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Sample records for ball-scale based hierarchical

  1. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

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

    2009-01-01

    This paper proposes a topology-based hierarchical scheduling scheme using Deficit Round Robin (DRR). The main idea of the topology-based hierarchical scheduling is to map the topology of the connected network into the logical structure of the scheduler, and combine several token schedulers accord...... of malicious traffic. This is significant for IPTV services in Carrier Ethernet networks....

  2. Communication Base Station Log Analysis Based on Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Zhang Shao-Hua

    2017-01-01

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

  3. Hierarchical Image Segmentation Based on Iterative Contraction and Merging.

    Science.gov (United States)

    Syu, Jia-Hao; Wang, Sheng-Jyh; Wang, Li-Chun

    2017-05-01

    In this paper, we propose a new framework for hierarchical image segmentation based on iterative contraction and merging. In the proposed framework, we treat the hierarchical image segmentation problem as a sequel of optimization problems, with each optimization process being realized by a contraction-and-merging process to identify and merge the most similar data pairs at the current resolution. At the beginning, we perform pixel-based contraction and merging to quickly combine image pixels into initial region-elements with visually indistinguishable intra-region color difference. After that, we iteratively perform region-based contraction and merging to group adjacent regions into larger ones to progressively form a segmentation dendrogram for hierarchical segmentation. Comparing with the state-of-the-art techniques, the proposed algorithm can not only produce high-quality segmentation results in a more efficient way, but also keep a lot of boundary details in the segmentation results.

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

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

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

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

    Science.gov (United States)

    Lemons, Nathan W; Hu, Bin; Hlavacek, William S

    2011-02-02

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

  6. Agent-based distributed hierarchical control of dc microgrid systems

    DEFF Research Database (Denmark)

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

    2014-01-01

    In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken...

  7. Intensity-based hierarchical elastic registration using approximating splines.

    Science.gov (United States)

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

    2014-01-01

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

  8. P2MP MPLS-Based Hierarchical Service Management System

    Science.gov (United States)

    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.

  9. Biomedical application of hierarchically built structures based on metal oxides

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2017-03-01

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

  11. Using PSO-Based Hierarchical Feature Selection Algorithm

    Directory of Open Access Journals (Sweden)

    Zhiwei Ji

    2014-01-01

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

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

    Science.gov (United States)

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

    2009-10-01

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

  13. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    Science.gov (United States)

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

    2007-10-01

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

  14. Chaotic Signal Denoising Based on Hierarchical Threshold Synchrosqueezed Wavelet Transform

    Science.gov (United States)

    Wang, Wen-Bo; Jing, Yun-yu; Zhao, Yan-chao; Zhang, Lian-Hua; Wang, Xiang-Li

    2017-12-01

    In order to overcoming the shortcoming of single threshold synchrosqueezed wavelet transform(SWT) denoising method, an adaptive hierarchical threshold SWT chaotic signal denoising method is proposed. Firstly, a new SWT threshold function is constructed based on Stein unbiased risk estimation, which is two order continuous derivable. Then, by using of the new threshold function, a threshold process based on the minimum mean square error was implemented, and the optimal estimation value of each layer threshold in SWT chaotic denoising is obtained. The experimental results of the simulating chaotic signal and measured sunspot signals show that, the proposed method can filter the noise of chaotic signal well, and the intrinsic chaotic characteristic of the original signal can be recovered very well. Compared with the EEMD denoising method and the single threshold SWT denoising method, the proposed method can obtain better denoising result for the chaotic signal.

  15. Hierarchical-control-based output synchronization of coexisting attractor networks

    International Nuclear Information System (INIS)

    Yun-Zhong, Song; Yi-Fa, Tang

    2010-01-01

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

  16. Multiscale experimental mechanics of hierarchical carbon-based materials.

    Science.gov (United States)

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

    2012-06-05

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

  17. Global Crop Monitoring: A Satellite-Based Hierarchical Approach

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

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

  18. Hierarchical system for content-based audio classification and retrieval

    Science.gov (United States)

    Zhang, Tong; Kuo, C.-C. Jay

    1998-10-01

    A hierarchical system for audio classification and retrieval based on audio content analysis is presented in this paper. The system consists of three stages. The audio recordings are first classical and segmented into speech, music, several types of environmental sounds, and silence, based on morphological and statistical analysis of temporal curves of the energy function, the average zero-crossing rate, and the fundamental frequency of audio signals. The first stage is called the coarse-level audio classification and segmentation. Then, environmental sounds are classified into finer classes such as applause, rain, birds' sound, etc., which is called the fine-level audio classification. The second stage is based on time-frequency analysis of audio signals and the use of the hidden Markov model (HMM) for classification. In the third stage, the query-by-example audio retrieval is implemented where similar sounds can be found according to the input sample audio. The way of modeling audio features with the hidden Markov model, the procedures of audio classification and retrieval, and the experimental results are described. It is shown that, with the proposed new system, audio recordings can be automatically segmented and classified into basic types in real time with an accuracy higher than 90%. Examples of audio fine classification and audio retrieval with the proposed HMM-based method are also provided.

  19. Hierarchical clustering of RGB surface water images based on MIA ...

    African Journals Online (AJOL)

    Thus characterised images were partitioned into clusters of similar images using hierarchical clustering. The best defined clusters were obtained when the Ward's method was applied. Images were partitioned into the 2 main clusters in terms of similar colours of displayed objects. Each main cluster was further partitioned ...

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

    African Journals Online (AJOL)

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

  1. Priority-Based Hierarchical Operational Management for Multiagent-Based Microgrids

    Directory of Open Access Journals (Sweden)

    Takumi Kato

    2014-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Yoshinobu Hagiwara

    2018-03-01

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

  3. Control of Batch Processes Based on Hierarchical Petri Nets

    OpenAIRE

    YAJIMA, Tomoyuki; ITO, Takashi; HASHIZUME, Susumu; KURIMOTO, Hidekazu; ONOGI, Katsuaki

    2004-01-01

    A batch process is a typical concurrent system in which multiple interacting tasks are carried out in parallel on several batches at the same time. A major difficulty in designing a batch control system is the lack of modeling techniques. This paper aims at developing a method of constructing batch control system models in a hierarchical manner and operating batch processes using the constructed models. For this purpose, it first defines process and plant specifications described by partial l...

  4. Hierarchical, model-based risk management of critical infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Baiardi, F. [Polo G.Marconi La Spezia, Universita di Pisa, Pisa (Italy); Dipartimento di Informatica, Universita di Pisa, L.go B.Pontecorvo 3 56127, Pisa (Italy)], E-mail: f.baiardi@unipi.it; Telmon, C.; Sgandurra, D. [Dipartimento di Informatica, Universita di Pisa, L.go B.Pontecorvo 3 56127, Pisa (Italy)

    2009-09-15

    Risk management is a process that includes several steps, from vulnerability analysis to the formulation of a risk mitigation plan that selects countermeasures to be adopted. With reference to an information infrastructure, we present a risk management strategy that considers a sequence of hierarchical models, each describing dependencies among infrastructure components. A dependency exists anytime a security-related attribute of a component depends upon the attributes of other components. We discuss how this notion supports the formal definition of risk mitigation plan and the evaluation of the infrastructure robustness. A hierarchical relation exists among models that are analyzed because each model increases the level of details of some components in a previous one. Since components and dependencies are modeled through a hypergraph, to increase the model detail level, some hypergraph nodes are replaced by more and more detailed hypergraphs. We show how critical information for the assessment can be automatically deduced from the hypergraph and define conditions that determine cases where a hierarchical decomposition simplifies the assessment. In these cases, the assessment has to analyze the hypergraph that replaces the component rather than applying again all the analyses to a more detailed, and hence larger, hypergraph. We also show how the proposed framework supports the definition of a risk mitigation plan and discuss some indicators of the overall infrastructure robustness. Lastly, the development of tools to support the assessment is discussed.

  5. Hierarchical, model-based risk management of critical infrastructures

    International Nuclear Information System (INIS)

    Baiardi, F.; Telmon, C.; Sgandurra, D.

    2009-01-01

    Risk management is a process that includes several steps, from vulnerability analysis to the formulation of a risk mitigation plan that selects countermeasures to be adopted. With reference to an information infrastructure, we present a risk management strategy that considers a sequence of hierarchical models, each describing dependencies among infrastructure components. A dependency exists anytime a security-related attribute of a component depends upon the attributes of other components. We discuss how this notion supports the formal definition of risk mitigation plan and the evaluation of the infrastructure robustness. A hierarchical relation exists among models that are analyzed because each model increases the level of details of some components in a previous one. Since components and dependencies are modeled through a hypergraph, to increase the model detail level, some hypergraph nodes are replaced by more and more detailed hypergraphs. We show how critical information for the assessment can be automatically deduced from the hypergraph and define conditions that determine cases where a hierarchical decomposition simplifies the assessment. In these cases, the assessment has to analyze the hypergraph that replaces the component rather than applying again all the analyses to a more detailed, and hence larger, hypergraph. We also show how the proposed framework supports the definition of a risk mitigation plan and discuss some indicators of the overall infrastructure robustness. Lastly, the development of tools to support the assessment is discussed.

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

    Science.gov (United States)

    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.

  7. Superhydrophobic SERS substrates based on silicon hierarchical nanostructures

    Science.gov (United States)

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

    2018-02-01

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

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

    Science.gov (United States)

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

    2017-03-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

    Kolekar, M. H.; Sengupta, S.

    2005-07-01

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

  11. Flexible Transparent Supercapacitors Based on Hierarchical Nanocomposite Films.

    Science.gov (United States)

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

    2017-05-31

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2015-12-07

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

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

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  16. Hierarchical Segmentation Using Tree-Based Shape Spaces.

    Science.gov (United States)

    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. IPTV traffic management using topology-based hierarchical scheduling in Carrier Ethernet transport networks

    DEFF Research Database (Denmark)

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

    2009-01-01

    of Service (QoS) provisioning abilities, which guarantee end-to-end performances of voice, video and data traffic delivered over networks. This paper introduces a topology-based hierarchical scheduler scheme, which controls the incoming traffic at the edge of the network based on the network topology....... This work has been carried out as a part of the research project HIPT (High quality IP network for IPTV and VoIP) founded by Danish Advanced Technology Foundation....

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

    Science.gov (United States)

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

    2017-07-19

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

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

    Science.gov (United States)

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

    2017-04-01

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

  20. Non-hierarchical clustering of Manihot esculenta Crantz germplasm based on quantitative traits

    OpenAIRE

    Oliveira, Eder Jorge de; Aud, Fabiana Ferraz; Morales, Cinara Fernanda Garcia; Oliveira, Saulo Alves Santos de; Santos, Vanderlei da Silva

    2016-01-01

    ABSTRACT The knowledge of the phenotypic variation of cassava (Manihot esculenta Crantz) germplasm allows the estimative of the genetic variability to support the selection of contrasting genitors. Therefore, the aim of this work was to define homogeneous groups of cassava germplasm based on yield traits, disease resistance and root quality using K-means as a non-hierarchical method. Breeding values estimated by Best Linear Unbiased Predictor (BLUP) were used for the cluster analysis. The num...

  1. Learning-based hierarchical graph for unsupervised matting and foreground estimation.

    Science.gov (United States)

    Tseng, Chen-Yu; Wang, Sheng-Jyh

    2014-12-01

    Automatically extracting foreground objects from a natural image remains a challenging task. This paper presents a learning-based hierarchical graph for unsupervised matting. The proposed hierarchical framework progressively condenses image data from pixels into cells, from cells into components, and finally from components into matting layers. First, in the proposed framework, a graph-based contraction process is proposed to condense image pixels into cells in order to reduce the computational loads in the subsequent processes. Cells are further mapped into matting components using spectral clustering over a learning based graph. The graph affinity is efficiently learnt from image patches of different resolutions and the inclusion of multiscale information can effectively improve the performance of spectral clustering. In the final stage of the hierarchical scheme, we propose a multilayer foreground estimation process to assemble matting components into a set of matting layers. Unlike conventional approaches, which typically address binary foreground/background partitioning, the proposed method provides a set of multilayer interpretations for unsupervised matting. Experimental results show that the proposed approach can generate more consistent and accurate results as compared with state-of-the-art techniques.

  2. Automatic complex building reconstruction from LIDAR based on hierarchical structure analysis

    Science.gov (United States)

    Li, Lelin; Zhang, Jing; Jiang, Wangshou

    2009-10-01

    Since manual surface reconstruction is very costly and time consuming, the development of automatic algorithm is of great importance. In this paper a fully automated technique based on hierarchical structure analysis of the building to extract urban building models from LIDAR data is presented. In the processing of reconstruction, the existing automatic algorithm can solve some simple building reconstructions, such as flat roof, gabled roof. As to complex buildings, many researchers use external information or manual interaction for help because of the complexity of the reconstruction and the uncertainty of the building models especially in urban areas. The contour has the characteristics of closed loop, not intersect and deterministic topological relationship, which can be used to extract building ROI (region of interesting). A contours tree is constructed, the topological relationships between the different contours which extracted by TIN from the LIDAR data are established, then the relationships among each hierarchical model can be determined by the analysis of the topological relationship among contour clusters and a component tree corresponding to the building can be constructed by tracing the contours tree. The accurate edges of hierarchical model can be gained by the "polarized cornerity index"-based polygonal approximation of the contour. Especially, a 3D model recognition based on 2D shape recognition is employed. According to the characteristics of the contours, the category of the primitive parts can be classified. We assemble the hierarchical models by using the topological relationships among layers, then, the complete model of the building can be obtained. Experimental results show that the proposed algorithm is suitable for automatically producing building models including most complex buildings from LIDAR data in urban areas.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    In this paper, the hierarchical control strategy of a photovoltaic/battery based dc microgrid is presented for electric vehicle (EV) wireless charging. Considering irradiance variations, battery charging/discharging requirements, wireless power transmission characteristics, and onboard battery...... charging power change and other factors, the possible operation states are obtained. A hierarchical control strategy is established, which includes central and local controllers. The central controller is responsible for the selection and transfer of operation states and the management of the local...... controllers. Local controllers implement these functions, which include PV maximum power point tracking (MPPT) algorithm, battery charging/discharging control, voltage control of DC bus for high-frequency inverter, and onboard battery charging control. By optimizing and matching parameters of transmitting...

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

    Science.gov (United States)

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

    2014-09-01

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

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

    KAUST Repository

    Li, Hui

    2018-02-01

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

  6. A Direct Elliptic Solver Based on Hierarchically Low-Rank Schur Complements

    KAUST Repository

    Chávez, Gustavo

    2017-03-17

    A parallel fast direct solver for rank-compressible block tridiagonal linear systems is presented. Algorithmic synergies between Cyclic Reduction and Hierarchical matrix arithmetic operations result in a solver with O(Nlog2N) arithmetic complexity and O(NlogN) memory footprint. We provide a baseline for performance and applicability by comparing with well-known implementations of the $$\\\\mathcal{H}$$ -LU factorization and algebraic multigrid within a shared-memory parallel environment that leverages the concurrency features of the method. Numerical experiments reveal that this method is comparable with other fast direct solvers based on Hierarchical Matrices such as $$\\\\mathcal{H}$$ -LU and that it can tackle problems where algebraic multigrid fails to converge.

  7. A Hierarchical Aggregation Approach for Indicators Based on Data Envelopment Analysis and Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Mohammad Sadegh Pakkar

    2016-01-01

    Full Text Available This research proposes a hierarchical aggregation approach using Data Envelopment Analysis (DEA and Analytic Hierarchy Process (AHP for indicators. The core logic of the proposed approach is to reflect the hierarchical structures of indicators and their relative priorities in constructing composite indicators (CIs, simultaneously. Under hierarchical structures, the indicators of similar characteristics can be grouped into sub-categories and further into categories. According to this approach, we define a domain of composite losses, i.e., a reduction in CI values, based on two sets of weights. The first set represents the weights of indicators for each Decision Making Unit (DMU with the minimal composite loss, and the second set represents the weights of indicators bounded by AHP with the maximal composite loss. Using a parametric distance model, we explore various ranking positions for DMUs while the indicator weights obtained from a three-level DEA-based CI model shift towards the corresponding weights bounded by AHP. An illustrative example of road safety performance indicators (SPIs for a set of European countries highlights the usefulness of the proposed approach.

  8. Reliability analysis of hierarchical computer-based systems subject to common-cause failures

    International Nuclear Information System (INIS)

    Xing Liudong; Meshkat, Leila; Donohue, Susan K.

    2007-01-01

    The results from reliability modeling and analysis are key contributors to design and tuning activities for computer-based systems. Each architecture style, however, poses different challenges for which analytical approaches must be developed or modified. The challenge we address in this paper is the reliability analysis of hierarchical computer-based systems (HS) with common-cause failures (CCF). The dependencies among components introduced by CCF complicate the reliability analysis of HS, especially when components affected by a common cause exist on different hierarchical levels. We propose an efficient decomposition and aggregation (EDA) approach for incorporating CCF into the reliability evaluation of HS. Our approach is to decompose an original HS reliability analysis problem with CCF into a number of reduced reliability problems freed from the CCF concerns. The approach is represented in a dynamic fault tree by a proposed CCF gate modeled after the functional dependency gate. We present the basics of the EDA approach by working through a hypothetical analysis of a HS subject to CCF and show how it can be extended to an analysis of a hierarchical phased-mission system subject to different CCF depending on mission phases

  9. Evaluating the Relevance of Corporate Ontological Knowledge Base Documents Using Their Hierarchical Role Clustering

    Directory of Open Access Journals (Sweden)

    A. P. Karpenko

    2014-01-01

    Full Text Available The article considers a corporate knowledge base representing a set of the large number of various semi-structured documents, which describe to some detail precedents i.e. some situations and decisions made in these situations. The task is to find the decision in such knowledge base and search the most suitable precedents and their corresponding documents in it.The work continues a series of the authors’ works, which develop an original approach to the solution of this task. It is supposed that metadata of the knowledge base documents are based on the ontology of the corresponding subject domain specified as a semantic network. As opposed to the previous works it is necessary that ontology of subject domain, and thereby and corresponding semantic network, is hierarchically clustered based on the roles of concepts.Documents in the knowledge base, and also search queries are presented as frames, which are called ‘patterns of design and inquiry’, respectively. Slots of these patterns correspond to roles of concepts of the used ontology. Above-noted roles break concepts of ontology, document, and request to the knowledge base into clusters. It is supposed that semantic networks of the abovementioned clusters are designed by a technique for creation of a semantic network of the document. Thus, search images of the document and inquiry are presented as a set of the semantic networks corresponding to slots of a pattern of design and a pattern of inquiry.The work offers the model of a semantic network of the ontological knowledge base using a hierarchical role clustering of concepts of this ontology. The task for a multi-criteria evaluation of relevance of corporate ontological knowledge base documents using their hierarchical role clustering is set. The method is offered to solve the task using the original measures of proximity of role patterns of design of the required document and inquiry.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Bin [Los Alamos National Laboratory; Hlavacek, William [Los Alamos National Laboratory

    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.

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

    Directory of Open Access Journals (Sweden)

    Lucas eBrely

    2015-07-01

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

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

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

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

  13. Robust Superhydrophobic Foam: A Graphdiyne-Based Hierarchical Architecture for Oil/Water Separation.

    Science.gov (United States)

    Gao, Xin; Zhou, Jingyuan; Du, Ran; Xie, Ziqian; Deng, Shibin; Liu, Rong; Liu, Zhongfan; Zhang, Jin

    2016-01-06

    Robust superhydrophobic foam is fabricated by combining an ordered graphdiyne-based hierarchical structure with a low-surface-energy coating. This foam shows not only superhydrophobicity both in air (≈160.1°) and in oil (≈171.0°), but also high resistance toward abrasion cycles. Owing to its 3D porous structures and numerous superhydrophobic surfaces, it can easily separate oil from water with high efficiency and good recyclability. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

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

    2015-11-17

    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.

