combined with hierarchical clustering analysis in non-functioning neuroendocrine tumor patients.

    PubMed

    Iida, Shinya; Miki, Yasuhiro; Ono, Katsuhiko; Akahira, Jun-ichi; Suzuki, Takashi; Ishida, Kazuyuki; Watanabe, Mika; Sasano, Hironobu

    2010-10-01

    Somatostatin analogues ameliorated many symptoms caused by neuroendocrine tumors (NET), but their antitumor activities are limited especially in non-functioning cases. An overactivation of signaling pathways under receptor tyrosine-kinase (RTK) has been recently demonstrated in some NET patients, but its details have remained largely unknown. Therefore, in this study, we immunolocalized therapeutic factors and evaluated the data to study the clinical significance of the molecules in non-functioning Japanese gastrointestinal NET. Fifty-two NET cases were available for examination in this study and expression of somatostatin receptor (sstr) 1, 2A, 2B, 3 and 5, activated form of mammalian target of rapamycin (mTOR), eukaryotic initiation factor 4-binding protein 1 (4EBP1), ribosomal protein s6 (S6), extracellular signal-regulated kinase (ERK) and insulin-like growth factor 1 receptor (IGF-1R) was evaluated using immunohistochemistry. We then studied the correlation among the immunohistochemical results of the individual cases using hierarchical clustering analysis. Results of clustering analysis demonstrated that NET cases were basically classified into Cluster I and II. Cluster I was associated with higher expression of sstr1, 2B and 3 and Cluster II was characterized by an activation of the PI3K/Akt pathway and IGF-1R and higher proliferative status. Cluster II was further classified into Cluster IIa and IIb. Cluster IIa was associated with higher expression of sstr1 and 5 and higher proliferative status and Cluster IIb was characterized by ERK activation. Hierarchical clustering analysis of immunoreactivity of the therapeutic factors can classify NET cases into three distinctive groups and the medical treatment may be determined according to this novel classification method for non-functioning NET patients.

  12. 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.

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

    SciTech Connect

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

    2016-12-28

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

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

    PubMed

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

    2016-12-28

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

  15. 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.

  16. Research on Assessment Method for Ruralinformatization Level Based on Ahp

    NASA Astrophysics Data System (ADS)

    Jing, Du; Li, Daoliang; Li, Hongwen; Zhang, Yanjun

    Based on rural informatization connotation and five essential elements that affect rural informatization assessment, which are development environment, information infrastructure, information resource, information service system and application of information technology in rural areas, This paper designs an indicator system for rural informatization level assessment. Through AHP method, it sets up the hierarchical construction model of rural informatization assessment and weight of each indicator is calculated. Thus the evaluation method for assessment on rural informatization level is proposed in this paper. It combines subjective evaluation with objective appraisal and will help direct rural informatization management departments with jobs and promotes rural informatization development.

  17. Hydrothermal Fabrication of WO₃ Hierarchical Architectures: Structure, Growth and Response.

    PubMed

    Wu, Chuan-Sheng

    2015-07-22

    Recently hierarchical architectures, consisting of two-dimensional (2D) nanostructures, are of great interest for potential applications in energy and environmental. Here, novel rose-like WO₃ hierarchical architectures were successfully synthesized via a facile hydrothermal method. The as-prepared WO₃ hierarchical architectures were in fact assembled by numerous nanosheets with an average thickness of ~30 nm. We found that the oxalic acid played a significant role in governing morphologies of WO₃ during hydrothermal process. Based on comparative studies, a possible formation mechanism was also proposed in detail. Furthermore, gas-sensing measurement showed that the well-defined 3D WO₃ hierarchical architectures exhibited the excellent gas sensing properties towards CO.

  18. 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.

  19. Hierarchical manifold learning.

    PubMed

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

    2012-01-01

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

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

    PubMed Central

    2010-01-01

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

  1. 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.

  2. 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

  3. 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

    2014-04-07

    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.

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

    PubMed

    Matzen, L H; 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.

