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Sample records for hierarchical method based

  1. 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.

  2. A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning

    PubMed Central

    Liu, Quan; Ling, Xionghong; Cui, Zhiming

    2014-01-01

    Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are “trial and error” and “related reward.” A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of “curse of dimensionality,” which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The “curse of dimensionality” problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well. PMID:24600318

  3. 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

  4. 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.

  5. 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

  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. 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].

  8. 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

  9. 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.

  10. Arbitrary Order Hierarchical Bases for Computational Electromagnetics

    SciTech Connect

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

    2002-12-20

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

  11. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    DTIC Science & Technology

    2016-01-05

    events (and subsequently, their likelihood of occurrence) based on historical evidence of the counts of previous event occurrences. The novel Bayesian...Aug-2014 22-May-2015 Approved for Public Release; Distribution Unlimited Final Report: Sparse Event Modeling with Hierarchical Bayesian Kernel Methods...Sparse Event Modeling with Hierarchical Bayesian Kernel Methods Report Title The research objective of this proposal was to develop a predictive Bayesian

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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. 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.

  2. 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.

  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. 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.

  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. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  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. 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.

  6. 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.

  7. 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.

  8. Content-based medical image classification using a new hierarchical merging scheme.

    PubMed

    Pourghassem, Hossein; Ghassemian, Hassan

    2008-12-01

    Automatic medical image classification is a technique for assigning a medical image to a class among a number of image categories. Due to computational complexity, it is an important task in the content-based image retrieval (CBIR). In this paper, we propose a hierarchical medical image classification method including two levels using a perfect set of various shape and texture features. Furthermore, a tessellation-based spectral feature as well as a directional histogram has been proposed. In each level of the hierarchical classifier, using a new merging scheme and multilayer perceptron (MLP) classifiers (merging-based classification), homogenous (semantic) classes are created from overlapping classes in the database. The proposed merging scheme employs three measures to detect the overlapping classes: accuracy, miss-classified ratio, and dissimilarity. The first two measures realize a supervised classification method and the last one realizes an unsupervised clustering technique. In each level, the merging-based classification is applied to a merged class of the previous level and splits it to several classes. This procedure is progressive to achieve more classes. The proposed algorithm is evaluated on a database consisting of 9100 medical X-ray images of 40 classes. It provides accuracy rate of 90.83% on 25 merged classes in the first level. If the correct class is considered within the best three matches, this value will increase to 97.9%.

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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).

  15. 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

  16. 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.

  17. 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…

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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…

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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.

  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. 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.

  5. 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.

  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. 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.

  8. 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

  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. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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…

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  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. 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.

  6. 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.

  7. 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.

  8. 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%.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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)

  9. 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

  10. 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.

  11. 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.

  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. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  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. 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…

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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."

  7. 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.

  8. 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.

  9. 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.

  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. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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...

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  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 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.

  19. 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.

  20. 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

  1. 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…

  2. 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)

  3. 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.

  4. 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.

  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

    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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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).

  15. Parallel hierarchical radiosity rendering

    SciTech Connect

    Carter, M.

    1993-07-01

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

  16. 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.

  17. 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…

  18. 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.

  19. 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.

  20. 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.

  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 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.

  4. 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.

  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. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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 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.

  20. 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.

  1. 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.

  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.

    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.

  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. 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.

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

    PubMed

    Chen, Kunlin; Zhou, Shuxue; Wu, Limin

    2016-01-26

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

  7. 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.

  8. 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.

  9. 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

  10. 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…

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

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

    PubMed

    Langheinrich, Jessica; Bogner, Franz X

    2015-01-01

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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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,

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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/.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  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. Spherical silica micro/nanomaterials with hierarchical structures: synthesis and applications.

    PubMed

    Du, Xin; He, Junhui

    2011-10-05

    This paper reviews the progress made recently in synthesis and applications of spherical silica micro/nanomaterials with multilevel (hierarchical) structures. The spherical silica micro/nanomaterials with hierarchical structures are classified into four main structural categories that include (1) hollow mesoporous spheres, (2) core-in-(hollow porous shell) spheres, (3) hollow spheres with multiple porous shells and (4) hierarchically porous spheres. Due to the complex structures and being focused on spherical silica micro/nanomaterials, some novel methods based on the combination of two routine methods or two surfactants, and some special synthetic strategies are proposed to produce the spherical silica micro/nanomaterials with hierarchical structures. Compared with the same-sized solid, porous or hollow silica spheres, these fantastic spherical silica micro/nanomaterials with hierarchical structures exhibit enhanced properties which may enable them to be used in broad and promising applications as ideal scaffolds (carriers) for biological, medical, and catalytic applications.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    PubMed Central

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

    2015-01-01

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

  1. 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

  2. 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

  3. 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.

  4. Hierarchical models of animal abundance and occurrence

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, R.M.

    2006-01-01

    Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

  5. 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.

  6. HDS: Hierarchical Data System

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  8. 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.

  9. 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

  10. 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.

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

    PubMed

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

    2014-07-15

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

  12. Hierarchical Bayesian random intercept model-based cross-level interaction decomposition for truck driver injury severity investigations.

    PubMed

    Chen, Cong; Zhang, Guohui; Tian, Zong; Bogus, Susan M; Yang, Yin

    2015-12-01

    Traffic crashes occurring on rural roadways induce more severe injuries and fatalities than those in urban areas, especially when there are trucks involved. Truck drivers are found to suffer higher potential of crash injuries compared with other occupational labors. Besides, unobserved heterogeneity in crash data analysis is a critical issue that needs to be carefully addressed. In this study, a hierarchical Bayesian random intercept model decomposing cross-level interaction effects as unobserved heterogeneity is developed to examine the posterior probabilities of truck driver injuries in rural truck-involved crashes. The interaction effects contributing to truck driver injury outcomes are investigated based on two-year rural truck-involved crashes in New Mexico from 2010 to 2011. The analysis results indicate that the cross-level interaction effects play an important role in predicting truck driver injury severities, and the proposed model produces comparable performance with the traditional random intercept model and the mixed logit model even after penalization by high model complexity. It is revealed that factors including road grade, number of vehicles involved in a crash, maximum vehicle damage in a crash, vehicle actions, driver age, seatbelt use, and driver under alcohol or drug influence, as well as a portion of their cross-level interaction effects with other variables are significantly associated with truck driver incapacitating injuries and fatalities. These findings are helpful to understand the respective or joint impacts of these attributes on truck driver injury patterns in rural truck-involved crashes.

  13. Deriving structural and functional insights from a ligand-based hierarchical classification of G protein-coupled receptors.

    PubMed

    Attwood, T K; Croning, M D R; Gaulton, A

    2002-01-01

    G protein-coupled receptors (GPCRs) constitute the largest known family of cell-surface receptors. With hundreds of members populating the rhodopsin-like GPCR superfamily and many more awaiting discovery in the human genome, they are of interest to the pharmaceutical industry because of the opportunities they afford for yielding potentially lucrative drug targets. Typical sequence analysis strategies for identifying novel GPCRs tend to involve similarity searches using standard primary database search tools. This will reveal the most similar sequence, generally without offering any insight into its family or superfamily relationships. Conversely, searches of most 'pattern' or family databases are likely to identify the superfamily, but not the closest matching subtype. Here we describe a diagnostic resource that allows identification of GPCRs in a hierarchical fashion, based principally upon their ligand preference. This resource forms part of the PRINTS database, which now houses approximately 250 GPCR-specific fingerprints (http://www.bioinf.man.ac.uk/dbbrowser/gpcrPRINTS/). This collection of fingerprints is able to provide more sensitive diagnostic opportunities than have been realized by related approaches and is currently the only diagnostic tool for assigning GPCR subtypes. Mapping such fingerprints on to three-dimensional GPCR models offers powerful insights into the structural and functional determinants of subtype specificity.

  14. A hierarchical Bayesian approach to the classification of C3 and C4 grass pollen based on SPIRAL δ13C data

    NASA Astrophysics Data System (ADS)

    Urban, Michael A.; Nelson, David M.; Kelly, Ryan; Ibrahim, Tahir; Dietze, Michael; Pearson, Ann; Hu, Feng Sheng

    2013-11-01

    Differentiating C3 and C4 grass pollen in the paleorecord is difficult because of their morphological similarity. Using a spooling wire microcombustion device interfaced with an isotope ratio mass spectrometer, Single Pollen Isotope Ratio AnaLysis (SPIRAL) enables classification of grass pollen as C3 or C4 based upon δ13C values. To address several limitations of this novel technique, we expanded an existing SPIRAL training dataset of pollen δ13C data from 8 to 31 grass species. For field validation, we analyzed δ13C of individual grains of grass pollen from the surface sediments of 15 lakes in Africa and Australia, added these results to a prior dataset of 10 lakes from North America, and compared C4-pollen abundance in surface sediments with C4-grass abundance on the surrounding landscape. We also developed and tested a hierarchical Bayesian model to estimate the relative abundance of C3- and C4-grass pollen in unknown samples, including an estimation of the likelihood that either pollen type is present in a sample. The mean (±SD) δ13C values for the C3 and C4 grasses in the training dataset were -29.6 ± 9.5‰ and -13.8 ± 9.5‰, respectively. Across a range of % C4 in samples of known composition, the average bias of the Bayesian model was <3% for C4 in samples of at least 50 grains, indicating that the model accurately predicted the relative abundance of C4 grass pollen. The hierarchical framework of the model resulted in less bias than a previous threshold-based C3/C4 classification method, especially near the high or low extremes of C4 abundance. In addition, the percent of C4 grass pollen in surface-sediment samples estimated using the model was strongly related to the abundance of C4 grasses on the landscape (n = 24, p < 0.001, r2 = 0.65). These results improve δ13C-based quantitative reconstructions of grass community composition in the paleorecord and demonstrate the utility of the Bayesian framework to aid the interpretation of stable isotope

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  17. Free-Energy Bounds for Hierarchical Spin Models

    NASA Astrophysics Data System (ADS)

    Castellana, Michele; Barra, Adriano; Guerra, Francesco

    2014-04-01

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

  18. A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine.

    PubMed

    Mastmeyer, André; Engelke, Klaus; Fuchs, Christina; Kalender, Willi A

    2006-08-01

    We have developed a new hierarchical 3D technique to segment the vertebral bodies in order to measure bone mineral density (BMD) with high trueness and precision in volumetric CT datasets. The hierarchical approach starts with a coarse separation of the individual vertebrae, applies a variety of techniques to segment the vertebral bodies with increasing detail and ends with the definition of an anatomic coordinate system for each vertebral body, relative to which up to 41 trabecular and cortical volumes of interest are positioned. In a pre-segmentation step constraints consisting of Boolean combinations of simple geometric shapes are determined that enclose each individual vertebral body. Bound by these constraints viscous deformable models are used to segment the main shape of the vertebral bodies. Volume growing and morphological operations then capture the fine details of the bone-soft tissue interface. In the volumes of interest bone mineral density and content are determined. In addition, in the segmented vertebral bodies geometric parameters such as volume or the length of the main axes of inertia can be measured. Intra- and inter-operator precision errors of the segmentation procedure were analyzed using existing clinical patient datasets. Results for segmented volume, BMD, and coordinate system position were below 2.0%, 0.6%, and 0.7%, respectively. Trueness was analyzed using phantom scans. The bias of the segmented volume was below 4%; for BMD it was below 1.5%. The long-term goal of this work is improved fracture prediction and patient monitoring in the field of osteoporosis. A true 3D segmentation also enables an accurate measurement of geometrical parameters that may augment the clinical value of a pure BMD analysis.

  19. Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based Object Recognition

    PubMed Central

    Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Zheng, Yuan F.

    2017-01-01

    Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

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

    SciTech Connect

    Lipnikov, Konstantin; Agouzal, Abdellatif; Vassilevski, Yuri

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  2. Megavariate analysis of hierarchical QSAR data

    NASA Astrophysics Data System (ADS)

    Eriksson, Lennart; Johansson, Erik; Lindgren, Fredrik; Sjöström, Michael; Wold, Svante

    2002-10-01

    Multivariate PCA- and PLS-models involving many variables are often difficult to interpret, because plots and lists of loadings, coefficients, VIPs, etc, rapidly become messy and hard to overview. There may then be a strong temptation to eliminate variables to obtain a smaller data set. Such a reduction of variables, however, often removes information and makes the modelling efforts less reliable. Model interpretation may be misleading and predictive power may deteriorate. A better alternative is usually to partition the variables into blocks of logically related variables and apply hierarchical data analysis. Such blocked data may be analyzed by PCA and PLS. This modelling forms the base-level of the hierarchical modelling set-up. On the base-level in-depth information is extracted for the different blocks. The score vectors formed on the base-level, here called `super variables', may be linked together in new matrices on the top-level. On the top-level superficial relationships between the X- and the Y-data are investigated. In this paper the basic principles of hierarchical modelling by means of PCA and PLS are reviewed. One objective of the paper is to disseminate this concept to a broader QSAR audience. The hierarchical methods are used to analyze a set of 10 haloalkanes for which K = 30 chemical descriptors and M = 255 biological responses have been gathered. Due to the complexity of the biological data, they are sub-divided in four blocks. All the modelling steps on the base-level and the top-level are reported and the final QSAR model is interpreted thoroughly.

  3. Contour detection and hierarchical image segmentation.

    PubMed

    Arbeláez, Pablo; Maire, Michael; Fowlkes, Charless; Malik, Jitendra

    2011-05-01

    This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

  4. Hierarchical Assembly of Multifunctional Oxide-based Composite Nanostructures for Energy and Environmental Applications

    PubMed Central

    Gao, Pu-Xian; Shimpi, Paresh; Gao, Haiyong; Liu, Caihong; Guo, Yanbing; Cai, Wenjie; Liao, Kuo-Ting; Wrobel, Gregory; Zhang, Zhonghua; Ren, Zheng; Lin, Hui-Jan

    2012-01-01

    Composite nanoarchitectures represent a class of nanostructured entities that integrates various dissimilar nanoscale building blocks including nanoparticles, nanowires, and nanofilms toward realizing multifunctional characteristics. A broad array of composite nanoarchitectures can be designed and fabricated, involving generic materials such as metal, ceramics, and polymers in nanoscale form. In this review, we will highlight the latest progress on composite nanostructures in our research group, particularly on various metal oxides including binary semiconductors, ABO3-type perovskites, A2BO4 spinels and quaternary dielectric hydroxyl metal oxides (AB(OH)6) with diverse application potential. Through a generic template strategy in conjunction with various synthetic approaches— such as hydrothermal decomposition, colloidal deposition, physical sputtering, thermal decomposition and thermal oxidation, semiconductor oxide alloy nanowires, metal oxide/perovskite (spinel) composite nanowires, stannate based nanocompostes, as well as semiconductor heterojunction—arrays and networks have been self-assembled in large scale and are being developed as promising classes of composite nanoarchitectures, which may open a new array of advanced nanotechnologies in solid state lighting, solar absorption, photocatalysis and battery, auto-emission control, and chemical sensing. PMID:22837702

  5. Hierarchical assembly of multifunctional oxide-based composite nanostructures for energy and environmental applications.

    PubMed

    Gao, Pu-Xian; Shimpi, Paresh; Gao, Haiyong; Liu, Caihong; Guo, Yanbing; Cai, Wenjie; Liao, Kuo-Ting; Wrobel, Gregory; Zhang, Zhonghua; Ren, Zheng; Lin, Hui-Jan

    2012-01-01

    Composite nanoarchitectures represent a class of nanostructured entities that integrates various dissimilar nanoscale building blocks including nanoparticles, nanowires, and nanofilms toward realizing multifunctional characteristics. A broad array of composite nanoarchitectures can be designed and fabricated, involving generic materials such as metal, ceramics, and polymers in nanoscale form. In this review, we will highlight the latest progress on composite nanostructures in our research group, particularly on various metal oxides including binary semiconductors, ABO(3)-type perovskites, A(2)BO(4) spinels and quaternary dielectric hydroxyl metal oxides (AB(OH)(6)) with diverse application potential. Through a generic template strategy in conjunction with various synthetic approaches- such as hydrothermal decomposition, colloidal deposition, physical sputtering, thermal decomposition and thermal oxidation, semiconductor oxide alloy nanowires, metal oxide/perovskite (spinel) composite nanowires, stannate based nanocompostes, as well as semiconductor heterojunction-arrays and networks have been self-assembled in large scale and are being developed as promising classes of composite nanoarchitectures, which may open a new array of advanced nanotechnologies in solid state lighting, solar absorption, photocatalysis and battery, auto-emission control, and chemical sensing.

  6. Adaptive Sampling in Hierarchical Simulation

    SciTech Connect

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

    2007-07-09

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

  7. Hierarchical self-assembly of switchable nucleolipid supramolecular gels based on environmentally-sensitive fluorescent nucleoside analogs

    NASA Astrophysics Data System (ADS)

    Nuthanakanti, Ashok; Srivatsan, Seergazhi G.