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

    Directory of Open Access Journals (Sweden)

    Ismail Butun

    2015-11-01

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-02-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

  18. Vehicle Chassis Integrated Control Based on Multimodel and Multilevel Hierarchical Control

    Directory of Open Access Journals (Sweden)

    Shu-en Zhao

    2014-01-01

    Full Text Available Aiming at the differences of vehicle chassis key subsystems influence on vehicle handling stability and effective acting regions, comprehensive considering of the nonlinear characteristic of the tires and the dynamic coupling among suspension, steering, and braking subsystems in vehicle chassis, the 14-DOF full vehicle model is built. Based on the control characteristic local optimum of each subsystem, multilevel hierarchical control theory is adopted and the vehicle stability coordinated control system including organization, coordination, and execution level is established. Using sliding mode control theory and the inverse tire model, the generalized target forces and moments from organization level are translated into the tire sideslip angle and slip ratio. And then, based on the principle of functional allocation, the control functions of each subsystem are coordinated and the function decoupling of vehicle chassis complex system is realized. The Matlab/Simulink platform is used and the full vehicle stability coordinated control system is simulated. The results show that the full vehicle coordinated control system based on multilevel hierarchical control theory can improve the vehicle stability preferably than the subsystem combined control and uncontrolled system.

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

    Directory of Open Access Journals (Sweden)

    Nabil Sabor

    2017-01-01

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

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

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

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

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

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    Peng Han

    2014-01-01

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

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    Housman, E.; Bush, E.R.

    1993-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Li-Mei Peng

    2010-03-01

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

  5. Gating mechanisms of mechanosensitive channels of large conductance, I: a continuum mechanics-based hierarchical framework.

    Science.gov (United States)

    Chen, Xi; Cui, Qiang; Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun

    2008-07-01

    A hierarchical simulation framework that integrates information from molecular dynamics (MD) simulations into a continuum model is established to study the mechanical response of mechanosensitive channel of large-conductance (MscL) using the finite element method (FEM). The proposed MD-decorated FEM (MDeFEM) approach is used to explore the detailed gating mechanisms of the MscL in Escherichia coli embedded in a palmitoyloleoylphosphatidylethanolamine lipid bilayer. In Part I of this study, the framework of MDeFEM is established. The transmembrane and cytoplasmic helices are taken to be elastic rods, the loops are modeled as springs, and the lipid bilayer is approximated by a three-layer sheet. The mechanical properties of the continuum components, as well as their interactions, are derived from molecular simulations based on atomic force fields. In addition, analytical closed-form continuum model and elastic network model are established to complement the MDeFEM approach and to capture the most essential features of gating. In Part II of this study, the detailed gating mechanisms of E. coli-MscL under various types of loading are presented and compared with experiments, structural model, and all-atom simulations, as well as the analytical models established in Part I. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction.

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

    Directory of Open Access Journals (Sweden)

    Jinjun Tang

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

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

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

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

  8. Fabrication of semi-transparent superoleophobic thin film from fabrics and nanoparticle-based hierarchical structure

    Directory of Open Access Journals (Sweden)

    Nishizawa S.

    2013-08-01

    Full Text Available Superoleophobic thin films have many potential applications including fluid transfer, fluid power systems, stain resistant and antifouling materials, and microfluidics among others. Transparency is also desired with superhydrophobicity for their numerous applications; however transparency and oleophobicity are almost incompatible relationship with each other in the point of surface structure. Because oleophobicity required rougher structure at nano-micro scale than hydrophobicity, and these rough structure brings light scattering. So far, there is very few report of the compatible of transparency and superoleophobicity. In this report, we proposed the see-through type fabrics using the nanoparticle-based hierarchical structure thin film for improving both of oleophobicity and transparency. The vacant space between fibrils of fabrics has two important roles: the one is to through the light, another one is to introduce air layer to realize Cassie state of liquid droplet on thin film. To realize the low surface energy and nanoscale rough structure surface on fibrils, we used the spray method with perfluoroalkyl methacrylic copolymer (PMC, silica nano particles and volatile solvent. From the SEM image, the hierarchical structures of nanoparticle were formed uniformly on the fabrics. The transparency of thin film obtained was approximately 61% and the change of transparency between pre-coated fabrics and coated was 11%. From investigation of the surface wettability, the contact angles of oils (rapeseed oil and hexadecane and water droplet on the fabricated film were over 150 degree.

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

    Science.gov (United States)

    Yan, Liang; Rong, Chunming; Zhao, Gansen

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

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

    Science.gov (United States)

    Zhu, Aichun; Wang, Tian; Snoussi, Hichem

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Aichun Zhu

    2018-03-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Muhammad Fayaz

    2017-10-01

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

  14. A Study of Tacit Knowledge Transfer Based on Complex Networks Technology in Hierarchical Organizations

    Science.gov (United States)

    Cheng, Tingting; Wang, Hengshan; Wang, Lubang

    In reality, most economic entities are hierarchical organizations. But in the hierarchical organizations tacit knowledge can be transferred across different hierarchies even across different departments. By use of complex networks technology, a hierarchical organization’s framework is modeled in this paper. Through quantifying a number of technical datas we analyze and have a research on the transfer distance and the optimum tacit knowledge transfer path in hierarchy networks.

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

    Science.gov (United States)

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

    2014-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Ariful Azad

    2016-08-01

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

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

    Science.gov (United States)

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

    2011-02-01

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

  18. SOFM Neural Network Based Hierarchical Topology Control for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhi Chen

    2014-01-01

    Full Text Available Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs. Self-organization feature map (SOFM neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the competitive learning among nodes, and takes the node residual energy and the distance to the neighbor nodes into account in the clustering process. In addition, the approach of dynamically adjusting the transmitting power of the cluster head nodes is adopted to optimize the network topology. Simulation results show that SOFMHTC may get a better energy-efficient performance and make more balanced energy consumption compared with some existing algorithms in WSNs.

  19. Hierarchical model-based predictive control of a power plant portfolio

    DEFF Research Database (Denmark)

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

    2011-01-01

    optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...... control” – becomes increasingly important as the ratio of renewable energy in a power system grows. As a consequence, tomorrow's “smart grids” require highly flexible and scalable control systems compared to conventional power systems. This paper proposes a hierarchical model-based predictive control......One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...

  20. Active Power Quality Improvement Strategy for Grid-connected Microgrid Based on Hierarchical Control

    DEFF Research Database (Denmark)

    Wei, Feng; Sun, Kai; Guan, Yajuan

    2018-01-01

    proposes an active, unbalanced, and harmonic GCC suppression strategy based on hierarchical theory. The voltage error between the bus of the DCGC-MG and the grid’s PCC was transformed to the dq frame. On the basis of the grid, an additional compensator, which consists of multiple resonant voltage......When connected to a distorted grid utility, droop-controlled grid-connected microgrids (DCGC-MG) exhibit low equivalent impedance. The harmonic and unbalanced voltage at the point of common coupling (PCC) deteriorates the power quality of the grid-connected current (GCC) of DCGC-MG. This work...... regulators, was then added to the original secondary control to generate the negative fundamental and unbalanced harmonic voltage reference. Proportional integral and multiple resonant controllers were adopted as voltage controller at the original primary level to improve the voltage tracking performance...

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

    Science.gov (United States)

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

    2011-06-01

    The pathways by which proteins fold into their specific native structure are still an unsolved mystery. Currently, many methods for protein structure prediction are available, and most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations toward each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method's abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the template-based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for template-based structure prediction, and in particular, the docking-basedranking technique presented here can be incorporated into any profile-profile comparison based method. Copyright © 2011 Wiley-Liss, Inc.

  2. Evaluation of the hierarchical control of distributed Energy Storage Systems in islanded Microgrids based on Std IEC/ISO 62264

    DEFF Research Database (Denmark)

    Palizban, Omid; Kauhaniemi, Kimmo; Guerrero, Josep M.

    2016-01-01

    In this paper, a decentralized control methodology based on hierarchical control levels is investigated. In recent years, efforts have been made to standardize microgrids (MGs), and the decentralized control method evaluated here is based on the IEC/ISO 62264 standard. Since the main challenge to...

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

    Science.gov (United States)

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

    2017-02-01

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

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

    Science.gov (United States)

    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

  5. The Optimal Confidence Intervals for Agricultural Products’ Price Forecasts Based on Hierarchical Historical Errors

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-12-01

    Full Text Available With the levels of confidence and system complexity, interval forecasts and entropy analysis can deliver more information than point forecasts. In this paper, we take receivers’ demands as our starting point, use the trade-off model between accuracy and informativeness as the criterion to construct the optimal confidence interval, derive the theoretical formula of the optimal confidence interval and propose a practical and efficient algorithm based on entropy theory and complexity theory. In order to improve the estimation precision of the error distribution, the point prediction errors are STRATIFIED according to prices and the complexity of the system; the corresponding prediction error samples are obtained by the prices stratification; and the error distributions are estimated by the kernel function method and the stability of the system. In a stable and orderly environment for price forecasting, we obtain point prediction error samples by the weighted local region and RBF (Radial basis function neural network methods, forecast the intervals of the soybean meal and non-GMO (Genetically Modified Organism soybean continuous futures closing prices and implement unconditional coverage, independence and conditional coverage tests for the simulation results. The empirical results are compared from various interval evaluation indicators, different levels of noise, several target confidence levels and different point prediction methods. The analysis shows that the optimal interval construction method is better than the equal probability method and the shortest interval method and has good anti-noise ability with the reduction of system entropy; the hierarchical estimation error method can obtain higher accuracy and better interval estimation than the non-hierarchical method in a stable system.

  6. Flexible free-standing luminescent two-component fiber films with tunable hierarchical structures based on hydrogen-bonding architecture.

    Science.gov (United States)

    Yan, Dongpeng; Williams, Gareth R; Zhao, Min; Li, Changming; Fan, Guoling; Yang, Hejia

    2013-12-17

    Although the fabrication of hierarchical architectures with highly ordered functional units is of great importance for both fundamental science and practical application, the development of one-dimensional (1D) organic hierarchical micro/nanostructures based on low-molecular-weight (LMW) building blocks remains at an early stage. Herein, we report two types of micro/nanoscaled multicomponent fluorescent fiber systems with tunable hierarchical morphologies through a one-step coassembly process. With the aid of hydrogen-bonding motifs, LMW precursors (1,4-bis(5-phenyloxazol-2-yl)benzene (A) and two coassembled building blocks: 4-bromotetrafluorobenzene carboxylic acid (B) and 2,3,4,5,6-pentafluorophenol (C)) have been self-organized into fibers and flexible free-standing films, which show hierarchical micro/nanostructures as well as tunable one-/two-photon luminescence. The disassembly of the multicomponent A.B and A.C fibers occurs at high temperature, which further alters the luminescence properties of the multicomponent materials. Therefore, this work provides a facile wet chemical route for fabricating multicomponent LMW self-assembled fibers and free-standing film systems with tunable hierarchical structures and photoemission behaviors, and such self-organized systems may have potential applications in fields of two-photon luminescence and thermal sensors.

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

    Directory of Open Access Journals (Sweden)

    Kellermann Walter

    2007-01-01

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

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

    Science.gov (United States)

    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

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

  11. A hierarchical detection method in external communication for self-driving vehicles based on TDMA.

    Science.gov (United States)

    Alheeti, Khattab M Ali; Al-Ani, Muzhir Shaban; McDonald-Maier, Klaus

    2018-01-01

    Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.

  12. Correlation-Based Tracking of Multiple Targets With Hierarchical Layered Structure.

    Science.gov (United States)

    Cao, Xianbin; Jiang, Xiaolong; Li, Xiaomei; Yan, Pingkun

    2018-01-01

    Visual target tracking is one of the most important research areas in the field of computer vision. Within this realm, multiple targets tracking (MTT) under complicated scene stands out for its great availability in real life applications, such as urban traffic surveillance and sports video analysis. However, in MTT, main difficulties arise from large variation in target saliency and significant motion heterogeneity, which may result in the failure of tracking weak targets. To tackle this challenge, a novel hierarchical layered tracking structure is proposed to perform tracking sequentially layer-by-layer. Upon this layered structure, we establish an intertarget mutual assistance mechanism on basis of intertarget correlation exploited among targets. The tracking results of a subset of targets can be utilized as additional prior information for tracking other targets. Specifically, a nonlinear motion model as well as a target interaction model basing on the intertarget correlation are proposed to effectively estimate the possible target region-of-interest to facilitate the prediction-based tracking. Moreover, the concept of motion entropy is introduced to quantitatively measure the degree of motion heterogeneity within the tracking scene for layer construction. Compared to other existing methods, extensive experiments demonstrated that the proposed method is capable of achieving higher tracking performance in complicated scenes, where targets are characterized with great heterogeneity.

  13. Trimethylamine Sensors Based on Au-Modified Hierarchical Porous Single-Crystalline ZnO Nanosheets

    Directory of Open Access Journals (Sweden)

    Fanli Meng

    2017-06-01

    Full Text Available It is of great significance for dynamic monitoring of foods in storage or during the transportation process through on-line detecting trimethylamine (TMA. Here, TMA were sensitively detected by Au-modified hierarchical porous single-crystalline ZnO nanosheets (HPSCZNs-based sensors. The HPSCZNs were synthesized through a one-pot wet-chemical method followed by an annealing treatment. Polyethyleneimine (PEI was used to modify the surface of the HPSCZNs, and then the PEI-modified samples were mixed with Au nanoparticles (NPs sol solution. Electrostatic interactions drive Au nanoparticles loading onto the surface of the HPSCZNs. The Au-modified HPSCZNs were characterized by X-ray diffraction (XRD, scanning electron microscopy (SEM, transmission electron microscopy (TEM and energy dispersive spectrum (EDS, respectively. The results show that Au-modified HPSCZNs-based sensors exhibit a high response to TMA. The linear range is from 10 to 300 ppb; while the detection limit is 10 ppb, which is the lowest value to our knowledge.

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

    Science.gov (United States)

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

    2014-01-01

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

  15. An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability

    Directory of Open Access Journals (Sweden)

    Xulin Guo

    2013-02-01

    Full Text Available Over 50% of world’s population presently resides in cities, and this number is expected to rise to ~70% by 2050. Increasing urbanization problems including population growth, urban sprawl, land use change, unemployment, and environmental degradation, have markedly impacted urban residents’ Quality of Life (QOL. Therefore, urban sustainability and its measurement have gained increasing attention from administrators, urban planners, and scientific communities throughout the world with respect to improving urban development and human well-being. The widely accepted definition of urban sustainability emphasizes the balancing development of three primary domains (urban economy, society, and environment. This article attempts to improve the aforementioned definition of urban sustainability by incorporating a human well-being dimension. Major problems identified in existing urban sustainability indicator (USI models include a weak integration of potential indicators, poor measurement and quantification, and insufficient spatial-temporal analysis. To tackle these challenges an integrated USI model based on a hierarchical indices system was established for monitoring and evaluating urban sustainability. This model can be performed by quantifying indicators using both traditional statistical approaches and advanced geomatic techniques based on satellite imagery and census data, which aims to provide a theoretical basis for a comprehensive assessment of urban sustainability from a spatial-temporal perspective.

  16. A hierarchical detection method in external communication for self-driving vehicles based on TDMA

    Science.gov (United States)

    Al-ani, Muzhir Shaban; McDonald-Maier, Klaus

    2018-01-01

    Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms. PMID:29315302

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

    Directory of Open Access Journals (Sweden)

    Linjun Fan

    2014-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    Science.gov (United States)

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

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

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

    KAUST Repository

    Tian, Qiwei

    2016-02-05

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

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

    Science.gov (United States)

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

    2001-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Kai Wang

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

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

    Science.gov (United States)

    Yigitsoy, Mehmet; Schmidt, Günter

    2017-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-01

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

  6. Lamellar Microdomains of Block-Copolymer-Based Ionic Supramolecules Exhibiting a Hierarchical Self-Assembly

    DEFF Research Database (Denmark)

    Ayoubi, Mehran Asad; Almdal, Kristoffer; Zhu, Kaizheng

    2014-01-01

    (Cn; n = 8, 12, and 16) trimethylammonium counterions (i.e., side chains) at various ion (pair) fractions X [i.e., counterion/side-chain grafting density; X = number of alkyl counterions (i.e., side chains) per acidic group of the parent PMAA block] these L-b-AC ionic supramolecules exhibit...... a spherical-in-lamellar hierarchical self-assembly. For these systems, (1) the effective Flory-Huggins interaction parameter between L- and AC-blocks chi'(Cn/x) was extracted, and (2) analysis of the lamellar microdomains showed that when there is an increase in X, alkyl counterion (i.e., side chain) length l......Based on a parent diblock copolymer of poly(styrene)-b-poly(methacrylic acid), PS-b-PMAA, linear-b-amphiphilic comb (L-b-AC) ionic supramolecules [Soft Matter 2013, 9, 1540-1555] are synthesized in which the poly(methacrylate) backbone of the ionic supramolecular AC-block is neutralized by alkyl...

  7. Pedestrian detection algorithm in traffic scene based on weakly supervised hierarchical deep model

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2016-02-01

    Full Text Available The emergence and development of deep learning theory in machine learning field provide new method for visual-based pedestrian recognition technology. To achieve better performance in this application, an improved weakly supervised hierarchical deep learning pedestrian recognition algorithm with two-dimensional deep belief networks is proposed. The improvements are made by taking into consideration the weaknesses of structure and training methods of existing classifiers. First, traditional one-dimensional deep belief network is expanded to two-dimensional that allows image matrix to be loaded directly to preserve more information of a sample space. Then, a determination regularization term with small weight is added to the traditional unsupervised training objective function. By this modification, original unsupervised training is transformed to weakly supervised training. Subsequently, that gives the extracted features discrimination ability. Multiple sets of comparative experiments show that the performance of the proposed algorithm is better than other deep learning algorithms in recognition rate and outperforms most of the existing state-of-the-art methods in non-occlusion pedestrian data set while performs fair in weakly and heavily occlusion data set.

  8. A hierarchical NeuroBayes-based algorithm for full reconstruction of B mesons at B factories

    Energy Technology Data Exchange (ETDEWEB)

    Feindt, M.; Keller, F.; Kreps, M.; Kuhr, T. [Institut fuer Experimentelle Kernphysik, Karlsruher Institut fuer Technologie, Campus Sued, Postfach 69 80, 76128 Karlsruhe (Germany); Neubauer, S., E-mail: neubauer@ekp.uni-karlsruhe.de [Institut fuer Experimentelle Kernphysik, Karlsruher Institut fuer Technologie, Campus Sued, Postfach 69 80, 76128 Karlsruhe (Germany); Zander, D.; Zupanc, A. [Institut fuer Experimentelle Kernphysik, Karlsruher Institut fuer Technologie, Campus Sued, Postfach 69 80, 76128 Karlsruhe (Germany)

    2011-10-21

    We describe a new B-meson full reconstruction algorithm designed for the Belle experiment at the B-factory KEKB, an asymmetric e{sup +}e{sup -} collider that collected a data sample of 771.6x10{sup 6}BB-bar pairs during its running time. To maximize the number of reconstructed B decay channels, it utilizes a hierarchical reconstruction procedure and probabilistic calculus instead of classical selection cuts. The multivariate analysis package NeuroBayes was used extensively to hold the balance between highest possible efficiency, robustness and acceptable consumption of CPU time. In total, 1104 exclusive decay channels were reconstructed, employing 71 neural networks altogether. Overall, we correctly reconstruct one B{sup {+-}} or B{sup 0} candidate in 0.28% or 0.18% of the BB-bar events, respectively. Compared to the cut-based classical reconstruction algorithm used at the Belle experiment, this is an improvement in efficiency by roughly a factor of 2, depending on the analysis considered. The new framework also features the ability to choose the desired purity or efficiency of the fully reconstructed sample freely. If the same purity as for the classical full reconstruction code is desired ({approx}25%), the efficiency is still larger by nearly a factor of 2. If, on the other hand, the efficiency is chosen at a similar level as the classical full reconstruction, the purity rises from {approx}25% to nearly 90%.