  5. 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.

  6. 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

    2016-06-08

    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.

  7. Metabolonote: a wiki-based database for managing hierarchical metadata of metabolome analyses.

    PubMed

    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://metabolonote.kazusa.or.jp/.

  8. 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

  9. Hierarchical Medical System Based on Big Data and Mobile Internet: A New Strategic Choice in Health Care.

    PubMed

    Wang, Yaogang; Sun, Li; Hou, Jie

    2017-08-08

    China is setting up a hierarchical medical system to solve the problems of biased resource allocation and high patient flows to large hospitals. The development of big data and mobile Internet technology provides a new perspective for the establishment of hierarchical medical system. This viewpoint discusses the challenges with the hierarchical medical system in China and how big data and mobile Internet can be used to mitigate these challenges. ©Yaogang Wang, Li Sun, Jie Hou. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 08.08.2017.

  10. Hierarchical regression for epidemiologic analyses of multiple exposures

    SciTech Connect

    Greenland, S.

    1994-11-01

    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 {open_quotes}semi-Bayes{close_quotes} 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. 35 refs., 1 fig., 1 tab.

  11. 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.

  12. 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

  13. Multiobjective decision making policies and coordination mechanisms in hierarchical organizations: results of an agent-based simulation.

    PubMed

    Leitner, Stephan; Wall, Friederike

    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).

  14. Delay-dependent H∞ robust control for large power systems based on two-level hierarchical decentralised coordinated control structure

    NASA Astrophysics Data System (ADS)

    Dou, Chun-Xia; Duan, Zhi-Sheng; Jia, Xing-Bei

    2013-02-01

    This article focuses on a novel two-level hierarchical decentralised coordinated control which consists of several local fuzzy power system stabilisers (LFPSSs) for each generator at the first level tuned by supervisory power system stabiliser (SPSS) at the secondary level for the transient stabilisation improvement of large power systems. First, in order to compensate the inherent nonlinear interconnections between subsystems in system dynamic model, a direct feedback linearisation compensator is proposed to act through the local excitation machine. Afterwards, the T-S fuzzy model-based decentralised LFPSS for each generator is designed. Then, for the purpose of improving dynamic performance, the SPSS is designed by using the remote signals from the wide area measurements system. However, there are unavoidable delays involved before the remote signals are received at the SPSS site or the control signals of SPSS are sent to the local systems. Taking consideration of the multiple delays, by using less conservative delay-dependent Lyapunov approach, the authors develop a delay-dependent H∞ robust control technique based on the decentralised coordinated control structure. Some sufficient conditions for the system stabilisation are presented in terms of linear matrix inequalities dependent only on the upper bounds of the time delays. Finally, the effectiveness of the proposed control scheme is demonstrated through simulation examples.

  15. 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.

  16. Hierarchical nanosheet-based Ni3S2 microspheres grown on Ni foam for high-performance all-solid-state asymmetric supercapacitors

    NASA Astrophysics Data System (ADS)

    Li, Gaofeng; Cong, Yuan; Zhang, Chuanxiang; Tao, Haijun; Sun, Yueming; Wang, Yuqiao

    2017-10-01

    The hierarchical nanosheet-based Ni3S2 microspheres directly grew on Ni foam using a two-step hydrothermal method. The microsphere with a diameter of ∼1 microns and a rough surface was well connected to each other without any binders to provide a larger specific surface area, shorter ion/electron diffusion paths, richer electroactive sites as a supercapacitor electrode. As a three-electrode supercapacitor, it delivers a high specific capacity of 981.8 F g‑1 at 2 A g‑1, an excellent rate capability of 436.4 F g‑1 at 12 A g‑1, and a good cycling stability of 950.9 F g‑1 with 96.9% retention after 1000 cycles at 2 A g‑1. Furthermore, an asymmetric supercapacitor based on Ni3S2-microsphere as a positive electrode and active carbon as a negative electrode shows a high energy density of 29.4 Wh kg‑1 at 324.5 W kg‑1 and a high power density of 3197.6 W kg‑1 at 15.1 Wh kg‑1. This work demonstrates that nanosheet-based Ni3S2 microspheres coated Ni foam can be an effective electrode for a real supercapacitor.