    2016-02-01

    Exquisite recognition and folding properties have rendered nucleic acids as useful supramolecular synthons for the construction of programmable architectures. Despite their proven applications in nanotechnology, scalability and fabrication of nucleic acid nanostructures still remain a challenge. Here, we describe a novel design strategy to construct new supramolecular nucleolipid synthons by using environmentally-sensitive fluorescent nucleoside analogs, based on 5-(benzofuran-2-yl)uracil and 5-(benzo[b]thiophen-2-yl)uracil cores, as the head group and fatty acids, attached to the ribose sugar, as the lipophilic group. These modified nucleoside-lipid hybrids formed organogels driven by hierarchical structures such as fibers, twisted ribbons, helical ribbons and nanotubes, which depended on the nature of fatty acid chain and nucleobase modification. NMR, single crystal X-ray and powder X-ray diffraction studies revealed the coordinated interplay of various non-covalent interactions invoked by modified nucleobase, sugar and fatty acid chains in setting up the pathway for the gelation process. Importantly, these nucleolipid gels retained or displayed aggregation-induced enhanced emission and their gelation behavior and photophysical properties could be reversibly switched by external stimuli such as temperature, ultrasound and chemicals. Furthermore, the switchable nature of nucleolipid gels to chemical stimuli enabled the selective two channel recognition of fluoride and Hg2+ ions through visual phase transition and fluorescence change. Fluorescent organogels exhibiting such a combination of useful features is rare, and hence, we expect that this innovative design of fluorescent nucleolipid supramolecular synthons could lead to the emergence of a new family of smart optical materials and probes.Exquisite recognition and folding properties have rendered nucleic acids as useful supramolecular synthons for the construction of programmable architectures. Despite their

  8. Hierarchical Multiobjective Linear Programming Problems with Fuzzy Domination Structures

    NASA Astrophysics Data System (ADS)

    Yano, Hitoshi

    2010-10-01

    In this paper, we focus on hierarchical multiobjective linear programming problems with fuzzy domination structures where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. After introducing decision powers and the solution concept based on the α-level set for the fuzzy convex cone Λ which reflects a fuzzy domination structure, we propose a fuzzy approach to obtain a satisfactory solution which reflects not only the hierarchical relationships between multiple decision makers but also their own preferences for their membership functions. In the proposed method, instead of Pareto optimal concept, a generalized Λ˜α-extreme point concept is introduced. In order to obtain a satisfactory solution from among a generalized Λ˜α-extreme point set, an interactive algorithm based on linear programming is proposed, and an interactive processes are demonstrated by means of an illustrative numerical example.

  9. Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

    NASA Astrophysics Data System (ADS)

    Edwards, Mark; Hu, Fei; Kumar, Sunil

    2004-10-01

    The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report

  10. Synthesis strategies in the search for hierarchical zeolites.

    PubMed

    Serrano, D P; Escola, J M; Pizarro, P

    2013-05-07

    Great interest has arisen in the past years in the development of hierarchical zeolites, having at least two levels of porosities. Hierarchical zeolites show an enhanced accessibility, leading to improved catalytic activity in reactions suffering from steric and/or diffusional limitations. Moreover, the secondary porosity offers an ideal space for the deposition of additional active phases and for functionalization with organic moieties. However, the secondary surface represents a discontinuity of the crystalline framework, with a low connectivity and a high concentration of silanols. Consequently, hierarchical zeolites exhibit a less "zeolitic behaviour" than conventional ones in terms of acidity, hydrophobic/hydrophilic character, confinement effects, shape-selectivity and hydrothermal stability. Nevertheless, this secondary surface is far from being amorphous, which provides hierarchical zeolites with a set of novel features. A wide variety of innovative strategies have been developed for generating a secondary porosity in zeolites. In the present review, the different synthetic routes leading to hierarchical zeolites have been classified into five categories: removal of framework atoms, surfactant-assisted procedures, hard-templating, zeolitization of preformed solids and organosilane-based methods. Significant advances have been achieved recently in several of these alternatives. These include desilication, due to its versatility, dual templating with polyquaternary ammonium surfactants and framework reorganization by treatment with surfactant-containing basic solutions. In the last two cases, the materials so prepared show both mesoscopic ordering and zeolitic lattice planes. Likewise, interesting results have been obtained with the incorporation of different types of organosilanes into the zeolite crystallization gels, taking advantage of their high affinity for silicate and aluminosilicate species. Crystallization of organofunctionalized species favours the

  11. Hierarchical self-assembly of switchable nucleolipid supramolecular gels based on environmentally-sensitive fluorescent nucleoside analogs.

    PubMed

    Nuthanakanti, Ashok; Srivatsan, Seergazhi G

    2016-02-14

    Exquisite recognition and folding properties have rendered nucleic acids as useful supramolecular synthons for the construction of programmable architectures. Despite their proven applications in nanotechnology, scalability and fabrication of nucleic acid nanostructures still remain a challenge. Here, we describe a novel design strategy to construct new supramolecular nucleolipid synthons by using environmentally-sensitive fluorescent nucleoside analogs, based on 5-(benzofuran-2-yl)uracil and 5-(benzo[b]thiophen-2-yl)uracil cores, as the head group and fatty acids, attached to the ribose sugar, as the lipophilic group. These modified nucleoside-lipid hybrids formed organogels driven by hierarchical structures such as fibers, twisted ribbons, helical ribbons and nanotubes, which depended on the nature of fatty acid chain and nucleobase modification. NMR, single crystal X-ray and powder X-ray diffraction studies revealed the coordinated interplay of various non-covalent interactions invoked by modified nucleobase, sugar and fatty acid chains in setting up the pathway for the gelation process. Importantly, these nucleolipid gels retained or displayed aggregation-induced enhanced emission and their gelation behavior and photophysical properties could be reversibly switched by external stimuli such as temperature, ultrasound and chemicals. Furthermore, the switchable nature of nucleolipid gels to chemical stimuli enabled the selective two channel recognition of fluoride and Hg(2+) ions through visual phase transition and fluorescence change. Fluorescent organogels exhibiting such a combination of useful features is rare, and hence, we expect that this innovative design of fluorescent nucleolipid supramolecular synthons could lead to the emergence of a new family of smart optical materials and probes.

  12. Hierarchical Multiagent Reinforcement Learning

    DTIC Science & Technology

    2004-01-25

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

  13. Bayesian Hierarchical Classes Analysis

    ERIC Educational Resources Information Center

    Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn

    2008-01-01

    Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…

  14. A Progressive Image Compression Method Based on EZW Algorithm

    NASA Astrophysics Data System (ADS)

    Du, Ke; Lu, Jianming; Yahagi, Takashi

    A simple method based on the EZW algorithm is presented for improving image compression performance. Recent success in wavelet image coding is mainly attributed to recognition of the importance of data organization and representation. There have been several very competitive wavelet coders developed, namely, Shapiro's EZW(Embedded Zerotree Wavelets)(1), Said and Pearlman's SPIHT(Set Partitioning In Hierarchical Trees)(2), and Bing-Bing Chai's SLCCA(Significance-Linked Connected Component Analysis for Wavelet Image Coding)(3). The EZW algorithm is based on five key concepts: (1) a DWT(Discrete Wavelet Transform) or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting self-similarity inherent in images, (3) entropy-coded successive-approximation quantization, (4) universal lossless data compression which is achieved via adaptive arithmetic coding. and (5) DWT coefficients' degeneration from high scale subbands to low scale subbands. In this paper, we have improved the self-similarity statistical characteristic in concept (5) and present a progressive image compression method.

  15. Chemistry Problem Solving Instruction: A Comparison of Three Computer-Based Formats for Learning from Hierarchical Network Problem Representations

    ERIC Educational Resources Information Center

    Ngu, Bing Hiong; Mit, Edwin; Shahbodin, Faaizah; Tuovinen, Juhani

    2009-01-01

    Within the cognitive load theory framework, we designed and compared three alternative instructional solution formats that can be derived from a common static hierarchical network representation depicting problem structure. The interactive-solution format permitted students to search in self-controlled manner for solution steps, static-solution…

  16. Hierarchical modelling of in situ elastic deformation of human enamel based on photoelastic and diffraction analysis of stresses and strains.

    PubMed

    Sui, Tan; Lunt, Alexander J G; Baimpas, Nikolaos; Sandholzer, Michael A; Hu, Jianan; Dolbnya, Igor P; Landini, Gabriel; Korsunsky, Alexander M

    2014-01-01

    Human enamel is a typical hierarchical mineralized tissue with a two-level composite structure. To date, few studies have focused on how the mechanical behaviour of this tissue is affected by both the rod orientation at the microscale and the preferred orientation of mineral crystallites at the nanoscale. In this study, wide-angle X-ray scattering was used to determine the internal lattice strain response of human enamel samples (with differing rod directions) as a function of in situ uniaxial compressive loading. Quantitative stress distribution evaluation in the birefringent mounting epoxy was performed in parallel using photoelastic techniques. The resulting experimental data was analysed using an advanced multiscale Eshelby inclusion model that takes into account the two-level hierarchical structure of human enamel, and reflects the differing rod directions and orientation distributions of hydroxyapatite crystals. The achieved satisfactory agreement between the model and the experimental data, in terms of the values of multidirectional strain components under the action of differently orientated loads, suggests that the multiscale approach captures reasonably successfully the structure-property relationship between the hierarchical architecture of human enamel and its response to the applied forces. This novel and systematic approach can be used to improve the interpretation of the mechanical properties of enamel, as well as of the textured hierarchical biomaterials in general.

  17. Considerations on the thermal performances of ribbed channels by means of a novel dynamic method for hierarchical clustering

    NASA Astrophysics Data System (ADS)

    Niro, A.; Fustinoni, D.; Vignati, F.; Gramazio, P.; Ciminà, S.

    2016-09-01

    The investigation of ribbed surfaces for the enhancement of heat transfer in forced convection allowed to observe that different geometries may lead to comparable performances. Due to the lack of an underlying structure of the data, a novel method for data clustering is introduced here, to assess to what extent comparable performances can be achieved using different rib geometries. The clustering method is an agglomerative technique, based on the inclusion of each configuration in another ones bounding box, whose size depends dynamically on the Nusselt number and the pumping power. The method is applied to a large database experimentally obtained at ThermALab of Politecnico di Milano, in order to identify the Nusselt number and the friction factor for diverse-rib configurations in a large-aspect ratio channel with low-Reynolds flows. The clusters are determined, and the resulting families of configurations are used to assess the possible effects of the rib geometry on the thermal and fluid-dynamic performances. The clustering analysis results suggest interesting considerations.

  18. Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

    NASA Technical Reports Server (NTRS)

    Choi, Sang Hyouk (Inventor); Park, Yeonjoon (Inventor); Chu, Sang-Hyon (Inventor); Elliott, James R. (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Lillehei, Peter T. (Inventor); Stoakley, Diane M. (Inventor)

    2011-01-01

    A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

  19. Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

    NASA Technical Reports Server (NTRS)

    Padovan, Joseph; Krishna, Lala; Gute, Douglas

    1997-01-01

    Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

  20. Hierarchical structure of Turkey's foreign trade

    NASA Astrophysics Data System (ADS)

    Kantar, Ersin; Deviren, Bayram; Keskin, Mustafa

    2011-10-01

    We examine the hierarchical structures of Turkey's foreign trade by using real prices of their commodity export and import move together over time. We obtain the topological properties among the countries based on Turkey's foreign trade during the 1996-2010 period by using the concept of hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)). These periods are divided into two subperiods, such as 1996-2002 and 2003-2010, in order to test various time-window and observe the temporal evolution. We perform the bootstrap techniques to investigate a value of the statistical reliability to the links of the MSTs and HTs. We also use a clustering linkage procedure in order to observe the cluster structure much better. From the structural topologies of these trees, we identify different clusters of countries according to their geographical location and economic ties. Our results show that the DE (Germany), UK (United Kingdom), FR (France), IT (Italy) and RU (Russia) are more important within the network, due to a tighter connection with other countries. We have also found that these countries play a significant role for Turkey's foreign trade and have important implications for the design of portfolio and investment strategies.

  1. Numerical simulation of strained Si/SiGe devices: the hierarchical approach

    NASA Astrophysics Data System (ADS)

    Meinerzhagen, B.; Jungemann, C.; Neinhüs, B.; Bartels, M.

    2004-03-01

    Performance predictions for 25 nm strained Si CMOS devices which are based on full-band Monte Carlo (FBMC) device simulations and which are in good agreement with the most recent experimental trends are presented. The FBMC simulator itself is part of a hierarchical device simulation system which allows to perform time-efficient hierarchical hydrodynamic (HD) device simulations of modern SiGe HBTs. As demonstrated below, the accuracy of a such a hydrodynamic-based dc, ac, transient, and noise analysis is comparable to FBMC device simulations. In addition, the new hierarchical numerical noise simulation method is experimentally verified based on a modern rf-CMOS technology of Philips Research. The MC-enhanced simulation accuracy of the hierarchical hydrodynamic and drift diffusion (DD) models can be also exploited for mixed-mode circuit simulations, which is shown by typical power sweep simulations of an industrial rf power amplifier.

  2. New physiologically-relevant liver tissue model based on hierarchically cocultured primary rat hepatocytes with liver endothelial cells.

    PubMed

    Xiao, Wenjin; Perry, Guillaume; Komori, Kikuo; Sakai, Yasuyuki

    2015-11-01

    To develop an in vitro liver tissue equivalent, hepatocytes should be cocultured with liver non-parenchymal cells to mimic the in vivo physiological microenvironments. In this work, we describe a physiologically-relevant liver tissue model by hierarchically organizing layers of primary rat hepatocytes and human liver sinusoidal endothelial cells (TMNK-1) on an oxygen-permeable polydimethylsiloxane (PDMS) membrane, which facilitates direct oxygenation by diffusion through the membrane. This in vivo-mimicking hierarchical coculture was obtained by simply proceeding the overlay of TMNK-1 cells on the hepatocyte layer re-formed on the collagen immobilized PDMS membranes. The comparison of hepatic functionalities was achieved between coculture and sandwich culture with Matrigel, in the presence and absence of direct oxygenation. A complete double-layered structure of functional liver cells with vertical contact between hepatocytes and TMNK-1 was successfully constructed in the coculture with direct oxygen supply and was well-maintained for 14 days. The hepatocytes in this hierarchical culture exhibited improved survival, functional bile canaliculi formation, cellular level polarization and maintenance of metabolic activities including Cyp1A1/2 activity and albumin production. By contrast, the two cell populations formed discontinuous monolayers on the same surfaces in the non-oxygen-permeable cultures. These results demonstrate that (i) the direct oxygenation through the PDMS membranes enables very simple formation of a hierarchical structure consisting of a hepatocyte layer and a layer of TMNK-1 and (ii) we may include other non-parenchymal cells in this format easily, which can be widely applicable to other epithelial organs.

  3. Self-Assembly of Hierarchical Chiral Nanostructures Based on Metal-Benzimidazole Interactions: Chiral Nanofibers, Nanotubes, and Microtubular Flowers.

    PubMed

    Zhou, Xiaoqin; Jin, Qingxian; Zhang, Li; Shen, Zhaocun; Jiang, Long; Liu, Minghua

    2016-09-01

    Controlled hierarchical self-assembly of synthetic molecules into chiral nanoarchitectures to mimic those biological chiral structures is of great importance. Here, a low-molecular-weight organogelator containing a benzimidazole moiety conjugated with an amphiphilic l-glutamic amide has been designed and its self-assembly into various hierarchical chiral nanostructures is investigated. Upon gel formation in organic solvents, 1D chiral nanostructure such as nanofiber and nanotube are obtained depending on the solvents. In the presence of transition and rare earth metal ions, hierarchical chiral nanostructures are formed. Specifically, the addition of TbCl3 , EuCl3 , and AgNO3 leads to nanofiber structures, while the addition of Cu(NO3 )2 , Tb(NO3 )3 , or Eu(NO3 )3 provides the microflower structures and microtubular flower structures, respectively. While Eu(III) and Tb(III)-containing microtubular flowers keep the chirality, the Cu(II)-coordinated microflowers lose chirality. More interestingly, the nanofibers formed by the gelator coordinated with Eu(III) or Tb(III) ions show not only the supramolecular chirality but also the circularly polarized luminescence.

  4. Hierarchical partial order ranking.

    PubMed

    Carlsen, Lars

    2008-09-01

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

  5. Inference and Hierarchical Modeling in the Social Sciences.

    ERIC Educational Resources Information Center

    Draper, David

    1995-01-01

    The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)

  6. Incorporating Usability Criteria into the Development of Animated Hierarchical Maps

    ERIC Educational Resources Information Center

    Shih, Yu-Cheng; Huang, Pei-Ren; Chen, Sherry Y.

    2013-01-01

    Nowadays, Web-based learning systems have become popular because they can provide multiple tools, among which hierarchical maps are widely used to support teaching and learning. However, traditional hierarchical maps may let learners easily get lost within large information space. This study proposes an animated hierarchical map to address this…

  7. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    NASA Astrophysics Data System (ADS)

    Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido

    2015-12-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.

  8. Accurate lithography hotspot detection based on principal component analysis-support vector machine classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Yu, Bei; Gao, Jhih-Rong; Ding, Duo; Zeng, Xuan; Pan, David Z.