  9. Hierarchical Terrain Classification Based on Multilayer Bayesian Network and Conditional Random Field

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-01-01

    Full Text Available This paper presents a hierarchical classification approach for Synthetic Aperture Radar (SAR images. The Conditional Random Field (CRF and Bayesian Network (BN are employed to incorporate prior knowledge into this approach for facilitating SAR image classification. (1 A multilayer region pyramid is constructed based on multiscale oversegmentation, and then, CRF is used to model the spatial relationships among those extracted regions within each layer of the region pyramid; the boundary prior knowledge is exploited and integrated into the CRF model as a strengthened constraint to improve classification performance near the boundaries. (2 Multilayer BN is applied to establish the causal connections between adjacent layers of the constructed region pyramid, where the classification probabilities of those sub-regions in the lower layer, conditioned on their parents’ regions in the upper layer, are used as adjacent links. More contextual information is taken into account in this framework, which is a benefit to the performance improvement. Several experiments are conducted on real ESAR and TerraSAR data, and the results show that the proposed method achieves better classification accuracy.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-11-15

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

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

    Science.gov (United States)

    Kantar, Ersin; Deviren, Bayram; Keskin, Mustafa

    2014-11-01

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

  12. Hierarchical Role Ontology-based Assessment of Trainee’s Conceptual Knowledge

    Directory of Open Access Journals (Sweden)

    V. V. Belous

    2014-01-01

    Full Text Available We believe that this knowledge base of training system structure is based on the subject semantic network (SSN containing concepts of subject domain and relations between them. The SSN is represented as a direct graph, with tops corresponding to concepts, and arcs corresponding to relations. We consider a technique for trainee’s conceptual knowledge assessment using the cognitive maps of trainees (CMT, each of which formalizes his ideas of some SSN fragment and theoretically coincides with this fragment. Assessment of trainee’s achievement of this SSN fragment comes to comparison of SSN subgraph, corresponding to this fragment, with the direct graph, which is defined by the corresponding CMT.A number of important subject domains possess the property that concepts in them have the attribute called ‘role’, and roles of concepts can be linearly sorted. The direct graph SSN, corresponding to such ontology can be presented in a tiered form.The work concerns the assessment of trainee’s conceptual knowledge in the subject domains of this class. The work represents the SSN and CMT models used, describes the offered methods to create CMT, as well metrics for trainee’s achievement of the conceptual knowledge based on his CMT.The main results of work are the following: the model of the semantic network corresponding to hierarchical role ontology, and also a model of a trainee’s cognitive map of are offered, methods for creating the trainee’s cognitive maps are developed, metrics of trainee’s achievement of conceptual knowledge are suggested.

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

    International Nuclear Information System (INIS)

    Dimas, Leon S; Buehler, Markus J

    2012-01-01

    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. (paper)

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

    Directory of Open Access Journals (Sweden)

    Atena Roshan Fekr

    2014-06-01

    Full Text Available 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

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

    Science.gov (United States)

    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

  16. Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

    Directory of Open Access Journals (Sweden)

    Jaron T Colas

    Full Text Available In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

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

    KAUST Repository

    Chen, Ping-Hei

    2011-01-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Science.gov (United States)

    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.

  20. A hierarchical network-based algorithm for multi-scale watershed delineation

    Science.gov (United States)

    Castronova, Anthony M.; Goodall, Jonathan L.

    2014-11-01

    Watershed delineation is a process for defining a land area that contributes surface water flow to a single outlet point. It is a commonly used in water resources analysis to define the domain in which hydrologic process calculations are applied. There has been a growing effort over the past decade to improve surface elevation measurements in the U.S., which has had a significant impact on the accuracy of hydrologic calculations. Traditional watershed processing on these elevation rasters, however, becomes more burdensome as data resolution increases. As a result, processing of these datasets can be troublesome on standard desktop computers. This challenge has resulted in numerous works that aim to provide high performance computing solutions to large data, high resolution data, or both. This work proposes an efficient watershed delineation algorithm for use in desktop computing environments that leverages existing data, U.S. Geological Survey (USGS) National Hydrography Dataset Plus (NHD+), and open source software tools to construct watershed boundaries. This approach makes use of U.S. national-level hydrography data that has been precomputed using raster processing algorithms coupled with quality control routines. Our approach uses carefully arranged data and mathematical graph theory to traverse river networks and identify catchment boundaries. We demonstrate this new watershed delineation technique, compare its accuracy with traditional algorithms that derive watershed solely from digital elevation models, and then extend our approach to address subwatershed delineation. Our findings suggest that the open-source hierarchical network-based delineation procedure presented in the work is a promising approach to watershed delineation that can be used summarize publicly available datasets for hydrologic model input pre-processing. Through our analysis, we explore the benefits of reusing the NHD+ datasets for watershed delineation, and find that the our technique

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

    Science.gov (United States)

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

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2010-10-01

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

  6. Hierarchical Communication Diagrams

    OpenAIRE

    Marcin Szpyrka; Piotr Matyasik; Jerzy Biernacki; Agnieszka Biernacka; Michał Wypych; Leszek Kotulski

    2016-01-01

    Formal modelling languages range from strictly textual ones like process algebra scripts to visual modelling languages based on hierarchical graphs like coloured Petri nets. Approaches equipped with visual modelling capabilities make developing process easier and help users to cope with more complex systems. Alvis is a modelling language that combines possibilities of formal models verification with flexibility and simplicity of practical programming languages. The paper deals with hierarchic...

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Science.gov (United States)

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

    2009-02-01

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

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

    Science.gov (United States)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Hu, He; Xu, Jie-yan; Yang, Hong; Liang, Jie [Department of Chemistry, Shanghai Normal University, No. 100, Guilin Road, Shanghai 200234 (China); Yang, Shiping, E-mail: shipingy@shnu.edu.cn [Department of Chemistry, Shanghai Normal University, No. 100, Guilin Road, Shanghai 200234 (China); Wu, Huixia [Department of Chemistry, Shanghai Normal University, No. 100, Guilin Road, Shanghai 200234 (China)

    2011-11-15

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

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

    Science.gov (United States)

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

    Science.gov (United States)

    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

  13. Hierarchical Formation of Fibrillar and Lamellar Self-Assemblies from Guanosine-Based Motifs

    Directory of Open Access Journals (Sweden)

    Paolo Neviani

    2010-01-01

    Full Text Available Here we investigate the supramolecular polymerizations of two lipophilic guanosine derivatives in chloroform by light scattering technique and TEM experiments. The obtained data reveal the presence of several levels of organization due to the hierarchical self-assembly of the guanosine units in ribbons that in turn aggregate in fibrillar or lamellar soft structures. The elucidation of these structures furnishes an explanation to the physical behaviour of guanosine units which display organogelator properties.

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2015-03-23

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

  16. Auditing SNOMED CT hierarchical relations based on lexical features of concepts in non-lattice subgraphs.

    Science.gov (United States)

    Cui, Licong; Bodenreider, Olivier; Shi, Jay; Zhang, Guo-Qiang

    2018-02-01

    We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT's IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the "Clinical Finding" and "Procedure" sub-hierarchies. Two domain experts confirmed 185 (among 223) suggested missing IS-A relations, a precision of 82.96%. Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  18. A hierarchical method for whole-brain connectivity-based parcellation.

    Science.gov (United States)

    Moreno-Dominguez, David; Anwander, Alfred; Knösche, Thomas R

    2014-10-01

    In modern neuroscience there is general agreement that brain function relies on networks and that connectivity is therefore of paramount importance for brain function. Accordingly, the delineation of functional brain areas on the basis of diffusion magnetic resonance imaging (dMRI) and tractography may lead to highly relevant brain maps. Existing methods typically aim to find a predefined number of areas and/or are limited to small regions of grey matter. However, it is in general not likely that a single parcellation dividing the brain into a finite number of areas is an adequate representation of the function-anatomical organization of the brain. In this work, we propose hierarchical clustering as a solution to overcome these limitations and achieve whole-brain parcellation. We demonstrate that this method encodes the information of the underlying structure at all granularity levels in a hierarchical tree or dendrogram. We develop an optimal tree building and processing pipeline that reduces the complexity of the tree with minimal information loss. We show how these trees can be used to compare the similarity structure of different subjects or recordings and how to extract parcellations from them. Our novel approach yields a more exhaustive representation of the real underlying structure and successfully tackles the challenge of whole-brain parcellation. Copyright © 2014 Wiley Periodicals, Inc.

  19. Hierarchical remote data possession checking method based on massive cloud files

    Directory of Open Access Journals (Sweden)

    Ma Haifeng

    2017-06-01

    Full Text Available Cloud storage service enables users to migrate their data and applications to the cloud, which saves the local data maintenance and brings great convenience to the users. But in cloud storage, the storage servers may not be fully trustworthy. How to verify the integrity of cloud data with lower overhead for users has become an increasingly concerned problem. Many remote data integrity protection methods have been proposed, but these methods authenticated cloud files one by one when verifying multiple files. Therefore, the computation and communication overhead are still high. Aiming at this problem, a hierarchical remote data possession checking (hierarchical-remote data possession checking (H-RDPC method is proposed, which can provide efficient and secure remote data integrity protection and can support dynamic data operations. This paper gives the algorithm descriptions, security, and false negative rate analysis of H-RDPC. The security analysis and experimental performance evaluation results show that the proposed H-RDPC is efficient and reliable in verifying massive cloud files, and it has 32–81% improvement in performance compared with RDPC.

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

    Science.gov (United States)

    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.

  1. Nested and Hierarchical Archimax copulas

    KAUST Repository

    Hofert, Marius

    2017-07-03

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Biochar-based carbons with hierarchical micro-meso-macro porosity for high rate and long cycle life supercapacitors

    Science.gov (United States)

    Qiu, Zhipeng; Wang, Yesheng; Bi, Xu; Zhou, Tong; Zhou, Jin; Zhao, Jinping; Miao, Zhichao; Yi, Weiming; Fu, Peng; Zhuo, Shuping

    2018-02-01

    The development of supercapacitors with high energy density and power density is an important research topic despite many challenging issues exist. In this work, porous carbon material was prepared from corn straw biochar and used as the active electrode material for electric double-layer capacitors (EDLCs). During the KOH activation process, the ratio of KOH/biochar significantly affects the microstructure of the resultant carbon, which further influences the capacitive performance. The optimized carbon material possesses typical hierarchical porosity composed of multi-leveled pores with high surface area and pore volume up to 2790.4 m2 g-1 and 2.04 cm3 g-1, respectively. Such hierarchical micro-meso-macro porosity significantly improved the rate performance of the biochar-based carbons. The achieved maximum specific capacitance was 327 F g-1 and maintained a high value of 205 F g-1 at a ultrahigh current density of 100 A g-1. Meanwhile, the prepared EDLCs present excellent cycle stability in alkaline electrolytes for 120 000 cycles at 5 A g-1. Moreover, the biochar-based carbon could work at a high voltage of 1.6 V in neutral Na2SO4, and exhibit a high specific capacitance of 227 F g-1, thus giving an outstanding energy density of 20.2 Wh kg-1.

  6. Hierarchical graphene nanocones over 3D platform of carbon fabrics: a route towards fully foldable graphene based electron source.

    Science.gov (United States)

    Maiti, Uday N; Maiti, Soumen; Das, Nirmalya S; Chattopadhyay, Kalyan K

    2011-10-05

    A three dimensional field emitter comprising hierarchical nanostructures of graphene over flexible fabric substrate is presented. The nanostructuring is realized through plasma treatment of graphene, coaxially deposited over individual carbon fiber by means of simple aqueous phase electrophoretic deposition technique. Hierarchical graphene nanocone, acting as a cold electron emitter, exhibits outstanding electron emission performance with a turn-on field as low as 0.41 V μm(-1) and a threshold field down to 0.81 V μm(-1). Electric field modification around the special woven like geometry of the underlying base fabric substrate serves as the booster to the nanostructured graphene related field amplification at the electron emission site. Superb robustness in the emission stability can be attributed to suppressed joule heating on behalf of higher inborn accessible surface area of graphene nanocone as well as excellent electrical and thermal conductivity of both the graphene and carbon fabrics. Superior flexibility of this high-performance graphene based emitter ensures their potential use in completely foldable and wearable field emission devices.

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

    Directory of Open Access Journals (Sweden)

    Gao Qingji

    2014-04-01

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

  8. Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC, to tackle complex high-dimensional problems. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operator is applied to enhance the global search ability between species. Experiments are conducted on a set of 20 continuous and discrete benchmark problems. The experimental results demonstrate remarkable performance of the HABC algorithm when compared with other six evolutionary algorithms.

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

    Science.gov (United States)

    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

  10. The role of the hierarchical theory in explaining the capital structure of the firms based on enterprise life cycle model

    Directory of Open Access Journals (Sweden)

    Jamal Bahiri Saleth

    2016-01-01

    Full Text Available Capital structure is a controversial issue in the field of corporate finance. There are several studies to find a way to determine the optimal capital structure to minimize the cost of capital and maximize the corporate value. In fact, capital structure is a combination of firms’ liabilities and capital to meet long term assets. This paper investigates the role of the hierarchical theory in explaining the capital structure of the firms based on enterprise life cycle model on selected firms listed on Tehran Stock Exchange (TSE using three methods of net equities, net liabilities and retained earnings. The study uses Park and Chen’s (2006 method [Park, Y., & Chen, K. H. (2006. The effect of accounting conservatism and life-cycle stages on firm valuation. Journal of Applied Business Research (JABR, 22(3, 75-92.] to categorize the life cycle of 81 randomly selected firms from TSE over the period 2007-2012. The results indicate that the hierarchical theory represents the growing firms better than the matured firms do. The results also show that firms were more willing to reduce their dividend per share for financing their projects.

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

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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 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 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. Electronic

  14. Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study

    International Nuclear Information System (INIS)

    Gitinavard, Hossein; Mousavi, S. Meysam; Vahdani, Behnam

    2017-01-01

    In numerous real-world energy decision problems, decision makers often encounter complex environments, in which existent imprecise data and uncertain information lead us to make an appropriate decision. In this paper, a new soft computing group decision-making approach is introduced based on novel compromise ranking method and interval-valued hesitant fuzzy sets (IVHFSs) for energy decision-making problems under multiple criteria. In the proposed approach, the assessment information is provided by energy experts or decision makers based on interval-valued hesitant fuzzy elements under incomplete criteria weights. In this respect, a new ranking index is presented respecting to interval-valued hesitant fuzzy Hamming distance measure to prioritize energy candidates, and criteria weights are computed based on an extended maximizing deviation method by considering the preferences experts' judgments about the relative importance of each criterion. Also, a decision making trial and evaluation laboratory (DEMATEL) method is extended under an IVHF-environment to compute the interdependencies between and within the selected criteria in the hierarchical structure. Accordingly, to demonstrate the applicability of the presented approach a case study and a practical example are provided regarding to hierarchical structure and criteria interdependencies relations for renewable energy and energy policy selection problems. Hence, the obtained computational results are compared with a fuzzy decision-making method from the recent literature based on some comparison parameters to show the advantages and constraints of the proposed approach. Finally, a sensitivity analysis is prepared to indicate effects of different criteria weights on ranking results to present the robustness or sensitiveness of the proposed soft computing approach versus the relative importance of criteria. - Highlights: • Introducing a novel interval-valued hesitant fuzzy compromise ranking method.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Le, Thanh; Altman, Tom; Gardiner, Katheleen

    2010-02-01

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

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

    Science.gov (United States)

    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.

  18. Agent-Based Hierarchical Approach For Executing Bag-Of-Tasks In Clouds

    Directory of Open Access Journals (Sweden)

    Włodzimierz Funika

    2014-01-01

    Full Text Available Numerous unrelated, independent (no inter-task communication tasks called “bag-oftasks”(BoTs compared with message passing applications can be highly parallelised andexecuted in any acceptable order. A common practice when executing bag-of-tasks applications(BoT is to exploit the master-slave topology. Cloud environments offer some featuresthat facilitate executing BoT applications. One of the approaches to control cloud resourcesis to use agents that can flexibly act in a dynamic environment. Given these assumptions wedesigned a combination of these approaches, which can be classified as: a distributed, hierarchicalsolution to the issue of scalable executing of bag-of-tasks. The concept of our systemrelates to a project that is focused on processing huge quantities of data incoming from anetwork of sensors by the Internet. Our aim is to create a mechanism for processing such dataas a system which executes jobs while exploiting load balancing for cloud resources using,e.g., Eucalyptus. The idea is to create a hybrid architecture which takes advantage of somecentralized parts of the system and full distributedness in other parts. On the other handwe balance dependencies between the system components using a hierarchic master-slavestructure.

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

    Science.gov (United States)

    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.

  20. Multiple target tracking by learning-based hierarchical association of detection responses.

    Science.gov (United States)

    Huang, Chang; Li, Yuan; Nevatia, Ramakant

    2013-04-01

    We propose a hierarchical association approach to multiple target tracking from a single camera by progressively linking detection responses into longer track fragments (i.e., tracklets). Given frame-by-frame detection results, a conservative dual-threshold method that only links very similar detection responses between consecutive frames is adopted to generate initial tracklets with minimum identity switches. Further association of these highly fragmented tracklets at each level of the hierarchy is formulated as a Maximum A Posteriori (MAP) problem that considers initialization, termination, and transition of tracklets as well as the possibility of them being false alarms, which can be efficiently computed by the Hungarian algorithm. The tracklet affinity model, which measures the likelihood of two tracklets belonging to the same target, is a linear combination of automatically learned weak nonparametric models upon various features, which is distinct from most of previous work that relies on heuristic selection of parametric models and manual tuning of their parameters. For this purpose, we develop a novel bag ranking method and train the crucial tracklet affinity models by the boosting algorithm. This bag ranking method utilizes the soft max function to relax the oversufficient objective function used by the conventional instance ranking method. It provides a tighter upper bound of empirical errors in distinguishing correct associations from the incorrect ones, and thus yields more accurate tracklet affinity models for the tracklet association problem. We apply this approach to the challenging multiple pedestrian tracking task. Systematic experiments conducted on two real-life datasets show that the proposed approach outperforms previous state-of-the-art algorithms in terms of tracking accuracy, in particular, considerably reducing fragmentations and identity switches.

  1. Negative Sequence Droop Method based Hierarchical Control for Low Voltage Ride-Through in Grid-Interactive Microgrids

    DEFF Research Database (Denmark)

    Zhao, Xin; Firoozabadi, Mehdi Savaghebi; Quintero, Juan Carlos Vasquez

    2015-01-01

    In highly microgrid (MG) integrated distribution systems, problems such as a sudden cut out of the MGs due to grid faults may lead to adverse effects to the grid. As a consequence, ancillary services provided by MGs are preferred since it can make the MG a contributor to ride through the faults....... In this paper, a voltage support strategy based on negative sequence droop control, which regulate the positive/negative sequence active and reactive power flow by means of sending proper voltage reference to the inner control loop, is proposed for the grid connected MGs to ride through voltage sags under...... complex line impedance conditions. In this case, the MGs should inject a certain amount of positive and negative sequence power to the grid so that the voltage quality at load side can be maintained at a satisfied level. A two layer hierarchical control strategy is proposed in this paper. The primary...

  2. A Comprehensive Decision-Making Approach Based on Hierarchical Attribute Model for Information Fusion Algorithms’ Performance Evaluation

    Directory of Open Access Journals (Sweden)

    Lianhui Li

    2014-01-01

    Full Text Available Aiming at the problem of fusion algorithm performance evaluation in multiradar information fusion system, firstly the hierarchical attribute model of track relevance performance evaluation model is established based on the structural model and functional model and quantization methods of evaluation indicators are given; secondly a combination weighting method is proposed to determine the weights of evaluation indicators, in which the objective and subjective weights are separately determined by criteria importance through intercriteria correlation (CRITIC and trapezoidal fuzzy scale analytic hierarchy process (AHP, and then experience factor is introduced to obtain the combination weight; at last the improved technique for order preference by similarity to ideal solution (TOPSIS replacing Euclidean distance with Kullback-Leibler divergence (KLD is used to sort the weighted indicator value of the evaluation object. An example is given to illustrate the correctness and feasibility of the proposed method.