  17. 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.

  18. 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.

  19. Efficient hierarchical Liouville space propagator to quantum dissipative dynamics.

    PubMed

    Shi, Qiang; Chen, Liping; Nan, Guangjun; Xu, Rui-Xue; Yan, Yijing

    2009-02-28

    We propose an efficient method to propagate the hierarchical quantum master equations based on a reformulation of the original formalism and the incorporation of a filtering algorithm that automatically truncates the hierarchy with a preselected tolerance. The new method is applied to calculate electron transfer dynamics in a spin-boson model and the absorption spectra of an excitonic dimmer. The proposed method significantly reduces the number of auxiliary density operators used in the hierarchical equation approach and thus provides an efficient way capable of studying real time dynamics of non-Markovian quantum dissipative systems in strong system-bath coupling and low temperature regimes.

  20. 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.

  1. Fabrication of long-term stable superoleophobic surface based on copper oxide/cobalt oxide with micro-nanoscale hierarchical roughness

    NASA Astrophysics Data System (ADS)

    Barthwal, Sumit; Lim, Si-Hyung

    2015-02-01

    We have demonstrated a simple and cost-effective technique for the large-area fabrication of a superoleophobic surface using copper as a substrate. The whole process included three simple steps: First, the copper substrate was oxidized under hot alkaline conditions to fabricate flower-like copper oxide microspheres by heating at a particular temperature for an interval of time. Second, the copper-oxide-covered copper substrate was further heated in a solution of cobalt nitrate and ammonium nitrate in the presence of an ammonia solution to fabricate cobalt oxide nanostructures. We applied this second step to increase the surface roughness because it is an important criterion for improved superoleophobicity. Finally, to reduce the surface energy of the fabricated structures, the surfaces were chemically modified with perfluorooctyltrichlorosilane. Contact-angle measurements indicate that the micro-nano binary (MNB) hierarchical structures fabricated on the copper substrate became super-repellent toward a broad range of liquids with surface tension in the range of 21.5-72 mN/m. In an attempt to significantly improve the superoleophobic property of the surface, we also examined and compared the role of nanostructures in MNB hierarchical structures with only micro-fabricated surfaces. The fabricated MNB hierarchical structures also displays thermal stability and excellent long-term stability after exposure in air for more than 9 months. Our method might provide a general route toward the preparation of novel hierarchical films on metal substrates for various industrial applications.

  2. UVliPiD: A UVPD-Based Hierarchical Approach for De Novo Characterization of Lipid A Structures.

    PubMed

    Morrison, Lindsay J; Parker, W Ryan; Holden, Dustin D; Henderson, Jeremy C; Boll, Joseph M; Trent, M Stephen; Brodbelt, Jennifer S

    2016-02-02

    The lipid A domain of the endotoxic lipopolysaccharide layer of Gram-negative bacteria is comprised of a diglucosamine backbone to which a variable number of variable length fatty acyl chains are anchored. Traditional characterization of these tails and their linkages by nuclear magnetic resonance (NMR) or mass spectrometry is time-consuming and necessitates databases of pre-existing structures for structural assignment. Here, we introduce an automated de novo approach for characterization of lipid A structures that is completely database-independent. A hierarchical decision-tree MS(n) method is used in conjunction with a hybrid activation technique, UVPDCID, to acquire characteristic fragmentation patterns of lipid A variants from a number of Gram-negative bacteria. Structural assignments are derived from integration of key features from three to five spectra and automated interpretation is achieved in minutes without the need for pre-existing information or candidate structures. The utility of this strategy is demonstrated for a mixture of lipid A structures from an enzymatically modified E. coli lipid A variant. A total of 27 lipid A structures were discovered, many of which were isomeric, showcasing the need for a rapid de novo approach to lipid A characterization.