    2015-01-01

    As technology nodes continue to shrink, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. We propose an accurate hotspot detection approach based on principal component analysis-support vector machine classifier. Several techniques, including hierarchical data clustering, data balancing, and multilevel training, are provided to enhance the performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation and provides a high flexibility for adapting to new lithography processes and rules.

  9. Assessing dose–response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure

    PubMed Central

    Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

    2017-01-01

    Objectives To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose–response effect) for data from a stepped-wedge design with a hierarchical structure. Design The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Setting Routinely and annually collected national data on China from 2008 to 2012. Participants 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Outcome measures Agreement and differences in estimates of dose–response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). Results The estimated dose–response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2–4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose–response among provinces, counties and facilities were estimated, and the ‘lowest’ or ‘highest’ units by their dose–response effects were pinpointed only by the multilevel RM model. Conclusions For examining dose–response effect based on data from multiple time points with hierarchical structure and the

  10. Enhanced photovoltaic performance of fully flexible dye-sensitized solar cells based on the Nb2O5 coated hierarchical TiO2 nanowire-nanosheet arrays

    NASA Astrophysics Data System (ADS)

    Liu, Wenwu; Hong, Chengxun; Wang, Hui-gang; Zhang, Mei; Guo, Min

    2016-02-01

    Nb2O5 coated hierarchical TiO2 nanowire-sheet arrays photoanode was synthesized on flexible Ti-mesh substrate by using a hydrothermal approach. The effect of TiO2 morphology and Nb2O5 coating layer on the photovoltaic performance of the flexible dye sensitized solar cells (DSSCs) based on Ti-mesh supported nanostructures were systematically investigated. Compared to the TiO2 nanowire arrays (NWAs), hierarchical TiO2 nanowire arrays (HNWAs) with enlarged internal surface area and strong light scattering properties exhibited higher overall conversion efficiency. The introduction of thin Nb2O5 coating layers on the surface of the TiO2 HNWAs played a key role in improving the photovoltaic performance of the flexible DSSC. By separating the TiO2 and electrolyte (I-/I3-), the Nb2O5 energy barrier decreased the electron recombination rate and increased electron collection efficiency and injection efficiency, resulting in improved Jsc and Voc. Furthermore, the influence of Nb2O5 coating amounts on the power conversion efficiency were discussed in detail. The fully flexible DSSC based on Nb2O5 coated TiO2 HNWAs films with a thickness of 14 μm displayed a well photovoltaic property of 4.55% (Jsc = 10.50 mA cm-2, Voc = 0.75 V, FF = 0.58). The performance enhancement of the flexible DSSC is largely attributed to the reduced electron recombination, enlarged internal surface area and superior light scattering ability of the formed hierarchical nanostructures.

  11. A computer-based image analysis method for assessing the severity of hip joint osteoarthritis

    NASA Astrophysics Data System (ADS)

    Boniatis, Ioannis; Costaridou, Lena; Cavouras, Dionisis; Panagiotopoulos, Elias; Panayiotakis, George

    2006-12-01

    A computer-based image analysis method was developed for assessing the severity of hip osteoarthritis (OA). Eighteen pelvic radiographs of patients with verified unilateral hip OA, were digitized and enhanced employing custom developed software. Two ROIs corresponding to osteoarthritic and contralateral-physiological radiographic Hip Joint Spaces (HJSs) were determined on each radiograph. Textural features were extracted from the HJS-ROIs utilizing the run-length matrices and Laws textural measures. A k-Nearest Neighbour based hierarchical tree structure was designed for classifying hips into three OA severity categories labeled as "Normal", "Mild/Moderate", and "Severe". Employing the run-length features, the overall classification accuracy of the hierarchical tree structure was 86.1%. The utilization of Laws' textural measures improved the system classification performance, providing an overall classification accuracy of 94.4%. The proposed method maybe of value to physicians in assessing the severity of hip OA.

  12. High-resolution numerical methods for compressible multi-phase flow in hierarchical porous media. Progress report, September 1993--September 1994

    SciTech Connect

    Trangenstein, J.A.

    1994-03-15

    This is the second 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.

  13. Joint Hierarchical Category Structure Learning and Large-Scale Image Classification.

    PubMed

    Qu, Yanyun; Lin, Li; Shen, Fumin; Lu, Chang; Wu, Yang; Xie, Yuan; Tao, Dacheng

    2016-10-05

    We investigate the scalable image classification problem with a large number of categories. Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image classification method based on learning hierarchical interclass structures. Specifically, we first design a fast algorithm to compute the similarity metric between categories, based on which a visual tree is constructed by hierarchical spectral clustering. Using the learned visual tree, a test sample label is efficiently predicted by searching for the best path over the entire tree. The proposed method is extensively evaluated on the ILSVRC2010 and Caltech 256 benchmark datasets. Experimental results show that our method obtains significantly better category hierarchies than other state-of-the-art visual tree-based methods and, therefore, much more accurate classification.

  14. Effective SERS-active substrates composed of hierarchical micro/nanostructured arrays based on reactive ion etching and colloidal masks

    NASA Astrophysics Data System (ADS)

    Zhang, Honghua; Liu, Dilong; Hang, Lifeng; Li, Xinyang; Liu, Guangqiang; Cai, Weiping; Li, Yue

    2016-09-01

    A facile route has been proposed for the fabrication of morphology-controlled periodic SiO2 hierarchical micro/nanostructured arrays by reactive ion etching (RIE) using monolayer colloidal crystals as masks. By effectively controlling the experimental conditions of RIE, the morphology of a periodic SiO2 hierarchical micro/nanostructured array could be tuned from a dome-shaped one to a circular truncated cone, and finally to a circular cone. After coating a silver thin layer, these periodic micro/nanostructured arrays were used as surface-enhanced Raman scattering (SERS)-active substrates and demonstrated obvious SERS signals of 4-Aminothiophenol (4-ATP). In addition, the circular cone arrays displayed better SERS enhancement than those of the dome-shaped and circular truncated cone arrays due to the rougher surface caused by physical bombardment. After optimization of the circular cone arrays with different periodicities, an array with the periodicity of 350 nm exhibits much stronger SERS enhancement and possesses a low detection limit of 10-10 M 4-ATP. This offers a practical platform to conveniently prepare SERS-active substrates.

  15. Three-dimensional beehive-like hierarchical porous polyacrylonitrile-based carbons as a high performance supercapacitor electrodes

    NASA Astrophysics Data System (ADS)

    Yao, Long; Yang, Guangzhi; Han, Pan; Tang, Zhihong; Yang, Junhe

    2016-05-01

    Three-dimensional beehive-like hierarchical porous carbons (HPCs) have been prepared by a facile carbonization of polymethylmethacrylate (PMMA)/polyacrylonitrile (PAN) core-shell polymer particle followed by KOH activation. The all-organic porogenic core-shell precursor was synthesized by a simple and green surfactant-free emulsion polymerization. The as-obtained HPCs show favorable features for electrochemical energy storage such as high specific surface area of up to 2085 m2 g-1, high volume of pores up to 1.89 cm3 g-1, hierarchical porosity consisting of micro, meso, and macropores, turbostratic carbon structure, uniform pore size and rich oxygen-doping (21.20%). The supercapacitor performance of HPCs exhibit a high specific capacitance 314 F g-1 at a current density of 0.5 A g-1 and 237 F g-1 at a current density of 20 A g-1, ultra-high rate capability with 83% retention rate from 1 to 20 A g-1 and outstanding cycling stability with 96% capacitance retention after 2000 cycles. The facile, efficient and green synthesis strategy for novel HPCs from polymer sources could find use in supercapacitors, lithium ion batteries, fuel cells and sorbents.

  16. Hierarchical LiFePO4 with a controllable growth of the (010) facet for lithium-ion batteries

    PubMed Central

    Guo, Binbin; Ruan, Hongcheng; Zheng, Cheng; Fei, Hailong; Wei, Mingdeng

    2013-01-01

    Hierarchically structured LiFePO4 was successfully synthesized by ionic liquid solvothermal method. These hierarchically structured LiFePO4 samples were constructed from nanostructured platelets with their (010) facets mainly exposed. To the best of our knowledge, facet control of a hierarchical LiFePO4 crystal has not been reported yet. Based on a series of experimental results, a tentative mechanism for the formation of these hierarchical structures was proposed. After these hierarchically structured LiFePO4 samples were coated with a thin carbon layer and used as cathode materials for lithium-ion batteries, they exhibited excellent high-rate discharge capability and cycling stability. For instance, a capacity of 95% can be maintained for the LiFePO4 sample at a rate as high as 20 C, even after 1000 cycles. PMID:24071818

  17. Hierarchical LiFePO4 with a controllable growth of the (010) facet for lithium-ion batteries.

    PubMed

    Guo, Binbin; Ruan, Hongcheng; Zheng, Cheng; Fei, Hailong; Wei, Mingdeng

    2013-09-27

    Hierarchically structured LiFePO4 was successfully synthesized by ionic liquid solvothermal method. These hierarchically structured LiFePO4 samples were constructed from nanostructured platelets with their (010) facets mainly exposed. To the best of our knowledge, facet control of a hierarchical LiFePO4 crystal has not been reported yet. Based on a series of experimental results, a tentative mechanism for the formation of these hierarchical structures was proposed. After these hierarchically structured LiFePO4 samples were coated with a thin carbon layer and used as cathode materials for lithium-ion batteries, they exhibited excellent high-rate discharge capability and cycling stability. For instance, a capacity of 95% can be maintained for the LiFePO4 sample at a rate as high as 20 C, even after 1000 cycles.

  18. Processing laser beam spot images using the parallel-hierarchical network for classification and forecasting their energy center coordinates

    NASA Astrophysics Data System (ADS)

    Timchenko, Leonid I.; Pijarski, Paweł; Zavadskiy, Vladislav; Nakonechna, Svitlana S.; Kokriatskaya, Nataliya I.

    2016-09-01

    The paper presents a method of forecasting the energy center position of the laser beam images using the parallel-hierarchical network. Main steps for classification and forecast of energy center coordinates of laser beam spot images are described, which allow to develop a new information technology for their classification and forecast their energy center coordinates. Predictions based on the known neural networks and on the proposed method using the parallel-hierarchical network were evaluated experimentally.

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

    PubMed Central

    Wu, Chuan-Sheng

    2015-01-01

    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. PMID:28347062

  20. A template-free CVD route to synthesize hierarchical porous ZnO films

    NASA Astrophysics Data System (ADS)

    Duan, Xiangyang; Chen, Guangde; Guo, Lu'an; Zhu, Youzhang; Ye, Honggang; Wu, Yelong

    2015-12-01

    Unique porous ZnO films were successfully synthesized on Si substrates without any catalysts or templates using chemical vapor deposition method. Unlike earlier reports, they are hierarchical porous, containing both macropores and mesopores. The zinc oxide seed layer and the weight ratio of source materials were found to be the major factors that would facilitate the synthesis of these hierarchical porous films. We found that all the macropores were surrounded by grain boundaries. As presented in the SEM images, the newborn ZnO atoms would prefer to adsorb nearby the grain boundaries and nucleate there in the growth stage. A schematic diagram based on the aforesaid phenomenon was proposed to explain the synthesis of the hierarchical porous ZnO film. An unusual strong emission peak located at 420 nm was observed in the photoluminescence spectrum. It was suggested that the emission peak was attributed to the special hierarchical porous structure, especially the grain boundaries in the nanowalls of these films.

  1. A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules.

    PubMed

    Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

    2015-01-01

    A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis.

  2. A hierarchical clustering methodology for the estimation of toxicity.

    PubMed

    Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

    2008-01-01

    ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

  3. A biologically-inspired framework for contour detection using superpixel-based candidates and hierarchical visual cues.

    PubMed

    Sun, Xiao; Shang, Ke; Ming, Delie; Tian, Jinwen; Ma, Jiayi

    2015-10-20

    Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast to previous models that detect contours from pixels, a modified superpixel generation processing is proposed to generate a contour candidate set and then weigh the candidates by extracting hierarchical visual cues. We extract the low-level visual local cues to weigh the contour intrinsic property and mid-level visual cues on the basis of Gestalt principles for weighting the contour grouping constraint. Experimental results tested on the BSDS benchmark show that the proposed framework exhibits promising performances to capture meaningful contours in complex scenes.

  4. A Biologically-Inspired Framework for Contour Detection Using Superpixel-Based Candidates and Hierarchical Visual Cues

    PubMed Central

    Sun, Xiao; Shang, Ke; Ming, Delie; Tian, Jinwen; Ma, Jiayi

    2015-01-01

    Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast to previous models that detect contours from pixels, a modified superpixel generation processing is proposed to generate a contour candidate set and then weigh the candidates by extracting hierarchical visual cues. We extract the low-level visual local cues to weigh the contour intrinsic property and mid-level visual cues on the basis of Gestalt principles for weighting the contour grouping constraint. Experimental results tested on the BSDS benchmark show that the proposed framework exhibits promising performances to capture meaningful contours in complex scenes. PMID:26492252

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  6. Hierarchical structure of biological systems

    PubMed Central

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  7. Differentiation of Isodon japonica and Adulterants Based on Identification and Quantitation 14 Diterpenoids Using LC-MS-MS Library Search Approach and Hierarchical Cluster Analysis.

    PubMed

    Jin, Yiran; Tian, Tingting; Ma, Yinghua; Liu, Minyan; Xie, Weiwei; Wang, Xin; Xu, Huijun; Du, Yingfeng

    2016-03-01

    The aim of this study was to investigate the chemical differences between genunine Isodon japonica and its adulterants. A linear ion trap liquid chromatography with tandem mass spectrometry analytical method has been developed for the identification and quantification of 14 major diterpenoids in I. japonica. Data acquisition was multiple reaction monitoring transitions mode followed by an information-dependent acquisition using the enhanced product ion (EPI) scan in a single run. The target compounds were further identified and confirmed using an EPI spectral library. Overall validation of the assay was carried out including linearity, accuracy, precision, limits of detection and quantification. The results demonstrated that the method was selective, sensitive and reliable. The determination results of 21 batches of I. japonica and adulterants were then analyzed and differentiated by hierarchical clustering analysis.

  8. A method of characterizing network topology based on the breadth-first search tree

    NASA Astrophysics Data System (ADS)

    Zhou, Bin; He, Zhe; Wang, Nianxin; Wang, Bing-Hong

    2016-05-01

    A method based on the breadth-first search tree is proposed in this paper to characterize the hierarchical structure of network. In this method, a similarity coefficient is defined to quantitatively distinguish networks, and quantitatively measure the topology stability of the network generated by a model. The applications of the method are discussed in ER random network, WS small-world network and BA scale-free network. The method will be helpful for deeply describing network topology and provide a starting point for researching the topology similarity and isomorphism of networks.

  9. Hierarchically UVO patterned elastomeric and thermoplastic structures

    NASA Astrophysics Data System (ADS)

    Chen, Ying; Kulkarni, Manish; Marshall, Allan; Karim, Alamgir

    2014-03-01

    We demonstrate a simple yet versatile method to fabricate tunable hierarchical micro-nanostructures on flexible Poly(dimethylsiloxane) (PDMS) elastomer and thermoplastic polymer surface by a two-step process. Nanoscale patterned PDMS was obtained by imprinting compact disc (CD)/digital video disc (DVD) patterns. The second micro pattern was superposed by selective densification of PDMS by exposing to ultraviolet-ozone radiation (UVO) through micro-patterned TEM grid as a mask. The nanoscale patterns are preserved through UVO exposure step leading to formation of deep hierarchical patterns, so that for a 19 um square mesh, the micro pattern has a depth of 600nm with 6h PDMS UVO exposure time. This simple method can be promoted to fabricate hierarchical structures of thermoplastic materials (such as polystyrene), from which the mechanism of capillary imprinting and thermal stability of hierarchical patterns are investigated. This study is potentially important to various applications ranging from biomimetic scaffolds to solar cell.

  10. Zeolitic materials with hierarchical porous structures.

    PubMed

    Lopez-Orozco, Sofia; Inayat, Amer; Schwab, Andreas; Selvam, Thangaraj; Schwieger, Wilhelm

    2011-06-17

    During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented.

  11. Perception and Hierarchical Dynamics

    PubMed Central

    Kiebel, Stefan J.; Daunizeau, Jean; Friston, Karl J.

    2009-01-01

    In this paper, we suggest that perception could be modeled by assuming that sensory input is generated by a hierarchy of attractors in a dynamic system. We describe a mathematical model which exploits the temporal structure of rapid sensory dynamics to track the slower trajectories of their underlying causes. This model establishes a proof of concept that slowly changing neuronal states can encode the trajectories of faster sensory signals. We link this hierarchical account to recent developments in the perception of human action; in particular artificial speech recognition. We argue that these hierarchical models of dynamical systems are a plausible starting point to develop robust recognition schemes, because they capture critical temporal dependencies induced by deep hierarchical structure. We conclude by suggesting that a fruitful computational neuroscience approach may emerge from modeling perception as non-autonomous recognition dynamics enslaved by autonomous hierarchical dynamics in the sensorium. PMID:19649171

  12. Learning deep hierarchical visual feature coding.

    PubMed

    Goh, Hanlin; Thome, Nicolas; Cord, Matthieu; Lim, Joo-Hwee

    2014-12-01

    In this paper, we propose a hybrid architecture that combines the image modeling strengths of the bag of words framework with the representational power and adaptability of learning deep architectures. Local gradient-based descriptors, such as SIFT, are encoded via a hierarchical coding scheme composed of spatial aggregating restricted Boltzmann machines (RBM). For each coding layer, we regularize the RBM by encouraging representations to fit both sparse and selective distributions. Supervised fine-tuning is used to enhance the quality of the visual representation for the categorization task. We performed a thorough experimental evaluation using three image categorization data sets. The hierarchical coding scheme achieved competitive categorization accuracies of 79.7% and 86.4% on the Caltech-101 and 15-Scenes data sets, respectively. The visual representations learned are compact and the model's inference is fast, as compared with sparse coding methods. The low-level representations of descriptors that were learned using this method result in generic features that we empirically found to be transferrable between different image data sets. Further analysis reveal the significance of supervised fine-tuning when the architecture has two layers of representations as opposed to a single layer.