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

    Science.gov (United States)

    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.

  4. A Spectral-Spatial Classification of Hyperspectral Images Based on the Algebraic Multigrid Method and Hierarchical Segmentation Algorithm

    Directory of Open Access Journals (Sweden)

    Haiwei Song

    2016-03-01

    Full Text Available The algebraic multigrid (AMG method is used to solve linear systems of equations on a series of progressively coarser grids and has recently attracted significant attention for image segmentation due to its high efficiency and robustness. In this paper, a novel spectral-spatial classification method for hyperspectral images based on the AMG method and hierarchical segmentation (HSEG algorithm is proposed. Our method consists of the following steps. First, the AMG method is applied to hyperspectral imagery to construct a multigrid structure of fine-to-coarse grids based on the anisotropic diffusion partial differential equation (PDE. The vertices in the multigrid structure are then considered as the initial seeds (markers for growing regions and are clustered to obtain a sequence of segmentation results. In the next step, a maximum vote decision rule is employed to combine the pixel-wise classification map and the segmentation maps. Finally, a final classification map is produced by choosing the optimal grid level to extract representative spectra. Experiments based on three different types of real hyperspectral datasets with different resolutions and contexts demonstrate that our method can obtain 3.84%–13.81% higher overall accuracies than the SVM classifier. The performance of our method was further compared to several marker-based spectral-spatial classification methods using objective quantitative measures and a visual qualitative evaluation.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Parvin Jeffrey

    2010-12-01

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

  7. Distributed and hierarchical object-based image analysis for damage assessment: a case study of 2008 Wenchuan earthquake, China

    Directory of Open Access Journals (Sweden)

    Jing Sun

    2016-11-01

    Full Text Available Object-based image analysis (OBIA is an emerging technique for analyzing remote sensing image based on object properties including spectral, geometry, contextual and texture information. To reduce the computational cost of this comprehensive OBIA and make it more feasible in disaster responses, we developed a unique approach – distributed and hierarchical OBIA approach for damage assessment. This study demonstrated a completed classification of YingXiu town, heavily devastated by the 2008 Wenchuan earthquake using Quickbrid imagery. Two distinctive areas, mountainous areas and urban, were analyzed separately. This approach does not require substantial processing power and large amounts of available memory because image of a large disaster-affected area was split in smaller pieces. Two or more computers could be used in parallel to process and analyze these sub-images based on different requirements. The approach can be applicable in other cases whereas the established set of rules can be adopted in similar study areas. More experiments will be carried out in future studies to prove its feasibility.

  8. Systems of Systems Modeled by a Hierarchical Part-Whole State-Based Formalism

    Directory of Open Access Journals (Sweden)

    Luca Pazzi

    2013-11-01

    Full Text Available The paper presents an explicit state-based modeling approach aimed at modeling Systems of Systems behavior. The approach allows to specify and verify incrementally safety and liveness rules without using model checking techniques. The state-based approach allows moreover to use the system behavior directly as an interface, greatly improving the effectiveness of the recursive composition needed when assembling Systems of Systems. Such systems are, at the same time, both parts and wholes, thus giving a formal characterization to the notion of Holon.

  9. Hierarchical species distribution models

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

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

  10. Hierarchical online appearance-based tracking for 3D head pose, eyebrows, lips, eyelids, and irises

    NARCIS (Netherlands)

    Orozco, Javier; Rudovic, Ognjen; Gonzalez Garcia, Jordi; Pantic, Maja

    In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can

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

    Science.gov (United States)

    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…

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

    Science.gov (United States)

    Eisank, C.; Dragut, L.

    2012-04-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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. © 2015 The International Union of Biochemistry and Molecular Biology.

  15. A Negative Selection Algorithm Based on Hierarchical Clustering of Self Set and its Application in Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Wen Chen

    2011-08-01

    Full Text Available A negative selection algorithm based on the hierarchical clustering of self set HC-RNSA is introduced in this paper. Several strategies are applied to improve the algorithm performance. First, the self data set is replaced by the self cluster centers to compare with the detector candidates in each cluster level. As the number of self clusters is much less than the self set size, the detector generation efficiency is improved. Second, during the detector generation process, the detector candidates are restricted to the lower coverage space to reduce detector redundancy. In the article, the problem that the distances between antigens coverage to a constant value in the high dimensional space is analyzed, accordingly the Principle Component Analysis (PCA method is used to reduce the data dimension, and the fractional distance function is employed to enhance the distinctiveness between the self and non-self antigens. The detector generation procedure is terminated when the expected non-self coverage is reached. The theory analysis and experimental results demonstrate that the detection rate of HC-RNSA is higher than that of the traditional negative selection algorithms while the false alarm rate and time cost are reduced.

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

    Science.gov (United States)

    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.

  17. Typing of unknown microorganisms based on quantitative analysis of fatty acids by mass spectrometry and hierarchical clustering

    Energy Technology Data Exchange (ETDEWEB)

    Li Tingting; Dai Ling; Li Lun; Hu Xuejiao; Dong Linjie; Li Jianjian; Salim, Sule Khalfan; Fu Jieying [Key Laboratory of Pesticides and Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, Hubei 430079 (China); Zhong Hongying, E-mail: hyzhong@mail.ccnu.edu.cn [Key Laboratory of Pesticides and Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, Hubei 430079 (China)

    2011-01-17

    Rapid identification of unknown microorganisms of clinical and agricultural importance is not only critical for accurate diagnosis of infections but also essential for appropriate and prompt treatment. We describe here a rapid method for microorganisms typing based on quantitative analysis of fatty acids by iFAT approach (Isotope-coded Fatty Acid Transmethylation). In this work, lyophilized cell lysates were directly mixed with 0.5 M NaOH solution in d3-methanol and n-hexane. After 1 min of ultrasonication, the top n-hexane layer was combined with a mixture of standard d0-methanol derived fatty acid methylesters with known concentration. Measurement of intensity ratios of d3/d0 labeled fragment ion and molecular ion pairs at the corresponding target fatty acids provides a quantitative basis for hierarchical clustering. In the resultant dendrogram, the Euclidean distance between unknown species and known species quantitatively reveals their differences or shared similarities in fatty acid related pathways. It is of particular interest to apply this method for typing fungal species because fungi has distinguished lipid biosynthetic pathways that have been targeted for lots of drugs or fungicides compared with bacteria and animals. The proposed method has no dependence on the availability of genome or proteome databases. Therefore, it is can be applicable for a broad range of unknown microorganisms or mutant species.

  18. Maximizing data holdings and data documentation with a hierarchical system for sample-based geochemical data

    Science.gov (United States)

    Hsu, L.; Lehnert, K. A.; Walker, J. D.; Chan, C.; Ash, J.; Johansson, A. K.; Rivera, T. A.

    2011-12-01

    Sample-based measurements in geochemistry are highly diverse, due to the large variety of sample types, measured properties, and idiosyncratic analytical procedures. In order to ensure the utility of sample-based data for re-use in research or education they must be associated with a high quality and quantity of descriptive, discipline-specific metadata. Without an adequate level of documentation, it is not possible to reproduce scientific results or have confidence in using the data for new research inquiries. The required detail in data documentation makes it challenging to aggregate large sets of data from different investigators and disciplines. One solution to this challenge is to build data systems with several tiers of intricacy, where the less detailed tiers are geared toward discovery and interoperability, and the more detailed tiers have higher value for data analysis. The Geoinformatics for Geochemistry (GfG) group, which is part of the Integrated Earth Data Applications facility (http://www.iedadata.org), has taken this approach to provide services for the discovery, access, and analysis of sample-based geochemical data for a diverse user community, ranging from the highly informed geochemist to non-domain scientists and undergraduate students. GfG builds and maintains three tiers in the sample based data systems, from a simple data catalog (Geochemical Resource Library), to a substantially richer data model for the EarthChem Portal (EarthChem XML), and finally to detailed discipline-specific data models for petrologic (PetDB), sedimentary (SedDB), hydrothermal spring (VentDB), and geochronological (GeoChron) samples. The data catalog, the lowest level in the hierarchy, contains the sample data values plus metadata only about the dataset itself (Dublin Core metadata such as dataset title and author), and therefore can accommodate the widest diversity of data holdings. The second level includes measured data values from the sample, basic information

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

    DEFF Research Database (Denmark)

    Marzband, Mousa; Parhizi, Narges; Savaghebi, Mehdi

    2016-01-01

    are treated as uncertainties in the proposed structure. In order to handle the uncertainties, Taguchi0s orthogonal array testing-TOAT approach is utilized. Then, the shortage or surplus of the MGs power should be submitted to a central EMS-CEMS in the secondary-level. In order to validate the proposed control...... structure, a test system is simulated and optimized based on multi-period imperialist competition algorithm- MICA. The obtained results clearly show that the proposed BLCS is effective in achieving optimal dispatch of generation resources in systems with multiple MGs....

  20. Probabilistic Path and Data Capacity Based Handover Decision for Hierarchical Macro- and Femtocell Networks

    Directory of Open Access Journals (Sweden)

    Jae-Wook Lee

    2016-01-01

    Full Text Available Femtocells are considered a technology to improve performance of a network by increasing network coverage and communication capacity at a relatively low cost. However, if there are a lot of femtocells in a macrocell, the number of handovers greatly increases, and unnecessary handovers can occur from the mobile station temporarily passing through a femtocell. In this paper, we propose a method that probabilistically estimates the path in a femtocell and makes a handover decision based on the available data capacity of a mobile station on the estimated path. Simulation results show that the proposed method effectively reduces the number of unnecessary handovers while improving the data rate and capacity.

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

    Science.gov (United States)

    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. Modeling and Sensitivity Study of Consensus Algorithm-Based Distributed Hierarchical Control for DC Microgrids

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Roldan Perez, Javier

    2016-01-01

    in the communication network, continuous-time methods can be inaccurate for this kind of dynamic study. Therefore, this paper aims at modeling a complete DC MG using a discrete-time approach in order to perform a sensitivity analysis taking into account the effects of the consensus algorithm. To this end......Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes...... a challenging issue when these kinds of algorithms are used, since the dynamics of the electrical and the communication systems interact with each other. Moreover, the transmission rate and topology of the communication network also affect the system dynamics. Due to discrete nature of the information exchange...

  3. Monte-Carlo-based uncertainty propagation with hierarchical models—a case study in dynamic torque

    Science.gov (United States)

    Klaus, Leonard; Eichstädt, Sascha

    2018-04-01

    For a dynamic calibration, a torque transducer is described by a mechanical model, and the corresponding model parameters are to be identified from measurement data. A measuring device for the primary calibration of dynamic torque, and a corresponding model-based calibration approach, have recently been developed at PTB. The complete mechanical model of the calibration set-up is very complex, and involves several calibration steps—making a straightforward implementation of a Monte Carlo uncertainty evaluation tedious. With this in mind, we here propose to separate the complete model into sub-models, with each sub-model being treated with individual experiments and analysis. The uncertainty evaluation for the overall model then has to combine the information from the sub-models in line with Supplement 2 of the Guide to the Expression of Uncertainty in Measurement. In this contribution, we demonstrate how to carry this out using the Monte Carlo method. The uncertainty evaluation involves various input quantities of different origin and the solution of a numerical optimisation problem.

  4. Robust ellipse detection based on hierarchical image pyramid and Hough transform.

    Science.gov (United States)

    Chien, Chung-Fang; Cheng, Yu-Che; Lin, Ta-Te

    2011-04-01

    In this research we propose a fast and robust ellipse detection algorithm based on a multipass Hough transform and an image pyramid data structure. The algorithm starts with an exhaustive search on a low-resolution image in the image pyramid using elliptical Hough transform. Then the image resolution is iteratively increased while the candidate ellipses with higher resolution are updated at each step until the original image resolution is reached. After removing the detected ellipses, the Hough transform is repeatedly applied in multiple passes to search for remaining ellipses, and terminates when no more ellipses are found. This approach significantly reduces the false positive error of ellipse detection as compared with the conventional randomized Hough transform method. The analysis shows that the computing complexity of this algorithm is Θ(n(5/2)), and thus the computation time and memory requirement are significantly reduced. The developed algorithm was tested with images containing various numbers of ellipses. The effects of noise-to-signal ratio combined with various ellipse sizes on the detection accuracy were analyzed and discussed. Experimental results revealed that the algorithm is robust to noise. The average detection accuracies were all above 90% for images with less than seven ellipses, and slightly decreased to about 80% for images with more ellipses. The average false positive error was less than 2%. © 2011 Optical Society of America

  5. Enabling Sustainability: Hierarchical Need-Based Framework for Promoting Sustainable Data Infrastructure in Developing Countries

    Directory of Open Access Journals (Sweden)

    David O. Yawson

    2009-11-01

    Full Text Available The paper presents thoughts on Sustainable Data Infrastructure (SDI development, and its user requirements bases. It brings Maslow's motivational theory to the fore, and proposes it as a rationalization mechanism for entities (mostly governmental that aim at realizing SDI. Maslow's theory, though well-known, is somewhat new in geospatial circles; this is where the novelty of the paper resides. SDI has been shown to enable and aid development in diverse ways. However, stimulating developing countries to appreciate the utility of SDI, implement, and use SDI in achieving sustainable development has proven to be an imposing challenge. One of the key reasons for this could be the absence of a widely accepted psychological theory to drive needs assessment and intervention design for the purpose of SDI development. As a result, it is reasonable to explore Maslow’s theory of human motivation as a psychological theory for promoting SDI in developing countries. In this article, we review and adapt Maslow’s hierarchy of needs as a framework for the assessment of the needs of developing nations. The paper concludes with the implications of this framework for policy with the view to stimulating the implementation of SDI in developing nations.

  6. Hierarchical Modeling of Mastic Asphalt in Layered Road Structures Based on the Mori-Tanaka Method

    Directory of Open Access Journals (Sweden)

    Richard Valenta

    2012-01-01

    Full Text Available We present an application of the Mori-Tanaka micromechanical model for a description of the highly nonlinear behavior of asphalt mixtures. This method is expected to replace an expensive finite element-based fully-coupled multi-scale analysis while still providing useful information about local fields on the meso-scale that are not predictable by strictly macroscopic simulations. Drawing on our recent results from extensive experimental and also numerical investigations this paper concentrates on principal limitations of the Mori-Tanaka method, typical of all two-point averaging schemes, when appliedto material systems prone to evolving highly localized deformation patterns such as a network of shear bands. The inability of the Mori-Tanaka method to properly capture the correct stress transfer between phases with increasing compliance of the matrix phase is remedied here by introducing a damage like parameter into the local constitutive equation of reinforcements (stones to control an amount of stress taken by this phase. A deficiency of the Mori-Tanaka method in the prediction of creep response is also mentioned particularly in the light of large scale simulations. A comparison with the application of macroscopic homogenized constitutive model for an asphalt mixture is also presented.

  7. QoSS Hierarchical NoC-Based Architecture for MPSoC Dynamic Protection

    Directory of Open Access Journals (Sweden)

    Johanna Sepulveda

    2012-01-01

    Full Text Available As electronic systems are pervading our lives, MPSoC (multiprocessor system-on-chip security is becoming an important requirement. MPSoCs are able to support multiple applications on the same chip. The challenge is to provide MPSoC security that makes possible a trustworthy system that meets the performance and security requirements of all the applications. The network-on-chip (NoC can be used to efficiently incorporate security. Our work proposes the implementation of QoSS (quality of security service to overcome present MPSoC vulnerabilities. QoSS is a novel concept for data protection that introduces security as a dimension of QoS. QoSS takes advantage of the NoC wide system visibility and critical role in enabling system operation, exploiting the NoC components to detect and prevent a wide range of attacks. In this paper, we present the implementation of a layered dynamic security NoC architecture that integrates agile and dynamic security firewalls in order to detect attacks based on different security rules. We evaluate the effectiveness of our approach over several MPSoCs scenarios and estimate their impact on the overall performance. We show that our architecture can perform a fast detection of a wide range of attacks and a fast configuration of different security policies for several MPSoC applications.

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

    Directory of Open Access Journals (Sweden)

    Hui-Jan Lin

    2012-06-01

    Full Text Available 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(OH6 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.

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

    Science.gov (United States)

    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. An RM-ODP Based Ontology and a CAD Tool for Modeling Hierarchical Systems in Enterprise Architecture

    OpenAIRE

    Lê, Lam Son; Wegmann, Alain

    2005-01-01

    Enterprise Architecture (EA) requires modeling enterprises across multiple levels (from markets down to IT systems) i.e. modeling hierarchical systems. Our goal is to build a Computer Aided Design (CAD) tool for EA. To be able to build this CAD tool, we need an ontology that can be used to describe hierarchical systems. The Reference Model of Open Distributed Processing (RM-ODP) was originally defined for describing IT systems and their environment. RM-ODP can also be suited to general, hier...

  11. Hierarchical architecture of active knits

    International Nuclear Information System (INIS)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-01-01

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

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

    Science.gov (United States)

    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…

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

    Directory of Open Access Journals (Sweden)

    R. Silva-Ortigoza

    2014-01-01

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

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

    Science.gov (United States)

    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. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  15. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

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

    2014-01-01

    Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non......-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Salvador Dura-Bernal

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

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

    Science.gov (United States)

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

    2012-01-01

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

  19. Two-step growth mechanism of supported Co3O4-based sea-urchin like hierarchical nanostructures

    Science.gov (United States)

    Maurizio, Chiara; Edla, Raju; Michieli, Niccolo'; Orlandi, Michele; Trapananti, Angela; Mattei, Giovanni; Miotello, Antonio

    2018-05-01

    Supported 3D hierarchical nanostructures of transition metal oxides exhibit enhanced photocatalytic performances and long-term stability under working conditions. The growth mechanisms crucially determine their intimate structure, that is a key element to optimize their properties. We report on the formation mechanism of supported Co3O4 hierarchical sea urchin-like nanostructured catalyst, starting from Co-O-B layers deposited by Pulsed Laser Deposition (PLD). The particles deposited on the layer surface, that constitute the seeds for the urchin formation, have been investigated after separation from the underneath deposited layer, by X-ray diffraction, X-ray absorption spectroscopy and scanning electron microscopy. The comparison with PLD deposited layers without O and/or B indicates a crucial role of B for the urchin formation that (i) limits Co oxidation during the deposition process and (ii) induces a chemical reduction of Co, especially in the particle core, in the first step of air annealing (2 h, 500 °C). After 2 h heating Co oxidation proceeds and Co atoms outdiffuse from the Co fcc particle core likely through fast diffusion channel present in the shell and form Co3O4 nano-needles. The growth of nano-needles from the layer beneath the particles is prevented by a faster Co oxidation and a minimum fraction of metallic Co. This investigation shows how diffusion mechanisms and chemical effects can be effectively coupled to obtain hierarchical structures of transition metal oxides.

  20. A Bayesian Hierarchical Model for Glacial Dynamics Based on the Shallow Ice Approximation and its Evaluation Using Analytical Solutions

    Science.gov (United States)

    Gopalan, Giri; Hrafnkelsson, Birgir; Aðalgeirsdóttir, Guðfinna; Jarosch, Alexander H.; Pálsson, Finnur

    2018-03-01

    Bayesian hierarchical modeling can assist the study of glacial dynamics and ice flow properties. This approach will allow glaciologists to make fully probabilistic predictions for the thickness of a glacier at unobserved spatio-temporal coordinates, and it will also allow for the derivation of posterior probability distributions for key physical parameters such as ice viscosity and basal sliding. The goal of this paper is to develop a proof of concept for a Bayesian hierarchical model constructed, which uses exact analytical solutions for the shallow ice approximation (SIA) introduced by Bueler et al. (2005). A suite of test simulations utilizing these exact solutions suggests that this approach is able to adequately model numerical errors and produce useful physical parameter posterior distributions and predictions. A byproduct of the development of the Bayesian hierarchical model is the derivation of a novel finite difference method for solving the SIA partial differential equation (PDE). An additional novelty of this work is the correction of numerical errors induced through a numerical solution using a statistical model. This error correcting process models numerical errors that accumulate forward in time and spatial variation of numerical errors between the dome, interior, and margin of a glacier.