  3. 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

  4. Rhipsalis (Cactaceae)-like Hierarchical Structure Based Microfluidic Chip for Highly Efficient Isolation of Rare Cancer Cells.

    PubMed

    Yan, Shuangqian; Zhang, Xian; Dai, Xiaofang; Feng, Xiaojun; Du, Wei; Liu, Bi-Feng

    2016-12-14

    The circulating tumor cells (CTCs), originating from the primary tumor, play a vital role in cancer diagnosis, prognosis, disease monitoring, and precise therapy. However, the CTCs are extremely rare in the peripheral bloodstream and hard to be isolated. To overcome current limitations associated with CTC capture and analysis, the strategy incorporating nanostructures with microfluidic devices receives wide attention. Here, we demonstrated a three-dimensional microfluidic device (Rm-chip) for capturing cancer cells with high efficiency by integrating a novel hierarchical structure, the "Rhipsalis (Cactaceae)"-like micropillar array, into the Rm-chip. The PDMS micropillar array was fabricated by soft-lithography and rapid prototyping method, which was then conformally plated with a thin gold layer through electroless plating. EpCAM antibody was modified onto the surface of the micropillars through the thiol-oligonucleotide linkers in order to release captured cancer cells by DNase I treatment. The antibody-functionalized device achieved an average capture efficiency of 88% in PBS and 83.7% in whole blood samples. We believe the Rm-chip provided a convenient, economical, and versatile approach for cell analysis with wide potential applications.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    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.

  6. Design of Hierarchical Structures for Synchronized Deformations

    NASA Astrophysics Data System (ADS)

    Seifi, Hamed; Javan, Anooshe Rezaee; Ghaedizadeh, Arash; Shen, Jianhu; Xu, Shanqing; Xie, Yi Min

    2017-01-01

    In this paper we propose a general method for creating a new type of hierarchical structures at any level in both 2D and 3D. A simple rule based on a rotate-and-mirror procedure is introduced to achieve multi-level hierarchies. These new hierarchical structures have remarkably few degrees of freedom compared to existing designs by other methods. More importantly, these structures exhibit synchronized motions during opening or closure, resulting in uniform and easily-controllable deformations. Furthermore, a simple analytical formula is found which can be used to avoid collision of units of the structure during the closing process. The novel design concept is verified by mathematical analyses, computational simulations and physical experiments.

  7. Multiple sequence alignment with hierarchical clustering.

    PubMed Central

    Corpet, F

    1988-01-01

    An algorithm is presented for the multiple alignment of sequences, either proteins or nucleic acids, that is both accurate and easy to use on microcomputers. The approach is based on the conventional dynamic-programming method of pairwise alignment. Initially, a hierarchical clustering of the sequences is performed using the matrix of the pairwise alignment scores. The closest sequences are aligned creating groups of aligned sequences. Then close groups are aligned until all sequences are aligned in one group. The pairwise alignments included in the multiple alignment form a new matrix that is used to produce a hierarchical clustering. If it is different from the first one, iteration of the process can be performed. The method is illustrated by an example: a global alignment of 39 sequences of cytochrome c. PMID:2849754

  8. Design of Hierarchical Structures for Synchronized Deformations

    PubMed Central

    Seifi, Hamed; Javan, Anooshe Rezaee; Ghaedizadeh, Arash; Shen, Jianhu; Xu, Shanqing; Xie, Yi Min

    2017-01-01

    In this paper we propose a general method for creating a new type of hierarchical structures at any level in both 2D and 3D. A simple rule based on a rotate-and-mirror procedure is introduced to achieve multi-level hierarchies. These new hierarchical structures have remarkably few degrees of freedom compared to existing designs by other methods. More importantly, these structures exhibit synchronized motions during opening or closure, resulting in uniform and easily-controllable deformations. Furthermore, a simple analytical formula is found which can be used to avoid collision of units of the structure during the closing process. The novel design concept is verified by mathematical analyses, computational simulations and physical experiments. PMID:28117427

  9. 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 advo