  13. Hierarchical Theme and Topic Modeling.

    PubMed

    Chien, Jen-Tzung

    2016-03-01

    Considering the hierarchical data groupings in text corpus, e.g., words, sentences, and documents, we conduct the structural learning and infer the latent themes and topics for sentences and words from a collection of documents, respectively. The relation between themes and topics under different data groupings is explored through an unsupervised procedure without limiting the number of clusters. A tree stick-breaking process is presented to draw theme proportions for different sentences. We build a hierarchical theme and topic model, which flexibly represents the heterogeneous documents using Bayesian nonparametrics. Thematic sentences and topical words are extracted. In the experiments, the proposed method is evaluated to be effective to build semantic tree structure for sentences and the corresponding words. The superiority of using tree model for selection of expressive sentences for document summarization is illustrated.

  14. Hierarchical structures of amorphous solids characterized by persistent homology

    PubMed Central

    Hiraoka, Yasuaki; Nakamura, Takenobu; Hirata, Akihiko; Escolar, Emerson G.; Matsue, Kaname; Nishiura, Yasumasa

    2016-01-01

    This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms. Then, specific distributions such as curves and islands in the PDs identify meaningful shape characteristics of the atomic configuration. Although the method can be applied to a wide variety of disordered systems, it is applied here to silica glass, the Lennard-Jones system, and Cu-Zr metallic glass as standard examples of continuous random network and random packing structures. In silica glass, the method classified the atomic rings as short-range and medium-range orders and unveiled hierarchical ring structures among them. These detailed geometric characterizations clarified a real space origin of the first sharp diffraction peak and also indicated that PDs contain information on elastic response. Even in the Lennard-Jones system and Cu-Zr metallic glass, the hierarchical structures in the atomic configurations were derived in a similar way using PDs, although the glass structures and properties substantially differ from silica glass. These results suggest that the PDs provide a unified method that extracts greater depth of geometric information in amorphous solids than conventional methods. PMID:27298351

  15. Hierarchically nanostructured hydroxyapatite: hydrothermal synthesis, morphology control, growth mechanism, and biological activity

    PubMed Central

    Ma, Ming-Guo

    2012-01-01

    Hierarchically nanosized hydroxyapatite (HA) with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours. Objective The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA) with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks. Methods A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Results HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did not decrease with the increasing concentration of hierarchically nanostructured HA added. Conclusion A novel, simple and reliable hydrothermal route had been developed for the synthesis of

  16. Graphene-based three-dimensional hierarchical sandwich-type architecture for high-performance Li/S batteries.

    PubMed

    Chen, Renjie; Zhao, Teng; Lu, Jun; Wu, Feng; Li, Li; Chen, Junzheng; Tan, Guoqiang; Ye, Yusheng; Amine, Khalil

    2013-10-09

    A multiwalled carbon nanotube/sulfur (MWCNT@S) composite with core-shell structure was successfully embedded into the interlay galleries of graphene sheets (GS) through a facile two-step assembly process. Scanning and transmission electron microscopy images reveal a 3D hierarchical sandwich-type architecture of the composite GS-MWCNT@S. The thickness of the S layer on the MWCNTs is ~20 nm. Raman spectroscopy, X-ray diffraction, thermogravimetric analysis, and energy-dispersive X-ray analysis confirm that the sulfur in the composite is highly crystalline with a mass loading up to 70% of the composite. This composite is evaluated as a cathode material for Li/S batteries. The GS-MWCNT@S composite exhibits a high initial capacity of 1396 mAh/g at a current density of 0.2C (1C = 1672 mA/g), corresponding to 83% usage of the sulfur active material. Much improved cycling stability and rate capability are achieved for the GS-MWCNT@S composite cathode compared with the composite lacking GS or MWCNT. The superior electrochemical performance of the GS-MWCNT@S composite is mainly attributed to the synergistic effects of GS and MWCNTs, which provide a 3D conductive network for electron transfer, open channels for ion diffusion, strong confinement of soluble polysulfides, and effective buffer for volume expansion of the S cathode during discharge.

  17. Electroencephalography-based real-time cortical monitoring system that uses hierarchical Bayesian estimations for the brain-machine interface.

    PubMed

    Choi, Kyuwan

    2014-06-01

    In this study, a real-time cortical activity monitoring system was constructed, which could estimate cortical activities every 125 milliseconds over 2,240 vertexes from 64 channel electroencephalography signals through the Hierarchical Bayesian estimation that uses functional magnetic resonance imaging data as its prior information. Recently, functional magnetic resonance imaging has mostly been used in the neurofeedback field because it allows for high spatial resolution. However, in functional magnetic resonance imaging, the time for the neurofeedback information to reach the patient is delayed several seconds because of its poor temporal resolution. Therefore, a number of problems need to be solved to effectively implement feedback training paradigms in patients. To address this issue, this study used a new cortical activity monitoring system that improved both spatial and temporal resolution by using both functional magnetic resonance imaging data and electroencephalography signals in conjunction with one another. This system is advantageous as it can improve applications in the fields of real-time diagnosis, neurofeedback, and the brain-machine interface.

  18. Hierarchical Bayesian analysis of outcome- and process-based social preferences and beliefs in Dictator Games and sequential Prisoner's Dilemmas.

    PubMed

    Aksoy, Ozan; Weesie, Jeroen

    2014-05-01

    In this paper, using a within-subjects design, we estimate the utility weights that subjects attach to the outcome of their interaction partners in four decision situations: (1) binary Dictator Games (DG), second player's role in the sequential Prisoner's Dilemma (PD) after the first player (2) cooperated and (3) defected, and (4) first player's role in the sequential Prisoner's Dilemma game. We find that the average weights in these four decision situations have the following order: (1)>(2)>(4)>(3). Moreover, the average weight is positive in (1) but negative in (2), (3), and (4). Our findings indicate the existence of strong negative and small positive reciprocity for the average subject, but there is also high interpersonal variation in the weights in these four nodes. We conclude that the PD frame makes subjects more competitive than the DG frame. Using hierarchical Bayesian modeling, we simultaneously analyze beliefs of subjects about others' utility weights in the same four decision situations. We compare several alternative theoretical models on beliefs, e.g., rational beliefs (Bayesian-Nash equilibrium) and a consensus model. Our results on beliefs strongly support the consensus effect and refute rational beliefs: there is a strong relationship between own preferences and beliefs and this relationship is relatively stable across the four decision situations.

  19. Estimation of inter-modular connectivity from the local field potentials in a hierarchical modular network

    NASA Astrophysics Data System (ADS)

    Cui, Xue-Mei; Kim, Won Sup; Hwang, Dong-Uk; Han, Seung Kee

    2015-05-01

    We propose a method of estimating inter-modular connectivity in a hierarchical modular network. The method is based on an analysis of inverse phase synchronization applied to the local field potentials on a hierarchical modular network of phase oscillators. For a strong-coupling strength, the inverse phase synchronization index of the local field potentials for two modules depends linearly on the corresponding inter-modular connectivity defined as the number of links connecting the modules. The method might enable us to estimate the inter-modular connectivity in various complex systems from the inverse phase synchronization index of the mesoscopic modular activities.

  20. Adaptive variable structure hierarchical fuzzy control for a class of high-order nonlinear dynamic systems.

    PubMed

    Mansouri, Mohammad; Teshnehlab, Mohammad; Aliyari Shoorehdeli, Mahdi

    2015-05-01

    In this paper, a novel adaptive hierarchical fuzzy control system based on the variable structure control is developed for a class of SISO canonical nonlinear systems in the presence of bounded disturbances. It is assumed that nonlinear functions of the systems be completely unknown. Switching surfaces are incorporated into the hierarchical fuzzy control scheme to ensure the system stability. A fuzzy soft switching system decides the operation area of the hierarchical fuzzy control and variable structure control systems. All the nonlinearly appeared parameters of conclusion parts of fuzzy blocks located in different layers of the hierarchical fuzzy control system are adjusted through adaptation laws deduced from the defined Lyapunov function. The proposed hierarchical fuzzy control system reduces the number of rules and consequently the number of tunable parameters with respect to the ordinary fuzzy control system. Global boundedness of the overall adaptive system and the desired precision are achieved using the proposed adaptive control system. In this study, an adaptive hierarchical fuzzy system is used for two objectives; it can be as a function approximator or a control system based on an intelligent-classic approach. Three theorems are proven to investigate the stability of the nonlinear dynamic systems. The important point about the proposed theorems is that they can be applied not only to hierarchical fuzzy controllers with different structures of hierarchical fuzzy controller, but also to ordinary fuzzy controllers. Therefore, the proposed algorithm is more general. To show the effectiveness of the proposed method four systems (two mechanical, one mathematical and one chaotic) are considered in simulations. Simulation results demonstrate the validity, efficiency and feasibility of the proposed approach to control of nonlinear dynamic systems.

  1. Hierarchical surface patterning of Ni- and Be-free Ti- and Zr-based bulk metallic glasses by thermoplastic net-shaping.

    PubMed

    Sarac, Baran; Bera, Supriya; Balakin, Sascha; Stoica, Mihai; Calin, Mariana; Eckert, Jürgen

    2017-04-01

    In order to establish a strong cell-material interaction, the surface topography of the implant material plays an important role. This contribution aims to analyze the formation kinetics of nickel and beryllium-free Ti- and Zr-based Bulk Metallic Glasses (BMGs) with potential biomedical applications. The surface patterning of the BMGs is achieved by thermoplastic net-shaping (TPN) into anisotropically etched cavities of silicon chips. The forming kinetics of the BMG alloys is assessed by thermal and mechanical measurements to determine the most suitable processing temperature and time, and load applied. Array of pyramidal micropatterns with a tip resolution down to 50nm is achievable for the Zr-BMG, where the generated hierarchical features are crucial for surface functionalization, acting as topographic cues for cell attachment. The unique processability and intrinsic properties of this new class of amorphous alloys make them competitive with the conventional biomaterials.

  2. Hierarchical Naive Bayes for genetic association studies

    PubMed Central

    2012-01-01

    Background Genome Wide Association Studies represent powerful approaches that aim at disentangling the genetic and molecular mechanisms underlying complex traits. The usual "one-SNP-at-the-time" testing strategy cannot capture the multi-factorial nature of this kind of disorders. We propose a Hierarchical Naïve Bayes classification model for taking into account associations in SNPs data characterized by Linkage Disequilibrium. Validation shows that our model reaches classification performances superior to those obtained by the standard Naïve Bayes classifier for simulated and real datasets. Methods In the Hierarchical Naïve Bayes implemented, the SNPs mapping to the same region of Linkage Disequilibrium are considered as "details" or "replicates" of the locus, each contributing to the overall effect of the region on the phenotype. A latent variable for each block, which models the "population" of correlated SNPs, can be then used to summarize the available information. The classification is thus performed relying on the latent variables conditional probability distributions and on the SNPs data available. Results The developed methodology has been tested on simulated datasets, each composed by 300 cases, 300 controls and a variable number of SNPs. Our approach has been also applied to two real datasets on the genetic bases of Type 1 Diabetes and Type 2 Diabetes generated by the Wellcome Trust Case Control Consortium. Conclusions The approach proposed in this paper, called Hierarchical Naïve Bayes, allows dealing with classification of examples for which genetic information of structurally correlated SNPs are available. It improves the Naïve Bayes performances by properly handling the within-loci variability. PMID:23095471

  3. High-performance supercapacitor and lithium-ion battery based on 3D hierarchical NH4F-induced nickel cobaltate nanosheet-nanowire cluster arrays as self-supported electrodes

    NASA Astrophysics Data System (ADS)

    Chen, Yuejiao; Qu, Baihua; Hu, Lingling; Xu, Zhi; Li, Qiuhong; Wang, Taihong

    2013-09-01

    A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions at the nanoscale, fast ion and electron transfer and good strain accommodation. Thus, when it is used for supercapacitor testing, a specific capacitance of 1069 F g-1 at a very high current density of 100 A g-1 was obtained. Even after more than 10 000 cycles at various large current densities, a capacitance of 2000 F g-1 at 10 A g-1 with 93.8% retention can be achieved. It also exhibits a high-power density (26.1 kW kg-1) at a discharge current density of 80 A g-1. When used as an anode material for lithium-ion batteries (LIBs), it presents a high reversible capacity of 976 mA h g-1 at a rate of 200 mA g-1 with good cycling stability and rate capability. This array material is rarely used as an anode material. Our results show that this unique 3D hierarchical porous nickel cobaltite is promising for electrochemical energy applications.A facile hydrothermal method is developed for large-scale production of three-dimensional (3D) hierarchical porous nickel cobaltate nanowire cluster arrays derived from nanosheet arrays with robust adhesion on Ni foam. Based on the morphology evolution upon reaction time, a possible formation process is proposed. The role of NH4F in formation of the structure has also been investigated based on different NH4F amounts. This unique structure significantly enhances the electroactive surface areas of the NiCo2O4 arrays, leading to better interfacial/chemical distributions

  4. Guided hierarchical co-assembly of soft patchy nanoparticles

    NASA Astrophysics Data System (ADS)

    Gröschel, André H.; Walther, Andreas; Löbling, Tina I.; Schacher, Felix H.; Schmalz, Holger; Müller, Axel H. E.

    2013-11-01

    The concept of hierarchical bottom-up structuring commonly encountered in natural materials provides inspiration for the design of complex artificial materials with advanced functionalities. Natural processes have achieved the orchestration of multicomponent systems across many length scales with very high precision, but man-made self-assemblies still face obstacles in realizing well-defined hierarchical structures. In particle-based self-assembly, the challenge is to program symmetries and periodicities of superstructures by providing monodisperse building blocks with suitable shape anisotropy or anisotropic interaction patterns (`patches'). Irregularities in particle architecture are intolerable because they generate defects that amplify throughout the hierarchical levels. For patchy microscopic hard colloids, this challenge has been approached by using top-down methods (such as metal shading or microcontact printing), enabling molecule-like directionality during aggregation. However, both top-down procedures and particulate systems based on molecular assembly struggle to fabricate patchy particles controllably in the desired size regime (10-100nm). Here we introduce the co-assembly of dynamic patchy nanoparticles--that is, soft patchy nanoparticles that are intrinsically self-assembled and monodisperse--as a modular approach for producing well-ordered binary and ternary supracolloidal hierarchical assemblies. We bridge up to three hierarchical levels by guiding triblock terpolymers (length scale ~10nm) to form soft patchy nanoparticles (20-50nm) of different symmetries that, in combination, co-assemble into substructured, compartmentalized materials (>10μm) with predictable and tunable nanoscale periodicities. We establish how molecular control over polymer composition programs the building block symmetries and regulates particle positioning, offering a route to well-ordered mixed mesostructures of high complexity.

  5. Spin-glass behavior of a hierarchically-organized, hybrid microporous material, based on an extended framework of octanuclear iron-oxo units.

    PubMed

    Cao, Xin-Yi; Hubbard, Jeremiah W; Guerrero-Medina, Jennifer; Hernández-Maldonado, Arturo J; Mathivathanan, Logesh; Rinaldi, Carlos; Sanakis, Yiannis; Raptis, Raphael G

    2015-02-21

    Inspired by the stepwise addition of octanuclear iron units into mammalian ferritin, a "stop-and-go" synthesis strategy was used to prepare two microporous (Langmuir surface area, 490 m(2) g(-1); effective pore size, 4-5 Å) hierarchical materials {[Fe8(μ4-O)4(μ-pz)12Cl0.3(μ-O)1.85}n () and {[Fe8(μ4-O)4(μ-4-Me-pz)12Cl0.4(μ-O)1.8}n (), which are new members of the EO2 family of polymeric materials (E = C, Si and Ge). The secondary building units (SBUs) E = [Fe8(μ4-O)4(μ-4-R-pz)12] (Fe8) are nanoscale pseudo-spherical clusters, rather than single atoms, forming μ-oxo Fe-O-Fe linkages between Fe8-SBUs. The characteristic Fe-O-Fe asymmetric stretching mode in the infrared (IR) spectra of these compounds appearing at around 800 cm(-1) suggest the formation of approximately linear μ-oxo Fe-O-Fe linkages between Fe8-SBUs in and . We employ the concept of continuous random network (CRN) to describe for the first time the framework features of a Fe8-based amorphous materials, in which the average connecting numbers of each Fe8-cluster are ∼3.7 and ∼3.6 for and , respectively. (57)Fe-Mössbauer spectroscopic analysis provides insights to the intercluster connectivity of and on one hand and to their magnetic properties on the other, evident by a magnetic split sextet below 30 K. The combination of Mössbauer spectroscopy and magnetism measurements reveals a spin-glass behavior with Tg of ∼30 K. The hierarchical porous materials and straddle the gap between metal oxides and metal-organic frameworks (MOFs). This study may open an alternative way for the development of multifunctional materials based on high nuclearity metal clusters.