  1. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

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

    2017-01-01

    Purpose This paper aims to present that deliberate change is strongly associated with formal structures and top-down influence. Hierarchical configurations have been used to structure processes, overcome resistance and get things done. But is deliberate change also possible without formal...... reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  2. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    In this paper, we present trapping issues of weight-dependent walks on weighted hierarchical networks which are based on the classic scale-free hierarchical networks. Assuming that edge's weight is used as local information by a random walker, we introduce a biased walk. The biased walk is that a walker, at each step, ...

  3. Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework

    International Nuclear Information System (INIS)

    Rezaei, Navid; Kalantar, Mohsen

    2015-01-01

    Highlights: • Detailed formulation of the microgrid static and dynamic securities based on droop control and virtual inertia concepts. • Constructing a novel objective function using frequency excursion and rate of change of frequency profiles. • Ensuring the microgrid security subject to the microgrid economic and environmental policies. • Coordinated management of demand response and droop controlled distributed generation resources. • Precise scheduling of day-ahead hierarchical frequency control ancillary services using a scenario based stochastic programming. - Abstract: Low inertia stack, high penetration levels of renewable energy source and great ratio of power deviations in a small power delivery system put microgrid frequency at risk of instability. On the basis of the close coupling between the microgrid frequency and system security requirements, procurement of adequate ancillary services from cost-effective and environmental friendly resources is a great challenge requests an efficient energy management system. Motivated by this need, this paper presents a novel energy management system that is aimed to coordinately manage the demand response and distributed generation resources. The proposed approach is carried out by constructing a hierarchical frequency control structure in which the frequency dependent control functions of the microgrid components are modeled comprehensively. On the basis of the derived modeling, both the static and dynamic frequency securities of an islanded microgrid are provided in primary and secondary control levels. Besides, to cope with the low inertia stack of islanded microgrids, novel virtual inertia concept is devised based on the precise modeling of droop controlled distributed generation resources. The proposed approach is applied to typical test microgrid. Energy and hierarchical reserve resource are scheduled precisely using a scenario-based stochastic programming methodology. Moreover, analyzing the

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

    Science.gov (United States)

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

    2016-09-30

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

  5. Unsupervised SAR Image Segmentation Based on a Hierarchical TMF Model in the Discrete Wavelet Domain for Sea Area Detection

    Directory of Open Access Journals (Sweden)

    Jiajing Wang

    2014-01-01

    Full Text Available Unsupervised synthetic aperture radar (SAR image segmentation is a fundamental preliminary processing step required for sea area detection in military applications. The purpose of this step is to classify large image areas into different segments to assist with identification of the sea area and the ship target within the image. The recently proposed triplet Markov field (TMF model has been successfully used for segmentation of nonstationary SAR images. This letter presents a hierarchical TMF model in the discrete wavelet domain of unsupervised SAR image segmentation for sea area detection, which we have named the wavelet hierarchical TMF (WHTMF model. The WHTMF model can precisely capture the global and local image characteristics in the two-pass computation of posterior distribution. The multiscale likelihood and the multiscale energy function are constructed to capture the intrascale and intrascale dependencies in a random field (X,U. To model the SAR data related to radar backscattering sources, the Gaussian distribution is utilized. The effectiveness of the proposed model for SAR image segmentation is evaluated using synthesized and real SAR data.

  6. Hierarchically Three-Dimensional Nanofiber Based Textile with High Conductivity and Biocompatibility As a Microbial Fuel Cell Anode.

    Science.gov (United States)

    Tao, Yifei; Liu, Qiongzhen; Chen, Jiahui; Wang, Bo; Wang, Yuedan; Liu, Ke; Li, Mufang; Jiang, Haiqing; Lu, Zhentan; Wang, Dong

    2016-07-19

    Microbial fuel cells (MFCs) encompass complex bioelectrocatalytic reactions that converting chemical energy of organic compounds to electrical energy. Improving the anode configuration is thought to be a critical step for enhancing MFCs performance. In present study, a hierarchically structured textile polypyrrole/poly(vinyl alcohol-co-polyethylene) nanofibers/poly(ethylene terephthalate) (referred to PPy/NFs/PET) is shown to be excellent anode for MFCs. This hierarchical PPy/NFs/PET anode affords an open porous and three-dimensional interconnecting conductive scaffold with larger surface roughness, facilitating microbial colonization and electron transfer from exoelectrogens to the anode. The mediator-less MFC equipped with PPy/NFs/PET anode achieves a remarkable maximum power density of 2420 mW m(-2) with Escherichia coli as the microbial catalyst at the current density of 5500 mA m(-2), which is approximately 17 times higher compared to a reference anode PPy/PET (144 mW m(-2)). Considering the low cost, low weight, facile fabrication, and good winding, this PPy/NFs/PET textile anode promises a great potential for high-performance and cost-effective MFCs in a large scale.

  7. A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2017-01-01

    Full Text Available A large number of studies demonstrated that major depressive disorder (MDD is characterized by the alterations in brain functional connections which is also identifiable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

  8. 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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Woosang Lim

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

  10. Inequality contrained hierarchical models

    NARCIS (Netherlands)

    Kato, B.S.

    2005-01-01

    In multilevel research, the data structure in the population is hierarchical, and the sample data are viewed as a multistage sample from this hierarchical population. For instance in educational research, the population consists of schools and pupils within these schools. In this scenario, pupils

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

    KAUST Repository

    Chavez, Gustavo Ivan

    2017-07-10

    This dissertation introduces a novel fast direct solver and preconditioner for the solution of block tridiagonal linear systems that arise from the discretization of elliptic partial differential equations on a Cartesian product mesh, such as the variable-coefficient Poisson equation, the convection-diffusion equation, and the wave Helmholtz equation in heterogeneous media. The algorithm extends the traditional cyclic reduction method with hierarchical matrix techniques. The resulting method exposes substantial concurrency, and its arithmetic operations and memory consumption grow only log-linearly with problem size, assuming bounded rank of off-diagonal matrix blocks, even for problems with arbitrary coefficient structure. The method can be used as a standalone direct solver with tunable accuracy, or as a black-box preconditioner in conjunction with Krylov methods. The challenges that distinguish this work from other thrusts in this active field are the hybrid distributed-shared parallelism that can demonstrate the algorithm at large-scale, full three-dimensionality, and the three stressors of the current state-of-the-art multigrid technology: high wavenumber Helmholtz (indefiniteness), high Reynolds convection (nonsymmetry), and high contrast diffusion (inhomogeneity). Numerical experiments corroborate the robustness, accuracy, and complexity claims and provide a baseline of the performance and memory footprint by comparisons with competing approaches such as the multigrid solver hypre, and the STRUMPACK implementation of the multifrontal factorization with hierarchically semi-separable matrices. The companion implementation can utilize many thousands of cores of Shaheen, KAUST\\'s Haswell-based Cray XC-40 supercomputer, and compares favorably with other implementations of hierarchical solvers in terms of time-to-solution and memory consumption.

  12. A method for identifying hierarchical sub-networks / modules and weighting network links based on their similarity in sub-network / module affiliation

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-06-01

    Full Text Available Some networks, including biological networks, consist of hierarchical sub-networks / modules. Based on my previous study, in present study a method for both identifying hierarchical sub-networks / modules and weighting network links is proposed. It is based on the cluster analysis in which between-node similarity in sets of adjacency nodes is used. Two matrices, linkWeightMat and linkClusterIDs, are achieved by using the algorithm. Two links with both the same weight in linkWeightMat and the same cluster ID in linkClusterIDs belong to the same sub-network / module. Two links with the same weight in linkWeightMat but different cluster IDs in linkClusterIDs belong to two sub-networks / modules at the same hirarchical level. However, a link with an unique cluster ID in linkClusterIDs does not belong to any sub-networks / modules. A sub-network / module of the greater weight is the more connected sub-network / modules. Matlab codes of the algorithm are presented.

  13. Client perception of therapeutic factors in group psychotherapy and growth groups: an empirically-based hierarchical model.

    Science.gov (United States)

    Dierick, Paul; Lietaer, Germain

    2008-04-01

    To assess group participants' perceptions of therapeutic factors, we developed an extensive questionnaire of 155 items that was administered to 489 members of 78 psychotherapy and growth groups of client-centered/experiential, psychoanalytic, behavioral, Gestalt and drama- and bodily oriented orientations. Using multivariate analyses we found a model that reveals the structure and connections of therapeutic factors as they are differentiated in the experience of the group members. Our model encompasses three hierarchical levels of abstraction: 28 Basic scales that appeared to be structured into seven main scales (Group Cohesion, Interactional Confirmation, Cathartic Self-Revelation, Self-Insight and Progress, Observational Experiences, Getting Directives, and Interactional Confrontation) and two dimensions (Relational Climate and Psychological Work). Validity for these therapeutic factors was found in their grounded content, statistically analyzed constructs, importance ratings, and correlations to intermediate outcome measures.

  14. Studying plasmonic resonance modes of hierarchical self-assembled meta-atoms based on their transfer matrix

    Science.gov (United States)

    Suryadharma, Radius N. S.; Fruhnert, Martin; Fernandez-Corbaton, Ivan; Rockstuhl, Carsten

    2017-07-01

    Hierarchical self-assembled meta-atoms are made from a larger number of suitably arranged metallic nanoparticles. They constitute the basic building blocks for isotropic metamaterials. The properties of these meta-atoms are usually studied upon illumination with a plane wave and by analyzing the multipolar composition of the scattered field. This, however, does not always provide full information. The coupling between multiple meta-atoms is usually not considered, and a physical understanding for the cause of the response is often incomplete. Here we overcome these limitations by performing a spectral eigenvalue analysis of the transfer matrix of isolated and coupled self-assembled meta-atoms. Emphasis is put on using a transfer-matrix formulation in either a local or a global coordinate frame. We show that for the magnetic resonance, coupling to nearest neighbors is weak, suggesting the possibility to preserve the response of the isolated meta-atom upon tight packaging in a metamaterial.

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

    Science.gov (United States)

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

    Directory of Open Access Journals (Sweden)

    Xiao Sun

    2015-10-01

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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Junyu Zhang

    2017-11-01

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

  19. Hierarchical quantum communication

    International Nuclear Information System (INIS)

    Shukla, Chitra; Pathak, Anirban

    2013-01-01

    A general approach to study the hierarchical quantum information splitting (HQIS) is proposed and the same is used to systematically investigate the possibility of realizing HQIS using different classes of 4-qubit entangled states that are not connected by stochastic local operations and classical communication (SLOCC). Explicit examples of HQIS using 4-qubit cluster state and 4-qubit |Ω〉 state are provided. Further, the proposed HQIS scheme is generalized to introduce two new aspects of hierarchical quantum communication. To be precise, schemes of probabilistic hierarchical quantum information splitting and hierarchical quantum secret sharing are obtained by modifying the proposed HQIS scheme. A number of practical situations where hierarchical quantum communication would be of use, are also presented.

  20. Hierarchical Estimation as Basis for Hierarchical Forecasting

    NARCIS (Netherlands)

    Strijbosch, L.W.G.; Heuts, R.M.J.; Moors, J.J.A.

    2006-01-01

    In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items.Since HF is a complicated procedure, analytical results are hard to obtain;

  1. Hierarchical energy management system for stand-alone hybrid system based on generation costs and cascade control

    International Nuclear Information System (INIS)

    Torreglosa, J.P.; García, P.; Fernández, L.M.; Jurado, F.

    2014-01-01

    Highlights: • We present an energy management system for a stand-alone WT/PV/hydrogen/battery hybrid system. • Hierarchical control composed by master and slave control strategies. • Control assures reliable electricity support for stand-alone applications subject to technical and economic criteria. - Abstract: This paper presents an energy management system (EMS) for stand-alone hybrid systems composed by photovoltaic (PV) solar panels and a wind turbine (WT) as primary energy sources and two energy storage systems, which are a hydrogen system and a battery. The hydrogen system is composed of fuel cell (FC), electrolyzer and hydrogen storage tank. The EMS is a hierarchical control composed by a master control strategy and a slave control strategy. On the one hand, the master control generates the reference powers to meet several premises (such as to satisfy the load power demand, and to maintain the hydrogen tank level and the state of charge (SOC) of the battery between their target margins), taking also into account economic aspects to discriminate between using the battery or hydrogen system. On the other hand, the slave control modifies the reference powers generated by the master control according to the energy sources dynamic limitations, and maintains the DC bus voltage at its reference value. The models, implemented in MATLAB-Simulink environment, have been developed from commercially available components. To check the viability of the proposed EMS, two kinds of simulations were carried out: (1) A long-term simulation of 25 years (expected lifetime of the system) with a sample time of one hour to validate the master control of the EMS; and (2) A short-term simulation with sudden net power variations to validate the slave control of the EMS

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

    Science.gov (United States)

    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…

  3. Long-Life Lithium-Sulfur Battery Derived from Nori-Based Nitrogen and Oxygen Dual-Doped 3D Hierarchical Biochar.

    Science.gov (United States)

    Wu, Xian; Fan, Lishuang; Wang, Maoxu; Cheng, Junhan; Wu, Hexian; Guan, Bin; Zhang, Naiqing; Sun, Kening

    2017-06-07

    Due to restrictions on the low conductivity of sulfur and soluble polysulfides during discharge, lithium sulfur batteries are unsuitable for further large scale applications. The current carbon based cathodes suffer from poor cycle stability and high cost. Recently, heteroatom doped carbons have been considered as a settlement to enhance the performance of lithium sulfur batteries. With this strategy, we report the low cost activated nori based N,O-doped 3D hierarchical carbon material (ANC) as a sulfur host. The N,O dual-doped ANC reveals an elevated electrochemical performance, which exhibits not only a good rate performance over 5 C, but also a high sulfur content of 81.2%. Further importantly, the ANC represents an excellent cycling stability, the cathode reserves a capacity of 618 mAh/g at 2 C after 1000 cycles, which shows a 0.022% capacity decay per cycle.

  4. Interpreting Hierarchical Linear and Hierarchical Generalized Linear Models with Slopes as Outcomes

    Science.gov (United States)

    Tate, Richard

    2004-01-01

    Current descriptions of results from hierarchical linear models (HLM) and hierarchical generalized linear models (HGLM), usually based only on interpretations of individual model parameters, are incomplete in the presence of statistically significant and practically important "slopes as outcomes" terms in the models. For complete description of…

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

    Science.gov (United States)

    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.

  6. Micro- and nanophase separations in hierarchical self-assembly of strongly amphiphilic block copolymer-based ionic supramolecules

    DEFF Research Database (Denmark)

    Ayoubi, Mehran Asad; Zhu, Kaizheng; Nyström, Bo

    2013-01-01

    By a selective complexation between different alkyltrimethylammonium amphiphiles (C8, C12 and C16) and three different diblock copolymer systems of poly(styrene)-b-poly(methacrylic acid) at various grafting densities X (X = number of alkyl chains per acidic group of the poly(methacrylic acid) PMAA...... block), a class of ionic supramolecules are successfully synthesized whose molecular architecture consists of a poly(styrene) PS block (Linear block) covalently connected to a strongly amphiphilic comb-like block (AmphComb block), i.e. Linear-b-AmphComb. In the melt state, these ionic supramolecules can...... show simultaneous microphase (between Linear and AmphComb blocks) and nanophase (within the AmphComb blocks) separations. This leads to the formation of various structure-in-structure two-scale hierarchical self-assemblies, including S-in-SLL, S-in-SBCC, S-in-C, S-in-L and C-in-L, where S, SLL, SBCC, C...

  7. Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

    Science.gov (United States)

    Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

    2015-08-01

    In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

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

    Science.gov (United States)

    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.

  9. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

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

  10. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

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

  11. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

  12. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

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

  13. Hierarchical multifunctional nanocomposites

    Science.gov (United States)

    Ghasemi-Nejhad, Mehrdad N.

    2014-03-01

    Nanocomposites; including nano-materials such as nano-particles, nanoclays, nanofibers, nanotubes, and nanosheets; are of significant importance in the rapidly developing field of nanotechnology. Due to the nanometer size of these inclusions, their physicochemical characteristics differ significantly from those of micron size and bulk materials. The field of nanocomposites involves the study of multiphase materials where at least one of the constituent phases has one dimension less than 100 nm. This is the range where the phenomena associated with the atomic and molecular interaction strongly influence the macroscopic properties of materials. Since the building blocks of nanocomposites are at nanoscale, they have an enormous surface area with numerous interfaces between the two intermix phases. The special properties of the nano-composite arise from the interaction of its phases at the interface and/or interphase regions. By contrast, in a conventional composite based on micrometer sized filler such as carbon fibers, the interfaces between the filler and matrix constitutes have a much smaller surface-to-volume fraction of the bulk materials, and hence influence the properties of the host structure to a much smaller extent. The optimum amount of nanomaterials in the nanocomposites depends on the filler size, shape, homogeneity of particles distribution, and the interfacial bonding properties between the fillers and matrix. The promise of nanocomposites lies in their multifunctionality, i.e., the possibility of realizing unique combination of properties unachievable with traditional materials. The challenges in reaching this promise are tremendous. They include control over the distribution in size and dispersion of the nanosize constituents, and tailoring and understanding the role of interfaces between structurally or chemically dissimilar phases on bulk properties. While the properties of the matrix can be improved by the inclusions of nanomaterials, the

  14. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  15. Effective implementation of hierarchical clustering

    Science.gov (United States)

    Verma, Mudita; Vijayarajan, V.; Sivashanmugam, G.; Bessie Amali, D. Geraldine

    2017-11-01

    Hierarchical clustering is generally used for cluster analysis in which we build up a hierarchy of clusters. In order to find that which cluster should be split a large amount of observations are being carried out. Here the data set of US based personalities has been considered for clustering. After implementation of hierarchical clustering on the data set we group it in three different clusters one is of politician, sports person and musicians. Training set is the main parameter which decides the category which has to be assigned to the observations that are being collected. The category of these observations must be known. Recognition comes from the formulation of classification. Supervised learning has the main instance in the form of classification. While on the other hand Clustering is an instance of unsupervised procedure. Clustering consists of grouping of data that have similar properties which are either their own or are inherited from some other sources.

  16. Extended Truncated Hierarchical Catmull-Clark Subdivision

    Science.gov (United States)

    2015-05-08

    number of degrees of freedom and reduced continuity (C1 for cubic splines ). THCCS, on the other hand, addresses both local refinement and arbitrary...Catmull-Clark subdivision is a popular quadrilateral-based subdivision scheme that is generalized from mid-knot insertion of bi- cubic B- splines to...hierarchical B- splines [14, 11, 25, 2]. For cubic hierarchical B- splines and Catmull-Clark subdivision, however, such basis-function-refinement needs

  17. Hierarchical screening for multiple mental disorders.

    Science.gov (United States)

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

    2013-10-01

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

  18. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    Science.gov (United States)

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-01-01

    Three-dimensional (3D) porous ZnO–CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO–CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO–CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO–CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM−1cm−2, the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior. PMID:25488502

  19. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

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

    1993-07-01

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

  20. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

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

    2017-01-01

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

  1. Hierarchical ordering of reticular networks.

    Directory of Open Access Journals (Sweden)

    Yuriy Mileyko

    Full Text Available The structure of hierarchical networks in biological and physical systems has long been characterized using the Horton-Strahler ordering scheme. The scheme assigns an integer order to each edge in the network based on the topology of branching such that the order increases from distal parts of the network (e.g., mountain streams or capillaries to the "root" of the network (e.g., the river outlet or the aorta. However, Horton-Strahler ordering cannot be applied to networks with loops because they they create a contradiction in the edge ordering in terms of which edge precedes another in the hierarchy. Here, we present a generalization of the Horton-Strahler order to weighted planar reticular networks, where weights are assumed to correlate with the importance of network edges, e.g., weights estimated from edge widths may correlate to flow capacity. Our method assigns hierarchical levels not only to edges of the network, but also to its loops, and classifies the edges into reticular edges, which are responsible for loop formation, and tree edges. In addition, we perform a detailed and rigorous theoretical analysis of the sensitivity of the hierarchical levels to weight perturbations. In doing so, we show that the ordering of the reticular edges is more robust to noise in weight estimation than is the ordering of the tree edges. We discuss applications of this generalized Horton-Strahler ordering to the study of leaf venation and other biological networks.

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

    Science.gov (United States)

    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

  3. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-07

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

  4. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

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

    2011-01-01

    zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  5. The Hierarchical Perspective

    Directory of Open Access Journals (Sweden)

    Daniel Sofron

    2015-05-01

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

  6. Hierarchical models and functional traits

    NARCIS (Netherlands)

    van Loon, E.E.; Shamoun-Baranes, J.; Sierdsema, H.; Bouten, W.; Cramer, W.; Badeck, F.; Krukenberg, B.; Klotz, S.; Kühn, I.; Schweiger, O.; Böhning-Gaese, K.; Schaefer, H.-C.; Kissling, D.; Brandl, R.; Brändle, M.; Fricke, R.; Leuschner, C.; Buschmann, H.; Köckermann, B.; Rose, L.

    2006-01-01

    Hierarchical models for animal abundance prediction are conceptually elegant. They are generally more parsimonous than non-hierarchical models derived from the same data, give relatively robust predictions and automatically provide consistent output at multiple (spatio-temporal) scales. Another

  7. Solid state nanofibers based on self-assemblies : from cleaving from self-assemblies to multilevel hierarchical constructs

    NARCIS (Netherlands)

    Ikkala, Olli; Ras, Robin H. A.; Houbenov, Nikolay; Ruokolainen, Janne; Paakko, Marjo; Laine, Janne; Leskela, Markku; Berglund, Lars A.; Lindstrom, Tom; ten Brinke, Gerrit; Iatrou, Hermis; Hadjichristidis, Nikos; Faul, Charl F. J.; Pääkkö, Marjo; Leskelä, Markku; Lindström, Tom

    2009-01-01

    Self-assemblies and their hierarchies are useful to construct soft materials with structures at different length scales and to tune the materials properties for various functions. Here we address routes for solid nanofibers based on different forms of self-assemblies. On the other hand, we discuss

  8. Design and implementation of a prototype graphical environment for (IMS/VS) hierarchical data-base application development (HIDAD)

    Energy Technology Data Exchange (ETDEWEB)

    Gopalakrishnan, T.

    1987-01-01

    In order to alleviate the existing software crisis, data-base application developers require a revolutionary approach for developing their applications. A graphical environment is suggested for this purpose. This dissertation describes and demonstrates a design and implementation of a prototype graphical environment for hierarchy data-base application development (HIDAD). The HIDAD graphical environment is composed of a graphic tool box, a graphic language, a graphic editor, a macro generator, and an application organizer. The graphic tool box contains a set of tools for generating the vocabulary of HIDAD graphic language. The graphic language is designed for representing data base applications. The microcomputer-based graphic editor is used to input and maintain the graphical representation of the system. This can generate intermediate code from graphical specifications. The macro generator uses the intermediate code in the mainframe computer and produces macros in COBOL, IMS, JCL and WYLBUR from primitive templates. The application organizer organizes the above macros from the respective libraries into an executable application program.

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

    Science.gov (United States)

    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.…

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

    Directory of Open Access Journals (Sweden)

    Dahou Yang

    2016-11-01

    Full Text Available 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.

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

    OpenAIRE

    Gao, Xin; Wang, Yifan; Sun, Hanxu; Jia, Qingxuan; Chen, Gang; Du, Mingtao; Yang, Yukun

    2016-01-01

    In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on th...

  12. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  13. 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.

    Science.gov (United States)

    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.

  14. 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

    International Nuclear Information System (INIS)

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

    2014-01-01

    We report new global minimum candidate structures for the (H 2 O) 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 2 O) 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

  15. Suitability Evaluation of Specific Shallow Geothermal Technologies Using a GIS-Based Multi Criteria Decision Analysis Implementing the Analytic Hierarchic Process

    Directory of Open Access Journals (Sweden)

    Francesco Tinti

    2018-02-01

    Full Text Available The exploitation potential of shallow geothermal energy is usually defined in terms of site-specific ground thermal characteristics. While true, this assumption limits the complexity of the analysis, since feasibility studies involve many other components that must be taken into account when calculating the effective market viability of a geothermal technology or the economic value of a shallow geothermal project. In addition, the results of a feasibility study are not simply the sum of the various factors since some components may be conflicting while others will be of a qualitative nature only. Different approaches are therefore needed to evaluate the suitability of an area for shallow geothermal installation. This paper introduces a new GIS platform-based multicriteria decision analysis method aimed at comparing as many different shallow geothermal relevant factors as possible. Using the Analytic Hierarchic Process Tool, a geolocalized Suitability Index was obtained for a specific technological case: the integrated technologies developed within the GEOTeCH Project. A suitability map for the technologies in question was drawn up for Europe.

  16. Three-dimensional hierarchical frameworks based on MoS₂ nanosheets self-assembled on graphene oxide for efficient electrocatalytic hydrogen evolution.

    Science.gov (United States)

    Zhou, Weijia; Zhou, Kai; Hou, Dongman; Liu, Xiaojun; Li, Guoqiang; Sang, Yuanhua; Liu, Hong; Li, Ligui; Chen, Shaowei

    2014-12-10

    Advanced materials for electrocatalytic water splitting are central to renewable energy research. In this work, three-dimensional (3D) hierarchical frameworks based on the self-assembly of MoS2 nanosheets on graphene oxide were produced via a simple one-step hydrothermal process. The structures of the resulting 3D frameworks were characterized by using a variety of microscopic and spectroscopic tools, including scanning and transmission electron microscopies, X-ray diffraction, X-ray photoelectron spectroscopy, and Raman scattering. Importantly, the three-dimensional MoS2/graphene frameworks might be used directly as working electrodes which exhibited apparent and stable electrocatalytic activity in hydrogen evolution reaction (HER), as manifested by a large cathodic current density with a small overpotential of -107 mV (-121 mV when loaded on a glassy-carbon electrode) and a Tafel slope of 86.3 mV/dec (46.3 mV/dec when loaded on a glassy-carbon electrode). The remarkable performance might be ascribed to the good mechanical strength and high electrical conductivity of the 3D frameworks for fast charge transport and collection, where graphene oxide provided abundant nucleation sites for MoS2 deposition and oxygen incorporation led to the formation of defect-rich MoS2 nanosheets with active sites for HER.

  17. Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery

    Directory of Open Access Journals (Sweden)

    Luca Demarchi

    2016-01-01

    Full Text Available In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA. Different segmentation levels were generated based on the two sources of Remote Sensing (RS data, namely very-high spatial resolution, near-infrared imagery (VHR and high-resolution LiDAR topography. At each level, different input object features were tested with Machine Learning classifiers for mapping riverscape units and in-stream mesohabitats. The GEOBIA approach proved to be a powerful tool for analyzing the river system at different levels of detail and for coupling spectral and topographic datasets, allowing for the delineation of the natural fluvial corridor with its primary riverscape units (e.g., water channel, unvegetated sediment bars, riparian densely-vegetated units, etc. and in-stream mesohabitats with a high level of accuracy, respectively of K = 0.91 and K = 0.83. This method is flexible and can be adapted to different sources of data, with the potential to be implemented at regional scales in the future. The analyzed dataset, composed of VHR imagery and LiDAR data, is nowadays increasingly available at larger scales, notably through European Member States. At the same time, this methodology provides a tool for monitoring and characterizing the hydromorphological status of river systems continuously along the entire channel network and coherently through time, opening novel and significant perspectives to river science and management, notably for planning and targeting actions.

  18. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    Dunson, David B

    2009-04-01

    In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

  19. Hierarchical energy and frequency security pricing in a smart microgrid: An equilibrium-inspired epsilon constraint based multi-objective decision making approach

    International Nuclear Information System (INIS)

    Rezaei, Navid; Kalantar, Mohsen

    2015-01-01

    Highlights: • Proposing a multi-objective security pricing mechanism for islanded microgrids. • Generating Pareto points using epsilon constraint methodology. • Best compromise solution using a novel decision making approach. • An equilibrium-inspired technique is used as an efficient decision making method. • Stochastic management of hierarchical reserves in a droop controlled microgrid. - Abstract: The present paper formulates a frequency security constrained energy management system for an islanded microgrid. Static and dynamic securities of the microgrids have been modeled in depth based on droop control paradigm. The derived frequency dependent modeling is incorporated into a multi-objective energy management system. Microgrid central controller is in charge to determine optimal prices of energy and frequency security such that technical, economic and environmental targets are satisfied simultaneously. The associated prices are extracted based on calculating related Lagrange multipliers corresponding to providing the microgrid hourly energy and reserve requirements. Besides, to generate optimal Pareto solutions of the proposed multi-objective framework augmented epsilon constraint method is applied. Moreover, a novel methodology on the basis of Nash equilibrium strategy is devised and employed to select the best compromise solution from the generated Pareto front. Comprehensive analysis tool is implemented in a typical test microgrid and executed over a 24 h scheduling time horizon. The energy, primary and secondary frequency control reserves have been scheduled appropriately in three different case-studies which are defined based on the microgrid various operational policies. The optimization results verify that the operational policies adopted by means of the microgrid central controller have direct impacts on determined energy and security prices. The illustrative implementations can give the microgrid central controller an insight view to provide

  20. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

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

  1. Acetone sensors based on microsheet-assembled hierarchical Fe2O3 with different Fe3+ concentrations

    Science.gov (United States)

    Wang, Han; Yan, Lei; Li, Shuo; Li, Yu; Liu, Li; Du, Liting; Duan, Haojie; Cheng, Yali

    2018-02-01

    Several different morphologies of microsheet-assembled Fe2O3 have been fabricated by hydrothermal method using diverse concentrations of Fe3+ precursor solutions (0.025, 0.020, 0.015, 0.010 mol/L Fe3+). The as-synthesized materials have been characterized by scanning electron microscope (SEM), X-ray powder diffraction (XRD), and energy-dispersive X-ray spectrometry (EDS). The SEM images reflect that the morphologies of as-synthesized materials are affected by the concentrations of Fe3+ in precursor solutions. The less concentration of Fe3+, the more porous of Fe2O3 microflowers, and thinner of slices distributed on the surface. Furthermore, gas sensors based on these Fe2O3 microflowers manufactured and tested to various common gases. The optimum response value to 100 ppm acetone is 52 at the working temperature of 220 °C. Meanwhile, the Fe2O3 microflower sensors possess ultrafast response-recovery speed, which are 8 and 19 s, respectively. The possible sensing mechanism was mainly attributed to the high surface area, three-dimensional porous structure.

  2. Extracting hierarchical organization of complex networks by dynamics towards synchronization

    Science.gov (United States)

    Wang, Xiao-Hua; Jiao, Li-Cheng; Wu, Jian-She

    2009-07-01

    Based on the dynamics towards synchronization in hierarchical networks, we present an efficient method for extracting hierarchical organization in complex network. In the synchronization process, hierarchical structures corresponding to well defined communities of nodes emerge in different time scales, ordered in a hierarchical way. Thus, a new strategy for quantifying the dissimilarity between a pair of nodes in networks is introduced according to their time scales of synchronization. Then, using such a dissimilarity measure in conjunction with a hierarchical clustering method, our extracting method is proposed. The performance of our approach is tested on a set of computer generated and real-world networks with known hierarchical organization. The results demonstrate that our method enables us to offer insight into the complex networks with a multi-scale description. In addition, using a criterion of modularity, the method can also accurately find community structures in complex networks.

  3. 3D hierarchical geometric modeling and multiscale FE analysis as a base for individualized medical diagnosis of bone structure.

    Science.gov (United States)

    Podshivalov, L; Fischer, A; Bar-Yoseph, P Z

    2011-04-01

    This paper describes a new alternative for individualized mechanical analysis of bone trabecular structure. This new method closes the gap between the classic homogenization approach that is applied to macro-scale models and the modern micro-finite element method that is applied directly to micro-scale high-resolution models. The method is based on multiresolution geometrical modeling that generates intermediate structural levels. A new method for estimating multiscale material properties has also been developed to facilitate reliable and efficient mechanical analysis. What makes this method unique is that it enables direct and interactive analysis of the model at every intermediate level. Such flexibility is of principal importance in the analysis of trabecular porous structure. The method enables physicians to zoom-in dynamically and focus on the volume of interest (VOI), thus paving the way for a large class of investigations into the mechanical behavior of bone structure. This is one of the very few methods in the field of computational bio-mechanics that applies mechanical analysis adaptively on large-scale high resolution models. The proposed computational multiscale FE method can serve as an infrastructure for a future comprehensive computerized system for diagnosis of bone structures. The aim of such a system is to assist physicians in diagnosis, prognosis, drug treatment simulation and monitoring. Such a system can provide a better understanding of the disease, and hence benefit patients by providing better and more individualized treatment and high quality healthcare. In this paper, we demonstrate the feasibility of our method on a high-resolution model of vertebra L3. Copyright © 2010 Elsevier Inc. All rights reserved.

  4. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

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

    2013-09-01

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

  5. Hierarchically nested river landform sequences

    Science.gov (United States)

    Pasternack, G. B.; Weber, M. D.; Brown, R. A.; Baig, D.

    2017-12-01

    River corridors exhibit landforms nested within landforms repeatedly down spatial scales. In this study we developed, tested, and implemented a new way to create river classifications by mapping domains of fluvial processes with respect to the hierarchical organization of topographic complexity that drives fluvial dynamism. We tested this approach on flow convergence routing, a morphodynamic mechanism with different states depending on the structure of nondimensional topographic variability. Five nondimensional landform types with unique functionality (nozzle, wide bar, normal channel, constricted pool, and oversized) represent this process at any flow. When this typology is nested at base flow, bankfull, and floodprone scales it creates a system with up to 125 functional types. This shows how a single mechanism produces complex dynamism via nesting. Given the classification, we answered nine specific scientific questions to investigate the abundance, sequencing, and hierarchical nesting of these new landform types using a 35-km gravel/cobble river segment of the Yuba River in California. The nested structure of flow convergence routing landforms found in this study revealed that bankfull landforms are nested within specific floodprone valley landform types, and these types control bankfull morphodynamics during moderate to large floods. As a result, this study calls into question the prevailing theory that the bankfull channel of a gravel/cobble river is controlled by in-channel, bankfull, and/or small flood flows. Such flows are too small to initiate widespread sediment transport in a gravel/cobble river with topographic complexity.

  6. Hierarchical Traces for Reduced NSM Memory Requirements

    Science.gov (United States)

    Dahl, Torbjørn S.

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

  7. Static and dynamic friction of hierarchical surfaces.

    Science.gov (United States)

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

    2016-12-01

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

  8. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

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

  9. Co3O4 based non-enzymatic glucose sensor with high sensitivity and reliable stability derived from hollow hierarchical architecture

    Science.gov (United States)

    Tian, Liangliang; He, Gege; Cai, Yanhua; Wu, Shenping; Su, Yongyao; Yan, Hengqing; Yang, Cong; Chen, Yanling; Li, Lu

    2018-02-01

    Inspired by kinetics, the design of hollow hierarchical electrocatalysts through large-scale integration of building blocks is recognized as an effective approach to the achievement of superior electrocatalytic performance. In this work, a hollow, hierarchical Co3O4 architecture (Co3O4 HHA) was constructed using a coordinated etching and precipitation (CEP) method followed by calcination. The resulting Co3O4 HHA electrode exhibited excellent electrocatalytic activity in terms of high sensitivity (839.3 μA mM-1 cm-2) and reliable stability in glucose detection. The high sensitivity could be attributed to the large specific surface area (SSA), ample unimpeded penetration diffusion paths and high electron transfer rate originating from the unique two-dimensional (2D) sheet-like character and hollow porous architecture. The hollow hierarchical structure also affords sufficient interspace for accommodation of volume change and structural strain, resulting in enhanced stability. The results indicate that Co3O4 HHA could have potential for application in the design of non-enzymatic glucose sensors, and that the construction of hollow hierarchical architecture provides an efficient way to design highly active, stable electrocatalysts.

  10. A facile approach for the synthesis of monolithic hierarchical porous carbons – high performance materials for amine based CO2 capture and supercapacitor electrode

    KAUST Repository

    Estevez, Luis

    2013-05-03

    An ice templating coupled with hard templating and physical activation approach is reported for the synthesis of hierarchically porous carbon monoliths with tunable porosities across all three length scales (macro- meso- and micro), with ultrahigh specific pore volumes [similar]11.4 cm3 g−1. The materials function well as amine impregnated supports for CO2 capture and as supercapacitor electrodes.

  11. Runtime Concepts of Hierarchical Software Components

    Czech Academy of Sciences Publication Activity Database

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

    2007-01-01

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

  12. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

  13. Hierarchical quark mass matrices

    International Nuclear Information System (INIS)

    Rasin, A.

    1998-02-01

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

  14. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...... for the manufacturing of hierarchical materials are advancing at a fast pace, opening new challenges and opportunities. This article presents an overview of possible applications of and perspectives on hierarchical materials.......Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements...

  15. A hierarchical classification approach for recognition of low-density (LDPE) and high-density polyethylene (HDPE) in mixed plastic waste based on short-wave infrared (SWIR) hyperspectral imaging.

    Science.gov (United States)

    Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia

    2018-03-03

    The aim of this work was to recognize different polymer flakes from mixed plastic waste through an innovative hierarchical classification strategy based on hyperspectral imaging, with particular reference to low density polyethylene (LDPE) and high-density polyethylene (HDPE). A plastic waste composition assessment, including also LDPE and HDPE identification, may help to define optimal recycling strategies for product quality control. Correct handling of plastic waste is essential for its further "sustainable" recovery, maximizing the sorting performance in particular for plastics with similar characteristics as LDPE and HDPE. Five different plastic waste samples were chosen for the investigation: polypropylene (PP), LDPE, HDPE, polystyrene (PS) and polyvinyl chloride (PVC). A calibration dataset was realized utilizing the corresponding virgin polymers. Hyperspectral imaging in the short-wave infrared range (1000-2500nm) was thus applied to evaluate the different plastic spectral attributes finalized to perform their recognition/classification. After exploring polymer spectral differences by principal component analysis (PCA), a hierarchical partial least squares discriminant analysis (PLS-DA) model was built allowing the five different polymers to be recognized. The proposed methodology, based on hierarchical classification, is very powerful and fast, allowing to recognize the five different polymers in a single step. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Adaptive Sampling in Hierarchical Simulation

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-09

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

  17. Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column: Original Research Article: Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Chao [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA; Xu, Zhijie [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA; Lai, Canhai [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA; Whyatt, Greg [Pacific Northwest National Laboratory, Energy and Environment Directorate, Richland WA; Marcy, Peter [Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos NM; Sun, Xin [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA

    2017-04-27

    A hierarchical model calibration and validation is proposed for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO2) capture is simulated and simulation results are compared to the parallel bench-scale experimental data. Two unit problems with increasing level of complexity are proposed to breakdown the complex physical/chemical processes of solvent-based CO2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e. the CO2 mass transfer across a falling ethanolamine (MEA) film in absence of chemical reaction. This problem is investigated both experimentally and numerically using nitrous oxide (N2O) as a surrogate for CO2. To capture the motion of gas-liquid interface, a volume of fluid method is employed together with a one-fluid formulation to compute the mass transfer between the two phases. Bench-scale parallel experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration. Two important transport parameters, e.g. Henry’s constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as the input for the second unit problem to address the chemical adsorption of CO2 across the MEA falling film, where both mass transfer and chemical reaction are involved.