  6. POLLUTION PREVENTION IN THE EARLY STAGES OF HIERARCHICAL PROCESS DESIGN

    EPA Science Inventory

    Hierarchical methods are often used in the conceptual stages of process design to synthesize and evaluate process alternatives. In this work, the methods of hierarchical process design will be focused on environmental aspects. In particular, the design methods will be coupled to ...

  7. Create and Publish a Hierarchical Progressive Survey (HiPS)

    NASA Astrophysics Data System (ADS)

    Fernique, P.; Boch, T.; Pineau, F.; Oberto, A.

    2014-05-01

    Since 2009, the CDS promotes a method for visualizing based on the HEALPix sky tessellation. This method, called “Hierarchical Progressive Survey" or HiPS, allows one to display a survey progressively. It is particularly suited for all-sky surveys or deep fields. This visualization method is now integrated in several applications, notably Aladin, the SiTools/MIZAR CNES framework, and the recent HTML5 “Aladin Lite". Also, more than one hundred surveys are already available in this view mode. In this article, we will present the progress concerning this method and its recent adaptation to the astronomical catalogs such as the GAIA simulation.

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

    PubMed

    Nitta, Tohru

    2016-06-30

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

  9. Biomimetic cellular metals-using hierarchical structuring for energy absorption.

    PubMed

    Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

    2016-07-19

    Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form

  10. Efficient scalable algorithms for hierarchically semiseparable matrices

    SciTech Connect

    Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de

    2011-09-14

    Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.

  11. A hierarchical exact accelerated stochastic simulation algorithm

    NASA Astrophysics Data System (ADS)

    Orendorff, David; Mjolsness, Eric

    2012-12-01

    A new algorithm, "HiER-leap" (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled "blocks" and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms.

  12. Hierarchical Nanoceramics for Industrial Process Sensors

    SciTech Connect

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

    2011-07-15

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

  13. Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

    SciTech Connect

    Nash, Stephen G.

    2013-11-11

    The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

  14. System and method for knowledge based matching of users in a network

    DOEpatents

    Verspoor, Cornelia Maria; Sims, Benjamin Hayden; Ambrosiano, John Joseph; Cleland, Timothy James

    2011-04-26

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

  15. Electrochemical properties and controlled-synthesis of hierarchical {beta}-Ni(OH){sub 2} micro-flowers and hollow microspheres

    SciTech Connect

    Wang, Yong; Zhu, Qingshan

    2010-12-15

    {beta}-Ni(OH){sub 2} hierarchical micro-flowers, hierarchical hollow microspheres and nanosheets were synthesized via a facile, single-step and selected-control hydrothermal method. Both hierarchical micro-flowers and hierarchical hollow microspheres were built from two-dimensional nanosheets with thickness of 50-100 nm. The as-obtained products were characterized by Brunauer-Emmett-Teller (BET) surface area analysis, X-ray powder diffraction (XRD) and field emission scanning electron microscopy (FESEM). It was observed that marked morphological changes in {beta}-Ni(OH){sub 2} depended on the initial concentrations of Ni{sup 2+} ions and glycine. A possible growth mechanism was proposed based on experimental results. In addition, the effect of morphology on the electrochemical properties was also investigated. Both hierarchical micro-flowers and hierarchical hollow microspheres exhibited enhanced specific capacity and high-rate discharge ability as compared with pure Ni(OH){sub 2} nanosheets. Investigations confirmed that hierarchical structures had a pronounced influence upon the electrochemical performance of nickel hydroxide.

  16. A hierarchical model for spatial capture-recapture data

    USGS Publications Warehouse

    Royle, J. Andrew; Young, K.V.

    2008-01-01

    Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  18. Effects of acid on the microstructures and properties of three-dimensional TiO2 hierarchical structures by solvothermal method.

    PubMed

    Zhou, Jing; Song, Bin; Zhao, Gaoling; Han, Gaorong

    2012-04-13

    Three-dimensional (3D) TiO2 hierarchical structures with various microstructures have been successfully synthesized via a surfactant-free and single-step solvothermal route, in which hydrochloric acid (HCl), nitric acid (HNO3), and acetic acid (HAc) are employed as the acid medium, respectively. The effects of acid medium on the microstructures and properties of 3D TiO2 hierarchical structure have been studied. The results indicate that 3D dandelion-like microspheres assembled of radial rutile nanorods are obtained in the sample prepared with HCl. Both the fraction of rutile and the diameter of nanorod enhance with the increasing HCl concentration. For the products derived from either HNO3 or HAc, 3D spheres composed of anatase nanoparticles are present. The 3D dandelion-like TiO2 hierarchical structures show low reflectance and efficient light harvesting since this ordered rod geometry offers a light-transfer path for incident light as well as multiple reflective and scattering effects. Moreover, 3D TiO2 with this unique topology shows superior photocatalytic activity despite low surface area, which can be ascribed to the enhanced light harvesting, fast electron transport, and low electron/hole recombination loss.

  19. Effects of acid on the microstructures and properties of three-dimensional TiO2 hierarchical structures by solvothermal method

    PubMed Central

    2012-01-01

    Three-dimensional (3D) TiO2 hierarchical structures with various microstructures have been successfully synthesized via a surfactant-free and single-step solvothermal route, in which hydrochloric acid (HCl), nitric acid (HNO3), and acetic acid (HAc) are employed as the acid medium, respectively. The effects of acid medium on the microstructures and properties of 3D TiO2 hierarchical structure have been studied. The results indicate that 3D dandelion-like microspheres assembled of radial rutile nanorods are obtained in the sample prepared with HCl. Both the fraction of rutile and the diameter of nanorod enhance with the increasing HCl concentration. For the products derived from either HNO3 or HAc, 3D spheres composed of anatase nanoparticles are present. The 3D dandelion-like TiO2 hierarchical structures show low reflectance and efficient light harvesting since this ordered rod geometry offers a light-transfer path for incident light as well as multiple reflective and scattering effects. Moreover, 3D TiO2 with this unique topology shows superior photocatalytic activity despite low surface area, which can be ascribed to the enhanced light harvesting, fast electron transport, and low electron/hole recombination loss. PMID:22500985

  20. Design and Tailoring of the 3D Macroporous Hydrous RuO2 Hierarchical Architectures with a Hard-Template Method for High-Performance Supercapacitors.

    PubMed

    Peng, Zhikun; Liu, Xu; Meng, Huan; Li, Zhongjun; Li, Baojun; Liu, Zhongyi; Liu, Shouchang

    2017-02-08

    In this work, RuO2 honeycomb networks (RHCs) and hollow spherical structures (RHSs) were rationally designed and synthesized with modified-SiO2 as a sacrificial template via two hydrothermal approaches. At a high current density of 20 A g(-1), the two hierarchical porous RuO2·xH2O frameworks showed the specific capacitance as high as 628 and 597 F g(-1); this is about 80% and 75% of the capacitance retention of 0.5 A g(-1) for RHCs and RHSs, respectively. Even after 4000 cycles at 5 A g(-1), the RHCs and RHSs can still remain at 86% and 91% of their initial specific capacitances, respectively. These two hierarchical frameworks have a well-defined pathway that benefits for the transmission/diffusion of electrolyte and surface redox reactions. As a result, they exhibit good supercapacitor performance in both acid (H2SO4) and alkaline (KOH) electrolytes. As compared to RuO2 bulk structure and similar RuO2 counterpart reported in pseudocapacitors, the two hierarchical porous RuO2·xH2O frameworks have better energy storage capabilities, high-rate performance, and excellent cycling stability.

  1. Fabrication of Hierarchical Layer-by-Layer Assembled Diamond-based Core-Shell Nanocomposites as Highly Efficient Dye Absorbents for Wastewater Treatment

    PubMed Central

    Zhao, Xinna; Ma, Kai; Jiao, Tifeng; Xing, Ruirui; Ma, Xilong; Hu, Jie; Huang, Hao; Zhang, Lexin; Yan, Xuehai

    2017-01-01

    The effective chemical modification and self-assembly of diamond-based hierarchical composite materials are of key importance for a broad range of diamond applications. Herein, we report the preparation of novel core-shell diamond-based nanocomposites for dye adsorption toward wastewater treatment through a layer-by-layer (LbL) assembled strategy. The synthesis of the reported composites began with the carboxyl functionalization of microdiamond by the chemical modification of diamond@graphene oxide composite through the oxidation of diamond@graphite. The carboxyl-terminated microdiamond was then alternatively immersed in the aqueous solution of amine-containing polyethylenimine and carboxyl-containing poly acrylic acid, which led to the formation of adsorption layer on diamond surface. Alternating (self-limiting) immersions in the solutions of the amine-containing and carboxyl-containing polymers were continued until the desired number of shell layers were formed around the microdiamond. The obtained core-shell nanocomposites were successfully synthesized and characterized by morphological and spectral techniques, demonstrating higher surface areas and mesoporous structures for good dye adsorption capacities than nonporous solid diamond particles. The LbL-assembled core-shell nanocomposites thus obtained demonstrated great adsorption capacity by using two model dyes as pollutants for wastewater treatment. Therefore, the present work on LbL-assembled diamond-based composites provides new alternatives for developing diamond hybrids as well as nanomaterials towards wastewater treatment applications. PMID:28272452

  2. Fabrication of Hierarchical Layer-by-Layer Assembled Diamond-based Core-Shell Nanocomposites as Highly Efficient Dye Absorbents for Wastewater Treatment

    NASA Astrophysics Data System (ADS)

    Zhao, Xinna; Ma, Kai; Jiao, Tifeng; Xing, Ruirui; Ma, Xilong; Hu, Jie; Huang, Hao; Zhang, Lexin; Yan, Xuehai

    2017-03-01

    The effective chemical modification and self-assembly of diamond-based hierarchical composite materials are of key importance for a broad range of diamond applications. Herein, we report the preparation of novel core-shell diamond-based nanocomposites for dye adsorption toward wastewater treatment through a layer-by-layer (LbL) assembled strategy. The synthesis of the reported composites began with the carboxyl functionalization of microdiamond by the chemical modification of diamond@graphene oxide composite through the oxidation of diamond@graphite. The carboxyl-terminated microdiamond was then alternatively immersed in the aqueous solution of amine-containing polyethylenimine and carboxyl-containing poly acrylic acid, which led to the formation of adsorption layer on diamond surface. Alternating (self-limiting) immersions in the solutions of the amine-containing and carboxyl-containing polymers were continued until the desired number of shell layers were formed around the microdiamond. The obtained core-shell nanocomposites were successfully synthesized and characterized by morphological and spectral techniques, demonstrating higher surface areas and mesoporous structures for good dye adsorption capacities than nonporous solid diamond particles. The LbL-assembled core-shell nanocomposites thus obtained demonstrated great adsorption capacity by using two model dyes as pollutants for wastewater treatment. Therefore, the present work on LbL-assembled diamond-based composites provides new alternatives for developing diamond hybrids as well as nanomaterials towards wastewater treatment applications.

  3. Grinding Wheel Condition Monitoring with Hidden Markov Model-Based Clustering Methods

    SciTech Connect

    Liao, T. W.; Hua, G; Qu, Jun; Blau, Peter Julian

    2006-01-01

    Hidden Markov model (HMM) is well known for sequence modeling and has been used for condition monitoring. However, HMM-based clustering methods are developed only recently. This article proposes a HMM-based clustering method for monitoring the condition of grinding wheel used in grinding operations. The proposed method first extract features from signals based on discrete wavelet decomposition using a moving window approach. It then generates a distance (dissimilarity) matrix using HMM. Based on this distance matrix several hierarchical and partitioning-based clustering algorithms are applied to obtain clustering results. The proposed methodology was tested with feature sequences extracted from acoustic emission signals. The results show that clustering accuracy is dependent upon cutting condition. Higher material removal rate seems to produce more discriminatory signals/features than lower material removal rate. The effect of window size, wavelet decomposition level, wavelet basis, clustering algorithm, and data normalization were also studied.

  4. Advanced hierarchical distance sampling

    USGS Publications Warehouse

    Royle, Andy

    2016-01-01

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

  5. Full hierarchic versus non-hierarchic classification approaches for mapping sealed surfaces at the rural-urban fringe using high-resolution satellite data.

    PubMed

    De Roeck, Tim; Van de Voorde, Tim; Canters, Frank

    2009-01-01

    Since 2008 more than half of the world population is living in cities and urban sprawl is continuing. Because of these developments, the mapping and monitoring of urban environments and their surroundings is becoming increasingly important. In this study two object-oriented approaches for high-resolution mapping of sealed surfaces are compared: a standard non-hierarchic approach and a full hierarchic approach using both multi-layer perceptrons and decision trees as learning algorithms. Both methods outperform the standard nearest neighbour classifier, which is used as a benchmark scenario. For the multi-layer perceptron approach, applying a hierarchic classification strategy substantially increases the accuracy of the classification. For the decision tree approach a one-against-all hierarchic classification strategy does not lead to an improvement of classification accuracy compared to the standard all-against-all approach. Best results are obtained with the hierarchic multi-layer perceptron classification strategy, producing a kappa value of 0.77. A simple shadow reclassification procedure based on characteristics of neighbouring objects further increases the kappa value to 0.84.

  6. Hierarchical tapered bar elements undergoing axial deformation

    NASA Technical Reports Server (NTRS)

    Ganesan, N.; Thampi, S. K.

    1992-01-01

    A method is described to model the dynamics of tapered axial bars of various cross sections based on the well-known Craig/Bampton component mode synthesis technique. This element is formed in terms of the static constraint modes and interface restrained normal modes. This is in contrast with the finite elements as implemented in NASTRAN where the interface restrained normal modes are neglected. These normal modes are in terms of Bessel functions. Restoration of a few of these modes leads to higher accuracy with fewer generalized coordinates. The proposed models are hierarchical so that all lower order element matrices are embedded in higher order element matrices. The advantages of this formulation compared to standard NASTRAN truss element formulation are demonstrated through simple numerical examples.

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

    NASA Astrophysics Data System (ADS)

    Chu, Fuqiang; Wu, Xiaomin

    2016-05-01

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

  8. Managing Clustered Data Using Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  9. A hierarchical clustering algorithm for MIMD architecture.

    PubMed

    Du, Zhihua; Lin, Feng

    2004-12-01

    Hierarchical clustering is the most often used method for grouping similar patterns of gene expression data. A fundamental problem with existing implementations of this clustering method is the inability to handle large data sets within a reasonable time and memory resources. We propose a parallelized algorithm of hierarchical clustering to solve this problem. Our implementation on a multiple instruction multiple data (MIMD) architecture shows considerable reduction in computational time and inter-node communication overhead, especially for large data sets. We use the standard message passing library, message passing interface (MPI) for any MIMD systems.

  10. Hierarchical Metal–Organic Framework Hybrids: Perturbation-Assisted Nanofusion Synthesis

    SciTech Connect

    Yue, Yanfeng; Fulvio, Pasquale F.; Dai, Sheng

    2015-12-04

    Metal–organic frameworks (MOFs) represent a new family of microporous materials; however, microporous–mesoporous hierarchical MOF materials have been less investigated because of the lack of simple, reliable methods to introduce mesopores to the crystalline microporous particles. State-of-the-art MOF hierarchical materials have been prepared by ligand extension methods or by using a template, resulting in intrinsic mesopores of longer ligands or replicated pores from template agents, respectively. However, mesoporous MOF materials obtained through ligand extension often collapse in the absence of guest molecules, which dramatically reduces the size of the pore aperture. Although the template-directed strategy allows for the preparation of hierarchical materials with larger mesopores, the latter requires a template removal step, which may result in the collapse of the implemented mesopores. Recently, a general template-free synthesis of hierarchical microporous crystalline frameworks, such as MOFs and Prussian blue analogues (PBAs), has been reported. Our new method is based on the kinetically controlled precipitation (perturbation), with simultaneous condensation and redissolution of polymorphic nanocrystallites in the mother liquor. This method further eliminates the use of extended organic ligands and the micropores do not collapse upon removal of trapped guest solvent molecules, thus yielding hierarchical MOF materials with intriguing porosity in the gram scale. The hierarchical MOF materials prepared in this way exhibited exceptional properties when tested for the adsorption of large organic dyes over their corresponding microporous frameworks, due to the enhanced pore accessibility and electrolyte diffusion within the mesopores. As for PBAs, the pore size distribution of these materials can be tailored by changing the metals substituting Fe cations in the PB lattice. For these, the textural mesopores increased from approximately 10 nm for Cu analogue (meso

  11. Analysis hierarchical model for discrete event systems

    NASA Astrophysics Data System (ADS)

    Ciortea, E. M.