  18. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

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

  19. Transmutations across hierarchical levels

    International Nuclear Information System (INIS)

    O'Neill, R.V.

    1977-01-01

    The development of large-scale ecological models depends implicitly on a concept known as hierarchy theory which views biological systems in a series of hierarchical levels (i.e., organism, population, trophic level, ecosystem). The theory states that an explanation of a biological phenomenon is provided when it is shown to be the consequence of the activities of the system's components, which are themselves systems in the next lower level of the hierarchy. Thus, the behavior of a population is explained by the behavior of the organisms in the population. The initial step in any modeling project is, therefore, to identify the system components and the interactions between them. A series of examples of transmutations in aquatic and terrestrial ecosystems are presented to show how and why changes occur. The types of changes are summarized and possible implications of transmutation for hierarchy theory, for the modeler, and for the ecological theoretician are discussed

  20. A -104dBc/Hz In-Band Phase Noise 3GHz All Digital PLL with Phase Interpolation Based Hierarchical Time to Digital Converter

    Science.gov (United States)

    Miyashita, Daisuke; Kobayashi, Hiroyuki; Deguchi, Jun; Kousai, Shouhei; Hamada, Mototsugu; Fujimoto, Ryuichi

    This paper presents an ADPLL using a hierarchical TDC composed of a 4fLO DCO followed by a divide-by-4 circuit and three stages of known phase interpolators. We derived simple design requirements for ensuring precision of the phase interpolator. The proposed architecture provides immunity to PVT and local variations, which allows calibration-free operation, as well as sub-inverter delay resolution contributing to good in-band phase noise performance. Also the hierarchical TDC makes it possible to employ a selective activation scheme for power saving. Measured performances demonstrate the above advantages and the in-band phase noise reaches -104dBc/Hz. It is fabricated in a 65nm CMOS process and the active area is 0.18mm2.

  1. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

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

    2012-01-01

    . On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  2. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls...

  3. An economic growth model based on financial credits distribution to the government economy priority sectors of each regency in Indonesia using hierarchical Bayesian method

    Science.gov (United States)

    Yasmirullah, Septia Devi Prihastuti; Iriawan, Nur; Sipayung, Feronika Rosalinda

    2017-11-01

    The success of regional economic establishment could be measured by economic growth. Since the Act No. 32 of 2004 has been implemented, unbalance economic among the regency in Indonesia is increasing. This condition is contrary different with the government goal to build society welfare through the economic activity development in each region. This research aims to examine economic growth through the distribution of bank credits to each Indonesia's regency. The data analyzed in this research is hierarchically structured data which follow normal distribution in first level. Two modeling approaches are employed in this research, a global-one level Bayesian approach and two-level hierarchical Bayesian approach. The result shows that hierarchical Bayesian has succeeded to demonstrate a better estimation than a global-one level Bayesian. It proves that the different economic growth in each province is significantly influenced by the variations of micro level characteristics in each province. These variations are significantly affected by cities and province characteristics in second level.

  4. Hierarchical microcrack model for materials exemplified at enamel.

    Science.gov (United States)

    Özcoban, H; Yilmaz, E D; Schneider, G A

    2018-01-01

    This article investigates the mechanical properties of a material with hierarchically arranged microcracks. Hierarchically structured biomaterials such as enamel exhibit superior mechanical properties as being stiff and damage tolerant at the same time. The common mechanical explanation for this behavior is based on the hierarchically structured arrangement of hard minerals and soft organics and their cooperative deformation mechanisms. In situ mechanical experiments with mm-sized bovine enamel bending bars an scanning electron microscope reveal that enamel is able to withstand mechanical loading even if it contains microcracks on different lengths scales. To clarify this issue an analytical hierarchical microcrack model of non-interacting cracks is presented. The model predicts a decrease of the elastic modulus and the fracture strength with increasing levels of hierarchy. The fracture strain on the other hand may decrease or increase with the number of hierarchical levels, depending on the microcrack density. This simple hierarchical microcrack model is able to explain already published experiments with focused ion beam prepared μm-sized enamel cantilevers on different hierarchical levels. In addition it is shown that microcracking during loading in hierarchical materials may lead to substantial pseudoplastic behavior. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

  5. In-plane crashworthiness of bio-inspired hierarchical honeycombs

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Hanfeng; Huang, Xiaofei; Scarpa, Fabrizio; Wen, Guilin; Chen, Yanyu; Zhang, Chao

    2018-05-01

    Biological tissues like bone, wood, and sponge possess hierarchical cellular topologies, which are lightweight and feature an excellent energy absorption capability. Here we present a system of bio-inspired hierarchical honeycomb structures based on hexagonal, Kagome, and triangular tessellations. The hierarchical designs and a reference regular honeycomb configuration are subjected to simulated in-plane impact using the nonlinear finite element code LS-DYNA. The numerical simulation results show that the triangular hierarchical honeycomb provides the best performance compared to the other two hierarchical honeycombs, and features more than twice the energy absorbed by the regular honeycomb under similar loading conditions. We also propose a parametric study correlating the microstructure parameters (hierarchical length ratio r and the number of sub cells N) to the energy absorption capacity of these hierarchical honeycombs. The triangular hierarchical honeycomb with N = 2 and r = 1/8 shows the highest energy absorption capacity among all the investigated cases, and this configuration could be employed as a benchmark for the design of future safety protective systems.

  6. Enhanced photovoltaic performance of fully flexible dye-sensitized solar cells based on the Nb{sub 2}O{sub 5} coated hierarchical TiO{sub 2} nanowire-nanosheet arrays

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Wenwu; Hong, Chengxun; Wang, Hui-gang; Zhang, Mei; Guo, Min, E-mail: guomin@ustb.edu.cn

    2016-02-28

    Graphical abstract: Nb{sub 2}O{sub 5} coated hierarchical TiO{sub 2} nanowire-sheet arrays photoanode was synthesized on Ti-mesh substrate by using a hydrothermal approach for fully flexible dye-sensitized solar cells which exhibited well photovoltaic efficiency of 4.55%. - Highlights: • Nb{sub 2}O{sub 5} coated hierarchical TiO{sub 2} nanowire-nanosheet arrays were prepared on Ti-mesh. • Nb{sub 2}O{sub 5} coated TiO{sub 2} HNWAs/Pt-ITO-PEN flexible DSSC was constructed. • The fully flexible DSSC exhibited an enhanced photovoltaic performance of 4.55%. • The reasons for the improved conversion efficiency of the DSSC were discussed. - Abstract: Nb{sub 2}O{sub 5} coated hierarchical TiO{sub 2} nanowire-sheet arrays photoanode was synthesized on flexible Ti-mesh substrate by using a hydrothermal approach. The effect of TiO{sub 2} morphology and Nb{sub 2}O{sub 5} 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 TiO{sub 2} nanowire arrays (NWAs), hierarchical TiO{sub 2} nanowire arrays (HNWAs) with enlarged internal surface area and strong light scattering properties exhibited higher overall conversion efficiency. The introduction of thin Nb{sub 2}O{sub 5} coating layers on the surface of the TiO{sub 2} HNWAs played a key role in improving the photovoltaic performance of the flexible DSSC. By separating the TiO{sub 2} and electrolyte (I{sup –}/I{sub 3}{sup –}), the Nb{sub 2}O{sub 5} energy barrier decreased the electron recombination rate and increased electron collection efficiency and injection efficiency, resulting in improved J{sub sc} and V{sub oc}. Furthermore, the influence of Nb{sub 2}O{sub 5} coating amounts on the power conversion efficiency were discussed in detail. The fully flexible DSSC based on Nb{sub 2}O{sub 5} coated TiO{sub 2} HNWAs films with a thickness of 14 μm displayed a well photovoltaic property

  7. Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models.

    Science.gov (United States)

    Alexandrescu, Roxana; Bottle, Alex; Jarman, Brian; Aylin, Paul

    2014-05-01

    The use of hierarchical logistic regression for provider profiling has been recommended due to the clustering of patients within hospitals, but has some associated difficulties. We assess changes in hospital outlier status based on standard logistic versus hierarchical logistic modelling of mortality. The study population consisted of all patients admitted to acute, non-specialist hospitals in England between 2007 and 2011 with a primary diagnosis of acute myocardial infarction, acute cerebrovascular disease or fracture of neck of femur or a primary procedure of coronary artery bypass graft or repair of abdominal aortic aneurysm. We compared standardised mortality ratios (SMRs) from non-hierarchical models with SMRs from hierarchical models, without and with shrinkage estimates of the predicted probabilities (Model 1 and Model 2). The SMRs from standard logistic and hierarchical models were highly statistically significantly correlated (r > 0.91, p = 0.01). More outliers were recorded in the standard logistic regression than hierarchical modelling only when using shrinkage estimates (Model 2): 21 hospitals (out of a cumulative number of 565 pairs of hospitals under study) changed from a low outlier and 8 hospitals changed from a high outlier based on the logistic regression to a not-an-outlier based on shrinkage estimates. Both standard logistic and hierarchical modelling have identified nearly the same hospitals as mortality outliers. The choice of methodological approach should, however, also consider whether the modelling aim is judgment or improvement, as shrinkage may be more appropriate for the former than the latter.

  8. A Hierarchical Clustering Methodology for the Estimation of Toxicity

    Science.gov (United States)

    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...

  9. Hierarchical Discriminant Analysis.

    Science.gov (United States)

    Lu, Di; Ding, Chuntao; Xu, Jinliang; Wang, Shangguang

    2018-01-18

    The Internet of Things (IoT) generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification) is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA). It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

  10. Hierarchical Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Di Lu

    2018-01-01

    Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

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

    Science.gov (United States)

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

    2013-12-01

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

  12. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

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

  13. Hierarchically structured distributed microprocessor network for control

    International Nuclear Information System (INIS)

    Greenwood, J.R.; Holloway, F.W.; Rupert, P.R.; Ozarski, R.G.; Suski, G.J.

    1979-01-01

    To satisfy a broad range of control-analysis and data-acquisition requirements for Shiva, a hierarchical, computer-based, modular-distributed control system was designed. This system handles the more than 3000 control elements and 1000 data acquisition units in a severe high-voltage, high-current environment. The control system design gives one a flexible and reliable configuration to meet the development milestones for Shiva within critical time limits

  14. Hierarchical Fuzzy Sets To Query Possibilistic Databases

    OpenAIRE

    Thomopoulos, Rallou; Buche, Patrice; Haemmerlé, Ollivier

    2008-01-01

    Within the framework of flexible querying of possibilistic databases, based on the fuzzy set theory, this chapter focuses on the case where the vocabulary used both in the querying language and in the data is hierarchically organized, which occurs in systems that use ontologies. We give an overview of previous works concerning two issues: firstly, flexible querying of imprecise data in the relational model; secondly, the introduction of fuzziness in hierarchies. Concerning the latter point, w...

  15. Bounded Target Cascading in Hierarchical Design Optimization

    Directory of Open Access Journals (Sweden)

    Xiaoling Zhang

    2014-06-01

    Full Text Available For large scale systems, as a hierarchical multilevel decomposed design optimization method, analytical target cascading coordinates the inconsistency between the assigned targets and response in each level by a weighted-sum formulation. To avoid the problems associated with the weighting coefficients, single objective functions in the hierarchical design optimization are formulated by a bounded target cascading method in this paper. In the BTC method, a single objective optimization problem is formulated in the system level, and two kinds of coordination constraints are added: one is bound constraint for the design points based on the response from each subsystem level and the other is linear equality constraint for the common variables based on their sensitivities with respect to each subsystem. In each subsystem level, the deviation with target for design point is minimized in the objective function, and the common variables are constrained by target bounds. Therefore, in the BTC method, the targets are coordinated based on the optimization iteration information in the hierarchical design problem and the performance of the subsystems, and BTC method will converge to the global optimum efficiently. Finally, comparisons of the results from BTC method and the weighted-sum analytical target cascading method are presented and discussed.

  16. Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

    DEFF Research Database (Denmark)

    Pedersen, Thomas Lin

    2017-01-01

    information to increase in knowledge. As the pangenome data structure is essentially a collection of sets we explore the potential for scalable set visualization as a tool for pangenome analysis. We present a new hierarchical clustering algorithm based on set arithmetics that optimizes the intersection sizes...... not correspond with the hierarchy, can be visualized using hierarchical edge bundles. When applied to pangenome data this plot shows putative horizontal gene transfers between the genomes and can highlight relationships between genomes that is not represented by the hierarchy.We illustrate the utility...... of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https://cran.r-project...

  17. Semantic Image Segmentation with Contextual Hierarchical Models.

    Science.gov (United States)

    Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-05-01

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

  18. Hierarchical Sliding Mode Algorithm for Athlete Robot Walking

    OpenAIRE

    Van Dong Hai Nguyen; Xuan-Dung Huynh; Minh-Tam Nguyen; Ionel Cristian Vladu; Mircea Ivanescu

    2017-01-01

    Dynamic equations and the control law for a class of robots with elastic underactuated MIMO system of legs, athlete Robot, are discussed in this paper. The dynamic equations are determined by Euler-Lagrange method. A new method based on hierarchical sliding mode for controlling postures is also introduced. Genetic algorithm is applied to design the oscillator for robot motion. Then, a hierarchical sliding mode controller is implemented to control basic posture of athlete robot stepping. Succe...

  19. Carbon fiber reinforced hierarchical orthogrid stiffened cylinder: Fabrication and testing

    Science.gov (United States)

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

    2018-04-01

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

  20. Hierarchical architecture for flexible energy storage.

    Science.gov (United States)

    Pan, H; Ma, J; Tao, J; Zhu, S

    2017-05-25

    The introduction of hierarchy and chirality into structure is of great interest, and can result in new optical and electronic properties due to the synergistic effect of helical and anisotropic structures. Herein, we demonstrate a simple and straightforward route toward the fabrication of hierarchical chiral materials based on the assembly of two-dimensional graphene oxide nanosheets (GO) and one-dimensional cellulose nanocrystals (CNCs). The unique layered structure of CNC/GO could be preserved in the solid state, allowing electrode active SnO 2 to be loaded for potential applications in energy storage. The resultant SnO 2 /CNC/reduced GO (SnO 2 /CNC/rGO) composite could be processed into film, fiber, and textile with an extremely high tensile strength of 100 MPa. The free-standing SnO 2 /CNC/rGO electrodes exhibit highly improved energy storage performance, with a reversible capacity of ∼500 mA h g -1 maintained for 1500 cycles in the film and ∼800 mA h g -1 maintained for 150 cycles in the textile at a current density of 500 mA g -1 . This is attributed to the prepared hierarchical chiral structures. The presented technique provides an effective approach to producing hierarchical functional materials from nanoparticles as building blocks, which might open an avenue for the creation of new flexible energy storage devices.

  1. Hierarchical structure of Turkey's foreign trade

    Science.gov (United States)

    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.

  2. Hierarchical Fiber Structures Made by Electrospinning Polymers

    Science.gov (United States)

    Reneker, Darrell H.

    2009-03-01

    A filter for water purification that is very thin, with small interstices and high surface area per unit mass, can be made with nanofibers. The mechanical strength of a very thin sheet of nanofibers is not great enough to withstand the pressure drop of the fluid flowing through. If the sheet of nanofibers is made thicker, the strength will increase, but the flow will be reduced to an impractical level. An optimized filter can be made with nanometer scale structures supported on micron scale structures, which are in turn supported on millimeter scale structures. This leads to a durable hierarchical structure to optimize the filtration efficiency with a minimum amount of material. Buckling coils,ootnotetextTao Han, Darrell H Reneker, Alexander L. Yarin, Polymer, Volume 48, issue 20 (September 21, 2007), p. 6064-6076. electrical bending coilsootnotetextDarrell H. Reneker and Alexander L. Yarin, Polymer, Volume 49, Issue 10 (2008) Pages 2387-2425, DOI:10.1016/j.polymer.2008.02.002. Feature Article. and pendulum coilsootnotetextT. Han, D.H. Reneker, A.L. Yarin, Polymer, Volume 49, (2008) Pages 2160-2169, doi:10.1016/jpolymer.2008.01.0487878. spanning dimensions from a few microns to a few centimeters can be collected from a single jet by controlling the position and motion of a collector. Attractive routes to the design and construction of hierarchical structures for filtration are based on nanofibers supported on small coils that are in turn supported on larger coils, which are supported on even larger overlapping coils. ``Such top-down'' hierarchical structures are easy to make by electrospinning. In one example, a thin hierarchical structure was made, with a high surface area and small interstices, having an open area of over 50%, with the thinnest fibers supported at least every 15 microns.

  3. Hierarchical Systems in Open Clusters

    Science.gov (United States)

    de La Fuente Marcos, R.; Aarseth, S. J.; Kiseleva, L. G.; Eggleton, P. P.

    In this paper we study the formation, evolution, and disruption of hierarchical systems in open clusters. With this purpose, N-body simulations of star clusters containing an initial population of binaries have been carried out using Aarseth's NBODY4 and NBODY5 codes. Stable triples may form from strong interactions of two binaries in which the widest pair is disrupted. The most frequent type of hierarchical systems found in the cluster models are triples in which the outer star is single, but in some cases the outer body is also a binary, giving a hierarchical quadruple. The formation of hierarchical systems of even higher multiplicity is also possible. Many triple systems are non-coplanar and the presence of even a very distant and small outer companion may affect the orbital parameters of the inner binary, including a possible mechanism of significant shrinkage if the binary experiences a weak tidal dissipation. The main features of these systems are analyzed in order to derive general properties which can be checked by observations. The inner binaries have periods in the range 1-1000 days, although rich clusters may have even smaller periods following common envelope evolution. For triple systems, the outer body usually has a mass less than 1/3 of the binary, but is sometimes a collapsed object with even smaller mass. The formation of exotic objects, such as blue stragglers and white dwarfs binaries, inside hierarchical triple systems is particularly interesting. An efficient mechanism for generating such objects is the previous formation of a hierarchical system in which the inner binary may develop a very short period during a common envelope phase, which finally results in a stellar collision.

  4. Technique for fast and efficient hierarchical clustering

    Science.gov (United States)

    Stork, Christopher

    2013-10-08

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

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

    Science.gov (United States)

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

    2017-08-15

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

  6. Nonlinear calibration transfer based on hierarchical Bayesian models and Lagrange Multipliers: Error bounds of estimates via Monte Carlo - Markov Chain sampling.

    Science.gov (United States)

    Seichter, Felicia; Vogt, Josef; Radermacher, Peter; Mizaikoff, Boris

    2017-01-25

    The calibration of analytical systems is time-consuming and the effort for daily calibration routines should therefore be minimized, while maintaining the analytical accuracy and precision. The 'calibration transfer' approach proposes to combine calibration data already recorded with actual calibrations measurements. However, this strategy was developed for the multivariate, linear analysis of spectroscopic data, and thus, cannot be applied to sensors with a single response channel and/or a non-linear relationship between signal and desired analytical concentration. To fill this gap for a non-linear calibration equation, we assume that the coefficients for the equation, collected over several calibration runs, are normally distributed. Considering that coefficients of an actual calibration are a sample of this distribution, only a few standards are needed for a complete calibration data set. The resulting calibration transfer approach is demonstrated for a fluorescence oxygen sensor and implemented as a hierarchical Bayesian model, combined with a Lagrange Multipliers technique and Monte-Carlo Markov-Chain sampling. The latter provides realistic estimates for coefficients and prediction together with accurate error bounds by simulating known measurement errors and system fluctuations. Performance criteria for validation and optimal selection of a reduced set of calibration samples were developed and lead to a setup which maintains the analytical performance of a full calibration. Strategies for a rapid determination of problems occurring in a daily calibration routine, are proposed, thereby opening the possibility of correcting the problem just in time. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Three-level parallel-set partitioning in hierarchical trees coding based on the collaborative CPU and GPU for remote sensing images compression

    Science.gov (United States)

    Chen, Hao; Wei, Anqi; Zhang, Ye

    2017-10-01

    To accelerate the massive remote sensing images (RSIs) coding in a ground service-oriented remote sensing system, this study proposes three-level (i.e., tree-level, bit-plane level, and byte-level) parallel-set partitioning in hierarchical trees (TP-SPIHT) coding on a collaborative central and graphic processing unit (CPU and GPU) to parallelize SPIHT by optimizing its dynamic processing with the linked list. Basic parallel SPIHT coding is presented with preprocessing, tree-level parallel coding, and bit-stream organization using three kinds of static marker matrices instead of the dynamic linked lists originally used to remove the data dependency of the original SPIHT. The bit-stream organization is implemented on CPU and other processes are implemented on GPU using GPU streams. The bit-stream organization is further divided into a bit-plane level parallel bit-plane stream extraction and a final bit-stream organization on a multicore CPU. Because no dependencies exist between the different byte operations in the final bit-stream organization, this organization is accelerated by byte-level parallelization on the GPU. Experimental results with different sized RSIs show that TP-SPIHT takes 292.03 ms to code a 2048×2048 image and achieves a 6.27 times speedup compared with an optimized CPU implementation. The speedup ratio improves as the image increases from 256×256 to 2048×2048.