    2015-11-01

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

  12. Intelligent controllers as hierarchical stochastic automata.

    PubMed

    Lima, P U; Saridis, G N

    1999-01-01

    This paper introduces a design methodology for intelligent controllers, based on a hierarchical linguistic model of command translation by tasks-primitive tasks-primitive actions, and on a two-stage hierarchical learning stochastic automaton that models the translation interfaces of a three-level hierarchical intelligent controller. The methodology relies on the designer's a priori knowledge on how to implement by primitive actions the different primitive tasks which define the intelligent controller. A cost function applicable to any primitive task is introduced and used to learn on-line the optimal choices from the corresponding predesigned sets of primitive actions. The same concept applies to the optimal tasks for each command, whose choice is based on conflict sets of stochastic grammar productions. Optional designs can be compared using this performance measure. A particular design evolves towards the command translation (by tasks-primitive tasks-primitive actions) that minimizes the cost function.

  13. How Hierarchical Topics Evolve in Large Text Corpora.

    PubMed

    Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

    2014-12-01

    Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

  14. Facile Preparation of Hierarchical Structures Using Crystallization-Kinetics Driven Self-Assembly.

    PubMed

    Cai, Jinguang; Lv, Chao; Watanabe, Akira

    2015-08-26

    Hierarchical structures (HSs) constructed by nanoparticle-based building blocks possess not only the properties of the primary building blocks but also collective properties of the assemblies. Here we report the facile preparation of hierarchical Ag nanoparticles/polyhedral oligomeric silsequioxane molecule (POSS) hybrid branched structures within tens of seconds by using spin-coating and doctor-blade methods. An assembly mechanism mainly controlled by POSS-crystallization kinetics and space resistance of Ag nanoparticles toward the diffusion of POSS molecules was tentatively proposed. It was demonstrated as a universal method for the preparation of hierarchical hybrid branched structures on arbitrary substrates, as well as by using other different POSS and inorganic nanoparticles. As a demonstration, Ag hierarchical structures obtained by heat treatment exhibit excellent SERS performance with enhancement factors as high as on the order of 10(7), making them promising sensors for the detection of trace amount of analyte adsorbed on the surface. Two-dimensional SERS mapping was also demonstrated by using a direct imaging system with high mapping speed and high resolution. Moreover, the substrates with Ag hierarchical structures were used as a SERS sensor for in situ detection due to the excellent SERS performance and stability of the structures.

  15. Free-standing iridium and rhodium-based hierarchically-coiled ultrathin nanosheets for highly selective reduction of nitrobenzene to azoxybenzene under ambient conditions.

    PubMed

    Zhang, Zhi-Ping; Wang, Xin-Yu; Yuan, Kun; Zhu, Wei; Zhang, Tao; Wang, Yu-Hao; Ke, Jun; Zheng, Xiao-Yu; Yan, Chun-Hua; Zhang, Ya-Wen

    2016-08-25

    The fabrication of atom-layered two dimensional (2D) noble metal nanosheets (NSs) in a face-centered cubic (fcc) structure is of broad scientific and technological importance, yet this remains a challenge due to the intrinsic cubic symmetry and high surface energy of fcc noble metals. Herein, we report a solid-liquid interface mediated 2D growth method towards the synthesis of hierarchically-coiled ultrathin Ir NSs (thickness <2 nm) and Rh NSs (0.8 nm thick), and bimetallic Ir-Rh NSs (1.2 nm thick) and Pt-Rh NSs (1.2 nm thick) using the benzyl alcohol solvothermal approach. The formation of NSs was attributed to the 2D oriented attachment of tiny seeds through the lateral growth stemming from the abundant defect sites of the seeds produced in the heterogeneous system. The free-standing Ir NSs, Rh NSs and Ir-Rh NSs exhibited high selectivities (from 83.9% to 88.5%) towards the selective reduction of nitrobenzene to azoxybenzene in ethanol at room temperature with 1 atm of hydrogen, because the condensation step of nitrosobenzene (PhNO) and phenylhydroxylamine (PhNHOH) was more exothermic than the dissociation step of Ph-NHOH on the (111) facets of the NSs under alkaline conditions, as indicated by density functional theory (DFT) calculations.

  16. Time Synchronization in Hierarchical TESLA Wireless Sensor Networks

    SciTech Connect

    Jason L. Wright; Milos Manic

    2009-08-01

    Time synchronization and event time correlation are important in wireless sensor networks. In particular, time is used to create a sequence events or time line to answer questions of cause and effect. Time is also used as a basis for determining the freshness of received packets and the validity of cryptographic certificates. This paper presents secure method of time synchronization and event time correlation for TESLA-based hierarchical wireless sensor networks. The method demonstrates that events in a TESLA network can be accurately timestamped by adding only a few pieces of data to the existing protocol.

  17. Hierarchical clustering techniques for image database organization and summarization

    NASA Astrophysics Data System (ADS)

    Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    This paper investigates clustering techniques as a method of organizing image databases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglomerative clustering techniques are studied as a method of organizing features space as well as summarizing image groups by the selection of a few appropriate representatives. Retrieval performance using both single and multiple level hierarchies are experimented with and the algorithms show an interesting relationship between the top k correct retrievals and the number of comparisons required. Some arguments are given to support the use of such cluster-based techniques for managing distributed image databases.

  18. Research on BOM based composable modeling method

    NASA Astrophysics Data System (ADS)

    Zhang, Mingxin; He, Qiang; Gong, Jianxing

    2013-03-01

    Composable modeling method has been a research hotpot in the area of Modeling and Simulation for a long time. In order to increase the reuse and interoperability of BOM based model, this paper put forward a composable modeling method based on BOM, studied on the basic theory of composable modeling method based on BOM, designed a general structure of the coupled model based on BOM, and traversed the structure of atomic and coupled model based on BOM. At last, the paper introduced the process of BOM based composable modeling and made a conclusion on composable modeling method based on BOM. From the prototype we developed and accumulative model stocks, we found this method could increase the reuse and interoperability of models.

  19. Hierarchical rutile TiO2 flower cluster-based high efficiency dye-sensitized solar cells via direct hydrothermal growth on conducting substrates.

    PubMed

    Ye, Meidan; Liu, Hsiang-Yu; Lin, Changjian; Lin, Zhiqun

    2013-01-28

    Dye-sensitized solar cells (DSSCs) based on hierarchical rutile TiO(2) flower clusters prepared by a facile, one-pot hydrothermal process exhibit a high efficiency. Complex yet appealing rutile TiO(2) flower films are, for the first time, directly hydrothermally grown on a transparent conducting fluorine-doped tin oxide (FTO) substrate. The thickness and density of as-grown flower clusters can be readily tuned by tailoring growth parameters, such as growth time, the addition of cations of different valence and size, initial concentrations of precursor and cation, growth temperature, and acidity. Notably, the small lattice mismatch between the FTO substrate and rutile TiO(2) renders the epitaxial growth of a compact rutile TiO(2) layer on the FTO glass. Intriguingly, these TiO(2) flower clusters can then be exploited as photoanodes to produce DSSCs, yielding a power conversion efficiency of 2.94% despite their rutile nature, which is further increased to 4.07% upon the TiCl(4) treatment.

  20. A novel signal amplification strategy of an electrochemical aptasensor for kanamycin, based on thionine functionalized graphene and hierarchical nanoporous PtCu.

    PubMed

    Qin, Xiaoli; Yin, Yan; Yu, Huijing; Guo, Wenjuan; Pei, Meishan

    2016-03-15

    An ultrasensitive electrochemical aptasensor for the quantitative detection of kanamycin antibiotic was fabricated based on a novel signal amplification strategy. This aptasensor was developed using thionine functionalized graphene (GR-TH) and hierarchical nanoporous (HNP) PtCu alloy as biosensing substrates for the first time. HNP-PtCu alloy with controllable bimodal ligament/pore distributions was successfully prepared by two-step dealloying of a well-designed PtCuAl precursor alloy combined with an annealing operation. GR-TH composite was synthesized by one-step reduction of graphene oxide (GO) in TH solution. Greatly amplified sensitivity was achieved by using GR-TH/HNP-PtCu composite owing to its large specific surface and good electron-transfer ability. Under the optimized conditions, the proposed aptasensor exhibited a high sensitivity and a wider linearity to kanamycin in the range 5 × 10(-7)-5 × 10(-2) μgmL(-1) with a low detection limit of 0.42 pgmL(-1). This aptasensor also displayed a satisfying electrochemical performance with good stability, selectivity and reproducibility. The as-prepared aptasensor was successfully used for the determination of kanamycin in animal derived food.

  1. A method of image compression based on lifting wavelet transform and modified SPIHT

    NASA Astrophysics Data System (ADS)

    Lv, Shiliang; Wang, Xiaoqian; Liu, Jinguo

    2016-11-01

    In order to improve the efficiency of remote sensing image data storage and transmission we present a method of the image compression based on lifting scheme and modified SPIHT(set partitioning in hierarchical trees) by the design of FPGA program, which realized to improve SPIHT and enhance the wavelet transform image compression. The lifting Discrete Wavelet Transform (DWT) architecture has been selected for exploiting the correlation among the image pixels. In addition, we provide a study on what storage elements are required for the wavelet coefficients. We present lena's image using the 3/5 lifting scheme.

  2. Method of recovering oil-based fluid

    SciTech Connect

    Brinkley, H.E.

    1993-07-13

    A method is described of recovering oil-based fluid, said method comprising the steps of: applying an oil-based fluid absorbent cloth of man-made fiber to an oil-based fluid, the cloth having at least a portion thereof that is napped so as to raise ends and loops of the man-made fibers and define voids; and absorbing the oil-based fluid into the napped portion of the cloth.

  3. Hierarchical object-based classification of ultra-high-resolution digital mapping camera (DMC) imagery for rangeland mapping and assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ultra high resolution digital aerial photography has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands...

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

    ERIC Educational Resources Information Center

    Gendreau, Audrey

    2014-01-01

    Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research,…

  5. Student Conceptions about the DNA Structure within a Hierarchical Organizational Level: Improvement by Experiment- and Computer-Based Outreach Learning

    ERIC Educational Resources Information Center

    Langheinrich, Jessica; Bogner, Franz X.

    2015-01-01

    As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module.…

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

    PubMed

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

    2014-08-01

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

  7. Hierarchical Pattern Classifier

    NASA Technical Reports Server (NTRS)

    Yates, Gigi L.; Eberlein, Susan J.

    1992-01-01

    Hierarchical pattern classifier reduces number of comparisons between input and memory vectors without reducing detail of final classification by dividing classification process into coarse-to-fine hierarchy that comprises first "grouping" step and second classification step. Three-layer neural network reduces computation further by reducing number of vector dimensions in processing. Concept applicable to pattern-classification problems with need to reduce amount of computation necessary to classify, identify, or match patterns to desired degree of resolution.

  8. A Microfluidic DNA Sensor Based on Three-Dimensional (3D) Hierarchical MoS2/Carbon Nanotube Nanocomposites

    PubMed Central

    Yang, Dahou; Tayebi, Mahnoush; Huang, Yinxi; Yang, Hui Ying; Ai, Ye

    2016-01-01

    In this work, we present a novel microfluidic biosensor for sensitive fluorescence detection of DNA based on 3D architectural MoS2/multi-walled carbon nanotube (MWCNT) nanocomposites. The proposed platform exhibits a high sensitivity, selectivity, and stability with a visible manner and operation simplicity. The excellent fluorescence quenching stability of a MoS2/MWCNT aqueous solution coupled with microfluidics will greatly simplify experimental steps and reduce time for large-scale DNA detection. PMID:27854247

  9. Nanorainforest solar cells based on multi-junction hierarchical p-Si/n-CdS/n-ZnO nanoheterostructures.

    PubMed

    Wang, Wei; Zhao, Qing; Laurent, Kevin; Leprince-Wang, Y; Liao, Zhi-Min; Yu, Dapeng

    2012-01-07

    Solar cells based on one-dimensional nanostructures have recently emerged as one of the most promising candidates to achieve high-efficiency solar energy conversion due to their reduced optical reflection, enhanced light absorption, and enhanced carrier collection. In nature, the rainforest, consisting of several stereo layers of vegetation, is the highest solar-energy-using ecosystem. Herein, we gave an imitation of the rainforest configuration in nanostructure-based solar cell design. Novel multi-layer nanorainforest solar cells based on p-Si nanopillar array/n-CdS nanoparticles/n-ZnO nanowire array heterostructures were achieved via a highly accessible, reproducible and controllable fabrication process. By choosing materials with appropriate bandgaps, an efficient light absorption and enhanced light harvesting were achieved due to the wide range of the solar spectrum covered. Si nanopillar arrays were introduced as direct conduction pathways for photon-generated charges' efficient collection and transport. The unique strategy using PMMA as a void-filling material to obtain a continuous, uniform and low resistance front electrode has significantly improved the overall light conversion efficiency by two orders of magnitude. These results demonstrate that nanorainforest solar cells, along with wafer-scale, low-cost and easily controlled processing, open up substantial opportunities for nanostructure photovoltaic devices.

  10. Hierarchical modeling for image classification

    NASA Technical Reports Server (NTRS)

    Likens, W.; Maw, K.

    1982-01-01

    As part of the California Integrated Remote Sensing System's (CIRSS) San Bernardino County Project, the use of data layers from a geographic information system (GIS) as an integral part of the Landsat image classification process was investigated. Through a hierarchical modeling technique, elevation, aspect, land use, vegetation, and growth management data from the project's data base were used to guide class labeling decisions in a 1976 Landsat MSS land cover classification. A similar model, incorporating 1976-1979 Landsat spectral change data in addition to other data base elements, was used in the classification of a 1979 Landsat image. The resultant Landsat products were integrated as additional layers into the data base for use in growth management, fire hazard, and hydrological modeling.

  11. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  12. Static and dynamic friction of hierarchical surfaces

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  13. Static and dynamic friction of hierarchical surfaces.

    PubMed

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

    2016-12-01

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

  14. Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D

    PubMed Central

    Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

    2014-01-01

    A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent. PMID:25834481

  15. Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

    PubMed Central

    Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

  16. Hierarchical models and the analysis of bird survey information

    USGS Publications Warehouse

    Sauer, J.R.; Link, W.A.

    2003-01-01

    Management of birds often requires analysis of collections of estimates. We describe a hierarchical modeling approach to the analysis of these data, in which parameters associated with the individual species estimates are treated as random variables, and probability statements are made about the species parameters conditioned on the data. A Markov-Chain Monte Carlo (MCMC) procedure is used to fit the hierarchical model. This approach is computer intensive, and is based upon simulation. MCMC allows for estimation both of parameters and of derived statistics. To illustrate the application of this method, we use the case in which we are interested in attributes of a collection of estimates of population change. Using data for 28 species of grassland-breeding birds from the North American Breeding Bird Survey, we estimate the number of species with increasing populations, provide precision-adjusted rankings of species trends, and describe a measure of population stability as the probability that the trend for a species is within a certain interval. Hierarchical models can be applied to a variety of bird survey applications, and we are investigating their use in estimation of population change from survey data.

  17. CLAG: an unsupervised non hierarchical clustering algorithm handling biological data

    PubMed Central

    2012-01-01

    Background Searching for similarities in a set of biological data is intrinsically difficult due to possible data points that should not be clustered, or that should group within several clusters. Under these hypotheses, hierarchical agglomerative clustering is not appropriate. Moreover, if the dataset is not known enough, like often is the case, supervised classification is not appropriate either. Results CLAG (for CLusters AGgregation) is an unsupervised non hierarchical clustering algorithm designed to cluster a large variety of biological data and to provide a clustered matrix and numerical values indicating cluster strength. CLAG clusterizes correlation matrices for residues in protein families, gene-expression and miRNA data related to various cancer types, sets of species described by multidimensional vectors of characters, binary matrices. It does not ask to all data points to cluster and it converges yielding the same result at each run. Its simplicity and speed allows it to run on reasonably large datasets. Conclusions CLAG can be used to investigate the cluster structure present in biological datasets and to identify its underlying graph. It showed to be more informative and accurate than several known clustering methods, as hierarchical agglomerative clustering, k-means, fuzzy c-means, model-based clustering, affinity propagation clustering, and not to suffer of the convergence problem proper to this latter. PMID:23216858

  18. Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: Assessment in two blind tests

    PubMed Central

    Ołdziej, S.; Czaplewski, C.; Liwo, A.; Chinchio, M.; Nanias, M.; Vila, J. A.; Khalili, M.; Arnautova, Y. A.; Jagielska, A.; Makowski, M.; Schafroth, H. D.; Kaźmierkiewicz, R.; Ripoll, D. R.; Pillardy, J.; Saunders, J. A.; Kang, Y. K.; Gibson, K. D.; Scheraga, H. A.

    2005-01-01

    Recent improvements in the protein-structure prediction method developed in our laboratory, based on the thermodynamic hypothesis, are described. The conformational space is searched extensively at the united-residue level by using our physics-based UNRES energy function and the conformational space annealing method of global optimization. The lowest-energy coarse-grained structures are then converted to an all-atom representation and energy-minimized with the ECEPP/3 force field. The procedure was assessed in two recent blind tests of protein-structure prediction. During the first blind test, we predicted large fragments of α and α+β proteins [60–70 residues with Cα rms deviation (rmsd) <6 Å]. However, for α+β proteins, significant topological errors occurred despite low rmsd values. In the second exercise, we predicted whole structures of five proteins (two α and three α+β, with sizes of 53–235 residues) with remarkably good accuracy. In particular, for the genomic target TM0487 (a 102-residue α+β protein from Thermotoga maritima), we predicted the complete, topologically correct structure with 7.3-Å Cα rmsd. So far this protein is the largest α+β protein predicted based solely on the amino acid sequence and a physics-based potential-energy function and search procedure. For target T0198, a phosphate transport system regulator PhoU from T. maritima (a 235-residue mainly α-helical protein), we predicted the topology of the whole six-helix bundle correctly within 8 Å rmsd, except the 32 C-terminal residues, most of which form a β-hairpin. These and other examples described in this work demonstrate significant progress in physics-based protein-structure prediction. PMID:15894609

  19. Types of Online Hierarchical Repository Structures

    ERIC Educational Resources Information Center

    Hershkovitz, Arnon; Azran, Ronit; Hardof-Jaffe, Sharon; Nachmias, Rafi

    2011-01-01

    This study presents an empirical investigation of online hierarchical repositories of items presented to university students in Web-supported course websites, using Web mining methods. To this end, data from 1747 courses were collected, and the use of online repositories of content items in these courses was examined. At a later stage, courses…

  20. A Hierarchical Grouping of Great Educators

    ERIC Educational Resources Information Center

    Barker, Donald G.

    1977-01-01

    Great educators of history were categorized on the basis of their: aims of education, fundamental ideas, and educational theories. They were classed by Ward's method of hierarchical analysis into six groupings: Socrates, Ausonius, Jerome, Abelard; Quintilian, Origen, Melanchthon, Ascham, Loyola; Alciun, Comenius; Vittorino, Basedow, Pestalozzi,…

  1. Metal oxide nanostructures with hierarchical morphology

    SciTech Connect

    Ren, Zhifeng; Lao, Jing Yu; Banerjee, Debasish

    2007-11-13

    The present invention relates generally to metal oxide materials with varied symmetrical nanostructure morphologies. In particular, the present invention provides metal oxide materials comprising one or more metallic oxides with three-dimensionally ordered nanostructural morphologies, including hierarchical morphologies. The present invention also provides methods for producing such metal oxide materials.

  2. The Hierarchical Structure of Formal Operational Tasks.

    ERIC Educational Resources Information Center

    Bart, William M.; Mertens, Donna M.

    1979-01-01

    The hierarchical structure of the formal operational period of Piaget's theory of cognitive development was explored through the application of ordering theoretical methods to a set of data that systematically utilized the various formal operational schemes. Results suggested a common structure underlying task performance. (Author/BH)

  3. A hierarchical Bayesian framework for force field selection in molecular dynamics simulations.

    PubMed

    Wu, S; Angelikopoulos, P; Papadimitriou, C; Moser, R; Koumoutsakos, P

    2016-02-13

    We present a hierarchical Bayesian framework for the selection of force fields in molecular dynamics (MD) simulations. The framework associates the variability of the optimal parameters of the MD potentials under different environmental conditions with the corresponding variability in experimental data. The high computational cost associated with the hierarchical Bayesian framework is reduced by orders of magnitude through a parallelized Transitional Markov Chain Monte Carlo method combined with the Laplace Asymptotic Approximation. The suitability of the hierarchical approach is demonstrated by performing MD simulations with prescribed parameters to obtain data for transport coefficients under different conditions, which are then used to infer and evaluate the parameters of the MD model. We demonstrate the selection of MD models based on experimental data and verify that the hierarchical model can accurately quantify the uncertainty across experiments; improve the posterior probability density function estimation of the parameters, thus, improve predictions on future experiments; identify the most plausible force field to describe the underlying structure of a given dataset. The framework and associated software are applicable to a wide range of nanoscale simulations associated with experimental data with a hierarchical structure.

  4. Unveiling Surface Redox Charge Storage of Interacting Two-Dimensional Hetero-Nanosheets in Hierarchical Architectures

    SciTech Connect

    Mahmood, Qasim; Bak, Seong-Min; Kim, Min G.; Yun, Sol; Yang, Xiao-Qing; Shin, Hyeon S.; Kim, Woo S.; Braun, Paul V.; Park, Ho S.

    2015-03-03

    Two-dimensional (2D) heteronanosheets are currently the focus of intense study due to the unique properties that emerge from the interplay between two low-dimensional nanomaterials with different properties. However, the properties and new phenomena based on the two 2D heteronanosheets interacting in a 3D hierarchical architecture have yet to be explored. Here, we unveil the surface redox charge storage mechanism of surface-exposed WS2 nanosheets assembled in a 3D hierarchical heterostructure using in situ synchrotron X-ray absorption and Raman spectroscopic methods. The surface dominating redox charge storage of WS2 is manifested in a highly reversible and ultrafast capacitive fashion due to the interaction of heteronanosheets and the 3D connectivity of the hierarchical structure. In contrast, compositionally identical 2D WS2 structures fail to provide a fast and high capacitance with different modes of lattice vibration. The distinctive surface capacitive behavior of 3D hierarchically structured heteronanosheets is associated with rapid proton accommodation into the in-plane W–S lattice (with the softening of the E2g bands), the reversible redox transition of the surface-exposed intralayers residing in the electrochemically active 1T phase of WS2 (with the reversible change in the interatomic distance and peak intensity of W–W bonds), and the change in the oxidation state during the proton insertion/deinsertion process. This proposed mechanism agrees with the dramatic improvement in the capacitive performance of the two heteronanosheets coupled in the hierarchical structure.

  5. A Hierarchical Preference Voting System for Mining Method Selection Problem / Wykorzystanie Systemu Głosowania Zakładający Hierarchię Preferencji Przy Wyborze Odpowiedniej Metody Wybierania

    NASA Astrophysics Data System (ADS)

    Nourali, Hamidreza; Nourali, Saeid; Ataei, Mohammad; Imanipour, Narges

    2012-12-01

    To apply decision making theory for Mining Method Selection (MMS) problem, researchers have faced two difficulties in recent years: (i) calculation of relative weight for each criterion, (ii) uncertainty in judgment for decision makers. In order to avoid these difficulties, we apply a Hierarchical Preference Voting System (HPVS) for MMS problem that uses a Data Envelopment Analysis (DEA) model to produce weights associated with each ranking place. The presented method solves the problem in two stages. In the first stage, weights of criteria are calculated and at the second stage, alternatives are ranked with respect to all criteria. A simple case study has also been presented to illustrate the competence of this method. The results show that this approach reduces some difficulties of previous methods and could be applied simply in group decision making with too many decision makers and criteria. Also, regarding to application of a mathematical model, subjectivity is reduced and outcomes are more reliable.

  6. Dpath software reveals hierarchical haemato-endothelial lineages of Etv2 progenitors based on single-cell transcriptome analysis

    PubMed Central

    Gong, Wuming; Rasmussen, Tara L.; Singh, Bhairab N.; Koyano-Nakagawa, Naoko; Pan, Wei; Garry, Daniel J.

    2017-01-01

    Developmental, stem cell and cancer biologists are interested in the molecular definition of cellular differentiation. Although single-cell RNA sequencing represents a transformational advance for global gene analyses, novel obstacles have emerged, including the computational management of dropout events, the reconstruction of biological pathways and the isolation of target cell populations. We develop an algorithm named dpath that applies the concept of metagene entropy and allows the ranking of cells based on their differentiation potential. We also develop self-organizing map (SOM) and random walk with restart (RWR) algorithms to separate the progenitors from the differentiated cells and reconstruct the lineage hierarchies in an unbiased manner. We test these algorithms using single cells from Etv2-EYFP transgenic mouse embryos and reveal specific molecular pathways that direct differentiation programmes involving the haemato-endothelial lineages. This software program quantitatively assesses the progenitor and committed states in single-cell RNA-seq data sets in a non-biased manner. PMID:28181481

  7. Galaxy formation through hierarchical clustering

    NASA Technical Reports Server (NTRS)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  8. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    PubMed

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  9. Hierarchically structured, hyaluronic acid-based hydrogel matrices via the covalent integration of microgels into macroscopic networks$

    PubMed Central

    Jha, Amit K.; Malik, Manisha S.; Farach-Carson, Mary C.; Duncan, Randall L.; Jia, Xinqiao

    2010-01-01

    We aimed to develop biomimetic hydrogel matrices that not only exhibit structural hierarchy and mechanical integrity, but also present biological cues in a controlled fashion. To this end, photocrosslinkable, hyaluronic acid (HA)-based hydrogel particles (HGPs) were synthesized via an inverse emulsion crosslinking process followed by chemical modification with glycidyl methacrylate (GMA). HA modified with GMA (HA-GMA) was employed as the soluble macromer. Macroscopic hydrogels containing covalently integrated hydrogel particles (HA-c-HGP) were prepared by radical polymerization of HA-GMA in the presence of crosslinkable HGPs. The covalent linkages between the hydrogel particles and the secondary HA matrix resulted in the formation of a diffuse, fibrilar interface around the particles. Compared to the traditional bulk gels synthesized by photocrosslinking of HA-GMA, these hydrogels exhibited a reduced sol fraction and a lower equilibrium swelling ratio. When tested under uniaxial compression, the HA-c-HGP gels were more pliable than the HA-p-HGP gels and fractured at higher strain than the HA-GMA gels. Primary bovine chondrocytes were photoencapsulated in the HA matrices with minimal cell damage. The 3D microenvironment created by HA-GMA and HA HGPs not only maintained the chondrocyte phenotype but also fostered the production of cartilage specific extracellular matrix. To further improve the biological activities of the HA-c-HGP gels, bone morphogenetic protein 2 (BMP-2) was loaded into the immobilized HGPs. BMP-2 was released from the HA-c-HGP gels in a controlled manner with reduced initial burst over prolonged periods of time. The HA-c-HGP gels are promising candidates for use as bioactive matrices for cartilage tissue engineering. PMID:20936090

  10. Method for indexing and retrieving manufacturing-specific digital imagery based on image content

    DOEpatents

    Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

    2004-06-15

    A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

  11. Solvothermal Synthesis of Three-Dimensional Hierarchical CuS Microspheres from a Cu-Based Ionic Liquid Precursor for High-Performance Asymmetric Supercapacitors.

    PubMed

    Zhang, Jing; Feng, Huijie; Yang, Jiaqin; Qin, Qing; Fan, Hongmin; Wei, Caiying; Zheng, Wenjun

    2015-10-07

    It is meaningful to exploit copper sulfide materials with desired structure as well as potential application due to their cheapness and low toxicity. A low-temperature and facile solvothermal method for preparing three-dimensional (3D) hierarchical covellite (CuS) microspheres from an ionic liquid precursor [Bmim]2Cu2Cl6 (Bmim = 1-butyl-3-methylimidazolium) is reported. The formation of CuS nanostructures was achieved by decomposition of intermediate complex Cu(Tu)3Cl (thiourea = Tu), which produced CuS microspheres with diameters of 2.5-4 μm assembled by nanosheets with thicknesses of 10-15 nm. The ionic liquid, as an "all-in-one" medium, played a key role for the fabrication and self-assembly of CuS nanosheets. The alkylimidazolium rings ([Bmim](+)) were found to adsorb onto the (001) facets of CuS crystals, which inhibited the crystal growth along the [001] direction, while the alkyl chain had influence on the assembly of CuS nanosheets. The CuS microspheres showed enhanced electrochemical performance and high stability for the application in supercapacitors due to intriguing structural design and large specific surface area. When this well-defined CuS electrode was assembled into an asymmetric supercapacitor (ASC) with an activated carbon (AC) electrode, the CuS//AC-ASC demonstrated good cycle performance (∼88% capacitance after 4000 cycles) and high energy density (15.06 W h kg(-1) at a power density of 392.9 W kg(-1)). This work provides new insights into the use of copper sulfide electrode materials for asymmetric supercapacitors and other electrochemical devices.

  12. Hierarchical structures based on self-assembling beta-hairpin peptides and their application as biomaterials and hybrid materials

    NASA Astrophysics Data System (ADS)

    Altunbas, Aysegul

    an effective vehicle for the localized delivery of curcumin over sustained periods of time in vitro. The curcumin-hydrogel is prepared in-situ where curcumin encapsulation within the hydrogel network is accomplished concurrently with peptide self-assembly. Physical characterization methods and in vitro biological studies were used to demonstrate the effectiveness of curcumin-loaded beta-hairpin hydrogels as injectable agents for localized curcumin delivery. Notably, rheological characterization of the curcumin loaded hydrogel before and after shear flow have indicated solid-like properties even at high curcumin payloads. In vitro experiments with a medulloblastoma cell line confirm that the encapsulation of the curcumin within the hydrogel does not have an adverse effect on its bioactivity. Most importantly, the rate of curcumin release and its consequent therapeutic efficacy can be conveniently modulated by changing the morphological characteristics of the peptide hydrogel network. Lastly, MAX8 hydrogel cytocompatibility and biocompatibility was assessed with the future aim of utilizing this hydrogel as a scaffold in liver regeneration studies in rats. MAX8 hydrogel cytotoxity was evaluated using MC3T3-E1 and MG63 cell lines. Encapsulation, syringe delivery and subsequent viability of MG63 cells in hydrogels was also assessed to study the feasibility of using hydrogel/cell constructs as minimally invasive cell delivery vehicles. Biocompatibility was evaluated by monitoring inflammatory response induced by the MAX8 hydrogel via a subcutaneous mice model. Biocompatibility of MAX8 hydrogels at sites other than the subcutaneous region was also investigated using a cylindrical punch resection model in rat liver. The preliminary biocompatibility studies provide an elemental understanding of MAX8 hydrogel behavior in vivo.

  13. Hierarchical Metal–Organic Framework Hybrids: Perturbation-Assisted Nanofusion Synthesis

    DOE PAGES

    Yue, Yanfeng; Fulvio, Pasquale F.; Dai, Sheng

    2015-12-04

    Metal–organic frameworks (MOFs) represent a new family of microporous materials; however, microporous–mesoporous hierarchical MOF materials have been less investigated because of the lack of simple, reliable methods to introduce mesopores to the crystalline microporous particles. State-of-the-art MOF hierarchical materials have been prepared by ligand extension methods or by using a template, resulting in intrinsic mesopores of longer ligands or replicated pores from template agents, respectively. However, mesoporous MOF materials obtained through ligand extension often collapse in the absence of guest molecules, which dramatically reduces the size of the pore aperture. Although the template-directed strategy allows for the preparation of hierarchicalmore » materials with larger mesopores, the latter requires a template removal step, which may result in the collapse of the implemented mesopores. Recently, a general template-free synthesis of hierarchical microporous crystalline frameworks, such as MOFs and Prussian blue analogues (PBAs), has been reported. Our new method is based on the kinetically controlled precipitation (perturbation), with simultaneous condensation and redissolution of polymorphic nanocrystallites in the mother liquor. This method further eliminates the use of extended organic ligands and the micropores do not collapse upon removal of trapped guest solvent molecules, thus yielding hierarchical MOF materials with intriguing porosity in the gram scale. The hierarchical MOF materials prepared in this way exhibited exceptional properties when tested for the adsorption of large organic dyes over their corresponding microporous frameworks, due to the enhanced pore accessibility and electrolyte diffusion within the mesopores. As for PBAs, the pore size distribution of these materials can be tailored by changing the metals substituting Fe cations in the PB lattice. For these, the textural mesopores increased from approximately 10 nm for Cu

  14. Automatic Construction of Hierarchical Road Networks

    NASA Astrophysics Data System (ADS)

    Yang, Weiping

    2016-06-01

    This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.

  15. The Metabolic Status Drives Acclimation of Iron Deficiency Responses in Chlamydomonas reinhardtii as Revealed by Proteomics Based Hierarchical Clustering and Reverse Genetics*

    PubMed Central

    Höhner, Ricarda; Barth, Johannes; Magneschi, Leonardo; Jaeger, Daniel; Niehues, Anna; Bald, Till; Grossman, Arthur; Fufezan, Christian; Hippler, Michael

    2013-01-01

    Iron is a crucial cofactor in numerous redox-active proteins operating in bioenergetic pathways including respiration and photosynthesis. Cellular iron management is essential to sustain sufficient energy production and minimize oxidative stress. To produce energy for cell growth, the green alga Chlamydomonas reinhardtii possesses the metabolic flexibility to use light and/or carbon sources such as acetate. To investigate the interplay between the iron-deficiency response and growth requirements under distinct trophic conditions, we took a quantitative proteomics approach coupled to innovative hierarchical clustering using different “distance-linkage combinations” and random noise injection. Protein co-expression analyses of the combined data sets revealed insights into cellular responses governing acclimation to iron deprivation and regulation associated with photosynthesis dependent growth. Photoautotrophic growth requirements as well as the iron deficiency induced specific metabolic enzymes and stress related proteins, and yet differences in the set of induced enzymes, proteases, and redox-related polypeptides were evident, implying the establishment of distinct response networks under the different conditions. Moreover, our data clearly support the notion that the iron deficiency response includes a hierarchy for iron allocation within organelles in C. reinhardtii. Importantly, deletion of a bifunctional alcohol and acetaldehyde dehydrogenase (ADH1), which is induced under low iron based on the proteomic data, attenuates the remodeling of the photosynthetic machinery in response to iron deficiency, and at the same time stimulates expression of stress-related proteins such as NDA2, LHCSR3, and PGRL1. This finding provides evidence that the coordinated regulation of bioenergetics pathways and iron deficiency response is sensitive to the cellular and chloroplast metabolic and/or redox status, consistent with systems approach data. PMID:23820728

  16. Hierarchical self-assembled structures based on nitrogen-doped carbon nanotubes as advanced negative electrodes for Li-ion batteries and 3D microbatteries

    NASA Astrophysics Data System (ADS)

    Sharifi, Tiva; Valvo, Mario; Gracia-Espino, Eduardo; Sandström, Robin; Edström, Kristina; Wågberg, Thomas

    2015-04-01

    Hierarchical structures based on carbon paper and multi-walled nitrogen-doped carbon nanotubes were fabricated and subsequently decorated with hematite nanorods to obtain advanced 3D architectures for Li-ion battery negative electrodes. The carbon paper provides a versatile metal-free 3D current collector ensuring a good electrical contact of the active materials to its carbon fiber network. Firstly, the nitrogen-doped carbon nanotubes onto the carbon paper were studied and a high footprint area capacity of 2.1 mAh cm-2 at 0.1 mA cm-2 was obtained. The Li can be stored in the inter-wall regions of the nanotubes, mediated by the defects formed on their walls by the nitrogen atoms. Secondly, the incorporation of hematite nanorods raised the footprint area capacity to 2.25 mAh cm-2 at 0.1 mA cm-2. However, the repeated conversion/de-conversion of Fe2O3 limited both coulombic and energy efficiencies for these electrodes, which did not perform as well as those including only the N-doped carbon nanotubes at higher current densities. Thirdly, long-cycling tests showed the robust Li insertion mechanism in these N-doped carbonaceous structures, which yielded an unmatched footprint area capacity enhancement up to 1.95 mAh cm-2 after 60 cycles at 0.3 mA cm-2 and an overall capacity of 204 mAh g-1 referred to the mass of the entire electrode.

  17. Comparison of a silver nanoparticle-based method and the modified spectrophotometric methods for assessing antioxidant capacity of rapeseed varieties.

    PubMed

    Szydłowska-Czerniak, Aleksandra; Tułodziecka, Agnieszka

    2013-12-01

    The antioxidant capacity of 15 rapeseed varieties was determined by the proposed silver nanoparticle-based (AgNP) method and three modified assays: ferric reducing antioxidant power (FRAP), 2,2'-diphenyl-1-picrylhydrazyl (DPPH) and Folin-Ciocalteu reducing capacity (FC). The average antioxidant capacities of the studied rapeseed cultivars ranged between 5261-9462, 3708-7112, 18864-31245 and 5816-9937 μmol sinapic acid (SA)/100g for AgNP, FRAP, DPPH and FC methods, respectively. There are significant, positive correlations between antioxidant capacities of the studied rapeseed cultivars determined by four analytical methods (r=0.5971-0.9149, p<0.05). The comparable precision for the proposed AgNP method (RSD=1.4-4.4%) and the modified FRAP, DPPH and FC methods (RSD=1.0-4.4%, 0.7-2.1% and 0.8-3.6%, respectively), demonstrate the benefit of the AgNP method in the routine analysis of antioxidant capacity of rapeseed cultivars. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for discrimination the quality of the studied rapeseed varieties based on their antioxidant potential determined by different analytical methods. Three main groups were identified by HCA, while the classification and characterisation of rapeseed varieties within each of these groups were obtained from PCA. The chemometric analyses demonstrated that, rapeseed variety S13 had the highest antioxidant capacity, thus this cultivar should be considered as the richest source of natural antioxidants.

  18. Distribution system reliability assessment using hierarchical Markov modeling

    SciTech Connect

    Brown, R.E.; Gupta, S.; Christie, R.D.; Venkata, S.S.; Fletcher, R.

    1996-10-01

    Distribution system reliability assessment is concerned with power availability and power quality at each customer`s service entrance. This paper presents a new method, termed Hierarchical Markov Modeling (HMM), which can perform predictive distribution system reliability assessment. HMM is unique in that it decomposes the reliability model based on system topology, integrated protection systems, and individual protection devices. This structure, which easily accommodates the effects of backup protection, fault isolation, and load restoration, is compared to simpler reliability models. HMM is then used to assess the reliability of an existing utility distribution system and to explore the reliability impact of several design improvement options.

  19. Hierarchical Safety Cases

    NASA Technical Reports Server (NTRS)

    Denney, Ewen W.; Whiteside, Iain J.

    2012-01-01

    We introduce hierarchical safety cases (or hicases) as a technique to overcome some of the difficulties that arise creating and maintaining industrial-size safety cases. Our approach extends the existing Goal Structuring Notation with abstraction structures, which allow the safety case to be viewed at different levels of detail. We motivate hicases and give a mathematical account of them as well as an intuition, relating them to other related concepts. We give a second definition which corresponds closely to our implementation of hicases in the AdvoCATE Assurance Case Editor and prove the correspondence between the two. Finally, we suggest areas of future enhancement, both theoretically and practically.

  20. Hierarchical modeling of protein interactions.

    PubMed

    Kurcinski, Mateusz; Kolinski, Andrzej

    2007-07-01

    A novel approach to hierarchical peptide-protein and protein-protein docking is described and evaluated. Modeling procedure starts from a reduced space representation of proteins and peptides. Polypeptide chains are represented by strings of alpha-carbon beads restricted to a fine-mesh cubic lattice. Side chains are represented by up to two centers of interactions, corresponding to beta-carbons and the centers of mass of the remaining portions of the side groups, respectively. Additional pseudoatoms are located in the centers of the virtual bonds connecting consecutive alpha carbons. These pseudoatoms support a model of main-chain hydrogen bonds. Docking starts from a collection of random configurations of modeled molecules. Interacting molecules are flexible; however, higher accuracy models are obtained when the conformational freedom of one (the larger one) of the assembling molecules is limited by a set of weak distance restraints extracted from the experimental (or theoretically predicted) structures. Sampling is done by means of Replica Exchange Monte Carlo method. Afterwards, the set of obtained structures is subject to a hierarchical clustering. Then, the centroids of the resulting clusters are used as scaffolds for the reconstruction of the atomic details. Finally, the all-atom models are energy minimized and scored using classical tools of molecular mechanics. The method is tested on a set of macromolecular assemblies consisting of proteins and peptides. It is demonstrated that the proposed approach to the flexible docking could be successfully applied to prediction of protein-peptide and protein-protein interactions. The obtained models are almost always qualitatively correct, although usually of relatively low (or moderate) resolution. In spite of this limitation, the proposed method opens new possibilities of computational studies of macromolecular recognition and mechanisms of assembly of macromolecular complexes.

  1. METHOD OF JOINING CARBIDES TO BASE METALS

    DOEpatents

    Krikorian, N.H.; Farr, J.D.; Witteman, W.G.

    1962-02-13

    A method is described for joining a refractory metal carbide such as UC or ZrC to a refractory metal base such as Ta or Nb. The method comprises carburizing the surface of the metal base and then sintering the base and carbide at temperatures of about 2000 deg C in a non-oxidizing atmosphere, the base and carbide being held in contact during the sintering step. To reduce the sintering temperature and time, a sintering aid such as iron, nickel, or cobait is added to the carbide, not to exceed 5 wt%. (AEC)

  2. A hierarchical algorithm for molecular similarity (H-FORMS).

    PubMed

    Ramirez-Manzanares, Alonso; Peña, Joaquin; Azpiroz, Jon M; Merino, Gabriel

    2015-07-15

    A new hierarchical method to determine molecular similarity is introduced. The goal of this method is to detect if a pair of molecules has the same structure by estimating a rigid transformation that aligns the molecules and a correspondence function that matches their atoms. The algorithm firstly detect similarity based on the global spatial structure. If this analysis is not sufficient, the algorithm computes novel local structural rotation-invariant descriptors for the atom neighborhood and uses this information to match atoms. Two strategies (deterministic and stochastic) on the matching based alignment computation are tested. As a result, the atom-matching based on local similarity indexes decreases the number of testing trials and significantly reduces the dimensionality of the Hungarian assignation problem. The experiments on well-known datasets show that our proposal outperforms state-of-the-art methods in terms of the required computational time and accuracy.

  3. Method for comparing content based image retrieval methods

    NASA Astrophysics Data System (ADS)

    Barnard, Kobus; Shirahatti, Nikhil V.

    2003-01-01

    We assume that the goal of content based image retrieval is to find images which are both semantically and visually relevant to users based on image descriptors. These descriptors are often provided by an example image--the query by example paradigm. In this work we develop a very simple method for evaluating such systems based on large collections of images with associated text. Examples of such collections include the Corel image collection, annotated museum collections, news photos with captions, and web images with associated text based on heuristic reasoning on the structure of typical web pages (such as used by Google(tm)). The advantage of using such data is that it is plentiful, and the method we propose can be automatically applied to hundreds of thousands of queries. However, it is critical that such a method be verified against human usage, and to do this we evaluate over 6000 query/result pairs. Our results strongly suggest that at least in the case of the Corel image collection, the automated measure is a good proxy for human evaluation. Importantly, our human evaluation data can be reused for the evaluation of any content based image retrieval system and/or the verification of additional proxy measures.

  4. Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

    PubMed

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

    2015-08-05

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

  5. Design for validation, based on formal methods

    NASA Technical Reports Server (NTRS)

    Butler, Ricky W.

    1990-01-01

    Validation of ultra-reliable systems decomposes into two subproblems: (1) quantification of probability of system failure due to physical failure; (2) establishing that Design Errors are not present. Methods of design, testing, and analysis of ultra-reliable software are discussed. It is concluded that a design-for-validation based on formal methods is needed for the digital flight control systems problem, and also that formal methods will play a major role in the development of future high reliability digital systems.

  6. Phase transition study of confined water molecules inside carbon nanotubes: hierarchical multiscale method from molecular dynamics simulation to ab initio calculation.

    PubMed

    Javadian, Soheila; Taghavi, Fariba; Yari, Faramarz; Hashemianzadeh, Seyed Majid

    2012-09-01

    In this study, the mechanism of the temperature-dependent phase transition of confined water inside a (9,9) single-walled carbon nanotube (SWCNT) was studied using the hierarchical multi-scale modeling techniques of molecular dynamics (MD) and density functional theory (DFT). The MD calculations verify the formation of hexagonal ice nanotubes at the phase transition temperature T(c)=275K by a sharp change in the location of the oxygen atoms inside the SWCNT. Natural bond orbital (NBO) analysis provides evidence of considerable intermolecular charge transfer during the phase transition and verifies that the ice nanotube contains two different forms of hydrogen bonding due to confinement. Nuclear quadrupole resonance (NQR) and nuclear magnetic resonance (NMR) analyses were used to demonstrate the fundamental influence of intermolecular hydrogen bonding interactions on the formation and electronic structure of ice nanotubes. In addition, the NQR analysis revealed that the rearrangement of nano-confined water molecules during the phase transition could be detected directly by the orientation of ¹⁷O atom EFG tensor components related to the molecular frame axes. The effects of nanoscale confinements in ice nanotubes and water clusters were analyzed by experimentally observable NMR and NQR parameters. These findings showed a close relationship between the phase behavior and orientation of the electronic structure in nanoscale structures and demonstrate the usefulness of NBO and NQR parameters for detecting phase transition phenomena in nanoscale confining environments.

  7. Integrating data sources to improve hydraulic head predictions : a hierarchical machine learning approach.

    SciTech Connect

    Michael, W. J.; Minsker, B. S.; Tcheng, D.; Valocchi, A. J.; Quinn, J. J.; Environmental Assessment; Univ. of Illinois

    2005-03-26

    This study investigates how machine learning methods can be used to improve hydraulic head predictions by integrating different types of data, including data from numerical models, in a hierarchical approach. A suite of four machine learning methods (decision trees, instance-based weighting, inverse distance weighting, and neural networks) are tested in several hierarchical configurations with different types of data from the 317/319 area at Argonne National Laboratory-East. The best machine learning model had a mean predicted head error 50% smaller than an existing MODFLOW numerical flow model, and a standard deviation of predicted head error 67% lower than the MODFLOW model, computed across all sampled locations used for calibrating the MODFLOW model. These predictions were obtained using decision trees trained with all historical quarterly data; the hourly head measurements were not as useful for prediction, most likely because of their poor spatial coverage. The results show promise for using hierarchical machine learning approaches to improve predictions and to identify the most essential types of data to guide future sampling efforts. Decision trees were also combined with an existing MODFLOW model to test their capabilities for updating numerical models to improve predictions as new data are collected. The combined model had a mean error 50% lower than the MODFLOW model alone. These results demonstrate that hierarchical machine learning approaches can be used to improve predictive performance of existing numerical models in areas with good data coverage. Further research is needed to compare this approach with methods such as Kalman filtering.

  8. Model-Based Method for Sensor Validation

    NASA Technical Reports Server (NTRS)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  9. Bone hierarchical structure in three dimensions.

    PubMed

    Reznikov, Natalie; Shahar, Ron; Weiner, Steve

    2014-09-01

    Bone is a complex hierarchically structured family of materials that includes a network of cells and their interconnected cell processes. New insights into the 3-D structure of various bone materials (mainly rat and human lamellar bone and minipig fibrolamellar bone) were obtained using a focused ion beam electron microscope and the serial surface view method. These studies revealed the presence of two different materials, the major material being the well-known ordered arrays of mineralized collagen fibrils and associated macromolecules, and the minor component being a relatively disordered material composed of individual collagen fibrils with no preferred orientation, with crystals inside and possibly between fibrils, and extensive ground mass. Significantly, the canaliculi and their cell processes are confined within the disordered material. Here we present a new hierarchical scheme for several bone tissue types that incorporates these two materials. The new scheme updates the hierarchical scheme presented by Weiner and Wagner (1998). We discuss the structures at different hierarchical levels with the aim of obtaining further insights into structure-function-related questions, as well as defining some remaining unanswered questions.

  10. BM-BC: a Bayesian method of base calling for Solexa sequence data

    PubMed Central

    2012-01-01

    Base calling is a critical step in the Solexa next-generation sequencing procedure. It compares the position-specific intensity measurements that reflect the signal strength of four possible bases (A, C, G, T) at each genomic position, and outputs estimates of the true sequences for short reads of DNA or RNA. We present a Bayesian method of base calling, BM-BC, for Solexa-GA sequencing data. The Bayesian method builds on a hierarchical model that accounts for three sources of noise in the data, which are known to affect the accuracy of the base calls: fading, phasing, and cross-talk between channels. We show that the new method improves the precision of base calling compared with currently leading methods. Furthermore, the proposed method provides a probability score that measures the confidence of each base call. This probability score can be used to estimate the false discovery rate of the base calling or to rank the precision of the estimated DNA sequences, which in turn can be useful for downstream analysis such as sequence alignment. PMID:23320938

  11. Hierarchical Context Modeling for Video Event Recognition.

    PubMed

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

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

  12. A Method for Capturing and Reconciling Stakeholder Intentions Based on the Formal Concept Analysis

    NASA Astrophysics Data System (ADS)

    Aoyama, Mikio

    Information systems are ubiquitous in our daily life. Thus, information systems need to work appropriately anywhere at any time for everybody. Conventional information systems engineering tends to engineer systems from the viewpoint of systems functionality. However, the diversity of the usage context requires fundamental change compared to our current thinking on information systems; from the functionality the systems provide to the goals the systems should achieve. The intentional approach embraces the goals and related aspects of the information systems. This chapter presents a method for capturing, structuring and reconciling diverse goals of multiple stakeholders. The heart of the method lies in the hierarchical structuring of goals by goal lattice based on the formal concept analysis, a semantic extension of the lattice theory. We illustrate the effectiveness of the presented method through application to the self-checkout systems for large-scale supermarkets.

  13. How hierarchical is language use?

    PubMed

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

    2012-11-22

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

  14. How hierarchical is language use?

    PubMed Central

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

    2012-01-01

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

  15. Hierarchical abstract semantic model for image classification

    NASA Astrophysics Data System (ADS)

    Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

    2015-09-01

    Semantic gap limits the performance of bag-of-visual-words. To deal with this problem, a hierarchical abstract semantics method that builds abstract semantic layers, generates semantic visual vocabularies, measures semantic gap, and constructs classifiers using the Adaboost strategy is proposed. First, abstract semantic layers are proposed to narrow the semantic gap between visual features and their interpretation. Then semantic visual words are extracted as features to train semantic classifiers. One popular form of measurement is used to quantify the semantic gap. The Adaboost training strategy is used to combine weak classifiers into strong ones to further improve performance. For a testing image, the category is estimated layer-by-layer. Corresponding abstract hierarchical structures for popular datasets, including Caltech-101 and MSRC, are proposed for evaluation. The experimental results show that the proposed method is capable of narrowing semantic gaps effectively and performs better than other categorization methods.

  16. Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

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