  8. High-performance non-enzymatic catalysts based on 3D hierarchical hollow porous Co3O4nanododecahedras in situ decorated on carbon nanotubes for glucose detection and biofuel cell application.

    Science.gov (United States)

    Wang, Shiyue; Zhang, Xiaohua; Huang, Junlin; Chen, Jinhua

    2018-03-01

    In this work, high-performance non-enzymatic catalysts based on 3D hierarchical hollow porous Co 3 O 4 nanododecahedras in situ decorated on carbon nanotubes (3D Co 3 O 4 -HPND/CNTs) were successfully prepared via direct carbonizing metal-organic framework-67 in situ grown on carbon nanotubes. The morphology, microstructure, and composite of 3D Co 3 O 4 -HPND/CNTs were characterized by scanning electron microscopy, transmission electron microscopy, micropore and chemisorption analyzer, and X-ray diffraction. The electrochemical characterizations indicated that 3D Co 3 O 4 -HPND/CNTs present considerably catalytic activity toward glucose oxidation and could be promising for constructing high-performance electrochemical non-enzymatic glucose sensors and glucose/O 2 biofuel cell. When used for non-enzymatic glucose detection, the 3D Co 3 O 4 -HPND/CNTs modified glassy carbon electrode (3D Co 3 O 4 -HPND/CNTs/GCE) exhibited excellent analytical performance with high sensitivity (22.21 mA mM -1  cm -2 ), low detection limit of 0.35 μM (S/N = 3), fast response (less than 5 s) and good stability. On the other hand, when the 3D Co 3 O 4 -HPND/CNTs/GCE worked as an anode of a biofuel cell, a maximum power density of 210 μW cm -2 at 0.15 V could be obtained, and the open circuit potential was 0.68 V. The attractive 3D hierarchical porous structural features, the large surface area, and the excellent conductivity based on the continuous and effective electron transport network in 3D Co 3 O 4 -HPND/CNTs endow 3D Co 3 O 4 -HPND/CNTs with the enhanced electrochemical performance and promising applications in electrochemical sensing, biofuel cell, and other energy storage and conversion devices such as supercapacitor. Graphical abstract High-performance non-enzymatic catalysts for enzymeless glucose sensing and biofuel cell based on 3D hierarchical hollow porous Co 3 O 4 nanododecahedras anchored on carbon nanotubes were successfully prepared via direct carbonizing

  9. In Situ Confined Growth Based on a Self-Templating Reduction Strategy of Highly Dispersed Ni Nanoparticles in Hierarchical Yolk-Shell Fe@SiO2Structures as Efficient Catalysts.

    Science.gov (United States)

    Jiao, Jiao; Wang, Haiyan; Guo, Wanchun; Li, Ruifei; Tian, Kesong; Xu, Zhaopeng; Jia, Yin; Wu, Yuehao; Cao, Ling

    2016-12-19

    Ni-based magnetic catalysts exhibit moderate activity, low cost, and magnetic reusability in hydrogenation reactions. However, Ni nanoparticles anchored on magnetic supports commonly suffer from undesirable agglomeration during catalytic reactions due to the relatively weak affinity of the magnetic support for the Ni nanoparticles. A hierarchical yolk-shell Fe@SiO 2 /Ni catalyst, with an inner movable Fe core and an ultrathin SiO 2 /Ni shell composed of nanosheets, was synthesized in a self-templating reduction strategy with a hierarchical yolk-shell Fe 3 O 4 @nickel silicate nanocomposite as the precursor. The spatial confinement of highly dispersed Ni nanoparticles with a mean size of 4 nm within ultrathin SiO 2 nanosheets with a thickness of 2.6 nm not only prevented their agglomeration during catalytic transformations but also exposed the abundant active Ni sites to reactants. Moreover, the large inner cavities and interlayer spaces between the assembled ultrathin SiO 2 /Ni nanosheets provided suitable mesoporous channels for diffusion of the reactants towards the active sites. As expected, the Fe@SiO 2 /Ni catalyst displayed high activity, high stability, and magnetic recoverability for the reduction of nitroaromatic compounds. In particular, the Ni-based catalyst in the conversion of 4-nitroamine maintained a rate of over 98 % and preserved the initial yolk-shell structure without any obvious aggregation of Ni nanoparticles after ten catalytic cycles, which confirmed the high structural stability of the Ni-based catalyst. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Modular networks with hierarchical organization

    Indian Academy of Sciences (India)

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary ...

  11. Evaluation of the three-in-one team-based care model on hierarchical diagnosis and treatment patterns among patients with diabetes: a retrospective cohort study using Xiamen's regional electronic health records.

    Science.gov (United States)

    Li, Xuejun; Li, Zhibin; Liu, Changqin; Zhang, Junfeng; Sun, Zhonghai; Feng, Yuji; Mei, Jing; Gu, Chengming; Li, Xiaoying; Yang, Shuyu

    2017-11-28

    Xiamen is a pilot city in China for hierarchical diagnosis and treatment reform of non-communicable diseases, especially diabetes. Since 2012, Xiamen has implemented a program called the "three-in-one", a team-based care model for the treatment of diabetes, which involves collaboration between diabetes specialists, general practitioners, and health managers. In addition, the program provides financial incentives to improve care, as greater accessibility to medications through community health care centers (CHCs). The aim of this study was to evaluate the effectiveness of these policies in shifting visits from general hospitals to CHCs for the treatment of type 2 diabetes mellitus (T2DM). A retrospective observational cohort study was conducted using Xiamen's regional electronic health record (EHR) database, which included 90% of all patients registered since 2012. Logistic regression was used to derive the adjusted odds ratio (OR) for patients shifting from general hospitals to CHCs. Among patients treated at hospitals, Kaplan-Meier(KM) curves were constructed to evaluate the time from each policy introduction until the switch to CHCs. A k-means clustering analysis was conducted to identify patterns of patient care-seeking behavior. In total, 89,558 patients and 2,373,524 visits were included. In contrast to increased outpatient visits to general hospitals in China overall, the percentage of visits to CHCs in Xiamen increased from 29.7% in 2012 to 66.5% in 2016. The most significant and rapid shift occurred in later periods after full policy implementation. Three clusters of patients were identified with different levels of complications and health care-seeking frequency. All had similar responses to the policies. The "three-in-one" team-based care model showed promising results for building a hierarchical health care system in China. These policy reforms effectively increased CHCs utilization among diabetic patients.

  12. Urban pattern: Layout design by hierarchical domain splitting

    KAUST Repository

    Yang, Yongliang

    2013-11-06

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

  13. Modelling complex networks by random hierarchical graphs

    Directory of Open Access Journals (Sweden)

    M.Wróbel

    2008-06-01

    Full Text Available Numerous complex networks contain special patterns, called network motifs. These are specific subgraphs, which occur oftener than in randomized networks of Erdős-Rényi type. We choose one of them, the triangle, and build a family of random hierarchical graphs, being Sierpiński gasket-based graphs with random "decorations". We calculate the important characteristics of these graphs - average degree, average shortest path length, small-world graph family characteristics. They depend on probability of decorations. We analyze the Ising model on our graphs and describe its critical properties using a renormalization-group technique.

  14. SORM applied to hierarchical parallel system

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager

    2006-01-01

    of a particular first order reliability method (FORM) was first described in a celebrated paper by Rackwitz and Fiessler more than a quarter of a century ago. The method has become known as the Rackwitz-Fiessler algorithm. The original RF-algorithm as applied to a hierarchical random variable model...... is recapitulated so that a simple but quite effective accuracy improving calculation can be explained. A limit state curvature correction factor on the probability approximation is obtained from the final stop results of the RF-algorithm. This correction factor is based on Breitung’s asymptotic formula for second...

  15. Image Information Mining Utilizing Hierarchical Segmentation

    Science.gov (United States)

    Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai

    2002-01-01

    The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

  16. Synthesis strategies in the search for hierarchical zeolites.

    Science.gov (United States)

    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

  17. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

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

    Science.gov (United States)

    Jeon, Hyeon-Ae

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hyeon-Ae eJeon

    2014-11-01

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

  20. Hybrid and hierarchical composite materials

    CERN Document Server

    Kim, Chang-Soo; Sano, Tomoko

    2015-01-01

    This book addresses a broad spectrum of areas in both hybrid materials and hierarchical composites, including recent development of processing technologies, structural designs, modern computer simulation techniques, and the relationships between the processing-structure-property-performance. Each topic is introduced at length with numerous  and detailed examples and over 150 illustrations.   In addition, the authors present a method of categorizing these materials, so that representative examples of all material classes are discussed.

  1. Hierarchical Parallelization of Gene Differential Association Analysis

    Directory of Open Access Journals (Sweden)

    Dwarkadas Sandhya

    2011-09-01

    Full Text Available Abstract Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

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

    Science.gov (United States)

    Shakouri, Amir; Xu, Feifei; Fan, Zheng

    2017-07-01

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

  3. Automated hierarchical testable design of digital circuits

    Science.gov (United States)

    Kraak, M.

    1993-03-01

    The thesis gives an overview of approaches dealing with the selection of test strategies and methods for digital circuits and the incorporation of test in designs. A review is provided of existing testability analyzers. A new way to analyze testability at three hierarchical levels of abstraction is presented. It is shown how this approach is contained in an expert system rule-base called TRI Stage Testability Analysis (TRISTAN). The paper then deals with testability synthesis. It is shown that a new synthesis method had to be devised to be able to hierarchically select test strategies and methods. The testability synthesizer is also contained in a rule-base, called Intelligent Synthesis of Testable Designs (ISOLDE). TRISTAN and ISOLDE are parts of an expert system called WAGNER. The knowledge processor for WAGNER is covered, presenting its knowledge representation scheme, knowledge acquisition and inference mechanism. Results of experiments done with WAGNER on board and chip level designs are given. Conclusive remarks provide an outlook to continued research.

  4. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  6. Development of hierarchical magnesium composites using hybrid microwave sintering.

    Science.gov (United States)

    Habibi, Meisam Kouhi; Joshi, Shailendra P; Gupta, Manoj

    2011-01-01

    In this work, hierarchical magnesium based composites with a micro-architecture comprising reinforcing constituent that is a composite in itself were fabricated using powder metallurgy route including microwave assisted rapid sintering technique and hot extrusion. Different level-I composite particles comprises sub-micron pure aluminum (Al) matrix containing Al2O3 particles of different length scale (from micrometer to nanometer size). Microstructural characterization of the hierarchical composites revealed reasonably uniform distribution of level-I composite particles and significant grain refinement compared to monolithic Mg. Hierarchical composite configurations exhibited different mechanical performance as a function of Al2O3 length scale. Among the different hierarchical formulations synthesized, the hierarchical configuration with level-I composition comprising Al and nano-Al2O3 (0.05 microm) exhibited the highest improvement in tensile yield strength (0.2% YS), ultimate tensile strength (UTS), tensile failure strain (FS), compressive yield strength (0.2% CYS) and ultimate compressive strength (UCS) (+96%, +80%, +42%, +80%, and +83%) as compared to monolithic Mg. An attempt has been made in the present study to correlate the effect of different length scales of Al2O3 particulates on the microstructural and mechanical response of magnesium.

  7. The concept of a hierarchical cosmos

    Science.gov (United States)

    Grujić, P. V.

    2003-10-01

    The idea of a hierachically structured cosmos can be traced back to the Presocratic Hellada. In the fifth century BC Anaxagoras from Clazomenae developed an idea of a sort of fractal material world, by introducing the concept of seeds (spermata), or homoeomeries as Aristotle dubbed it later (Grujić 2001). Anaxagoras ideas have been grossly neglected during the Middle Ages, to be invoked by a number of post-Renaissance thinkers, like Leibniz, Kant, etc, though neither of them referred to their Greek predecessor. But the real resurrections of the hierarchical paradigm started at the beginning of the last century, with Fournier and Charlier (Grujić 2002). Second half of the 20th century witnessed an intensive development of the theoretical models based on the (multi)fractal paradigm, as well as a considerable body of the observational evidence in favour of the hierarchical cosmos (Saar 1988). We overview the state of the art of the cosmological fractal concept, both within the astrophysical (Sylos Labini et al 1998), methodological (Ribeiro 2001) and epistemological (Ribeiro and Videira 1998) context.

  8. Nanoscale hierarchical optical interactions for secure information

    Directory of Open Access Journals (Sweden)

    Tate Naoya

    2016-12-01

    Full Text Available There is increasing demand for novel physical security that can differentiate between real and false specific artifact that have been added to bank bills, certifications, and other vouchers. The most simple and effective method for improving the security level is to scale down the elemental structures so that they cannot be duplicated by attackers. While there is a paradox that the achieved fabrication resolution by a defender can also be realized by an attacker, further improvement in security is possible by the functional fusion of artifact metrics and nanophotonics. The fundamental advantages of this concept are the high-level clone resistance and individuality of nanoscale artifacts, which are based on the super-resolution fabrication and nanoscale hierarchical structure of optical near-field interactions, respectively. In this paper, the basis for the fabrication of nanoscale artifacts by utilizing random phenomena is described, and a quantitative evaluation of the security level is presented. An experimental demonstration using a nano-/macro-hierarchical hologram is presented to demonstrate the fundamental procedure for retrieving nanoscale features as hidden information. Finally, the concept and a simple demonstration of non-scanning probe microscopy are described as a practical application of the retrieval and authentication of nanoscale artifact metrics.

  9. Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

    Science.gov (United States)

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

    2017-11-01

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

  10. Multimodal X-ray Imaging of Hierarchical Materials

    DEFF Research Database (Denmark)

    Birkbak, Mie Elholm

    2017-01-01

    Hierarchical materials – materials displaying distinct structural features on multiple different length scales - are found in abundance in nature. Bone is an excellent example of a hierarchical material, combining mineral platelets, water and organic molecules to an intricate 3D structure. Well...... to understand this class of materials, information covering the different hierarchical levels in 3D is essential. The requirement of high resolution, large field of views and sufficient penetration power makes this a remarkably challenging task. With its relative weak interaction with matter and a multitude...... of the narwhal and the attachment spicule of the deep sea sponge Euplectella aspergillum. The findings have been enabled by modern synchrotron tomography methods, allowing sub-micron 3D resolution of extended samples. The development of growing bone was followed using scanning based techniques showing gradual...

  11. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Ji

    2017-02-01

    Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

  12. Detecting the overlapping and hierarchical community structure in complex networks

    International Nuclear Information System (INIS)

    Lancichinetti, Andrea; Fortunato, Santo; Kertesz, Janos

    2009-01-01

    Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.

  13. A Hierarchical Learning Control Framework for an Aerial Manipulation System

    Science.gov (United States)

    Ma, Le; Chi, yanxun; Li, Jiapeng; Li, Zhongsheng; Ding, Yalei; Liu, Lixing

    2017-07-01

    A hierarchical learning control framework for an aerial manipulation system is proposed. Firstly, the mechanical design of aerial manipulation system is introduced and analyzed, and the kinematics and the dynamics based on Newton-Euler equation are modeled. Secondly, the framework of hierarchical learning for this system is presented, in which flight platform and manipulator are controlled by different controller respectively. The RBF (Radial Basis Function) neural networks are employed to estimate parameters and control. The Simulation and experiment demonstrate that the methods proposed effective and advanced.

  14. Hierarchical Sliding Mode Algorithm for Athlete Robot Walking

    Directory of Open Access Journals (Sweden)

    Van Dong Hai Nguyen

    2017-01-01

    Full Text Available Dynamic equations and the control law for a class of robots with elastic underactuated MIMO system of legs, athlete Robot, are discussed in this paper. The dynamic equations are determined by Euler-Lagrange method. A new method based on hierarchical sliding mode for controlling postures is also introduced. Genetic algorithm is applied to design the oscillator for robot motion. Then, a hierarchical sliding mode controller is implemented to control basic posture of athlete robot stepping. Successful simulation results show the motion of athlete robot.

  15. Higher-Order Hierarchical Legendre Basis Functions in Applications

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  16. Design of a Predictive Hierarchical Controller Using FEMLAB

    OpenAIRE

    B. Rehák

    2006-01-01

    A hierarchical controller with two levels is proposed. One level is based on dynamic optimization while the second is responsible for tracking the optimal trajectory and rejecting disturbances. Its implementation using the FEMLAB system is described. Some simulations are presented at the end of the paper, together with an evaluation of the performance. 

  17. A Rational Synthesis of Hierarchically Porous, N-Doped Carbon from Mg-Based MOFs: Understanding the Link between Nitrogen Content and Oxygen Reduction Electrocatalysis

    NARCIS (Netherlands)

    Eisenberg, D.; Stroek, W.; Geels, N.J.; Tanase, S.; Ferbinteanu, M.; Teat, S.J.; Mettraus, P.; Yan, N.; Rothenberg, G.

    2016-01-01

    Controlled mixtures of novel Mg-based metal–organic frameworks (MOFs) were prepared, with H+ or K+ as counterions. A linear relation was found between synthesis pH and K/H ratio in the resultant mixture, establishing the tunability of the synthesis. Upon pyrolysis, these precursor mixtures yield

  18. Loops in hierarchical channel networks

    Science.gov (United States)

    Katifori, Eleni; Magnasco, Marcelo

    2012-02-01

    Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

  19. Hierarchical organisation of causal graphs

    International Nuclear Information System (INIS)

    Dziopa, P.

    1993-01-01

    This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs

  20. Stability of glassy hierarchical networks

    Science.gov (United States)

    Zamani, M.; Camargo-Forero, L.; Vicsek, T.

    2018-02-01

    The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

  1. Multilevel hierarchically ordered artificial biomineral.

    Science.gov (United States)

    Liu, Xiaoguo; Lin, Kaili; Wu, Chengtie; Wang, Yueyue; Zou, Zhaoyong; Chang, Jiang

    2014-01-15

    Living organisms are known for creating complex organic-inorganic hybrid materials such as bone, teeth, and shells, which possess outstanding functions as compared to their simple mineral forms. This has inspired many attempts to mimic such structures, but has yielded few practical advances. In this study, a multilevel hierarchically ordered artificial biomineral (a composite of hydroxyapatite and gelatine) with favorable nanomechanical properties is reported. A typical optimized HAp/gelatin hybrid material in the perpendicular direction of the HAp c-axis has a modulus of 25.91 + 1.78 GPa and hardness of 0.90 + 0.10 GPa, which well matches that of human cortical bone (modulus 24.3 + 1.4 GPa, hardness 0.69 + 0.05 GPa). The bottom-up crystal constructions (from nano- to micro- to macroscale) of this material are achieved through a hard template approach by the phase transformation from DCP to HAp. The structural biomimetic material shows another way to mimic the complex hierarchical designs of sclerous tissues which have potential value for application in hard tissue engineering. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Comparing and Ranking tourism websites performance based on e-satisfaction, e-trust, e-quality, and e-loyalty: A combined approach of structural equation modeling, fuzzy and analytical hierarchical process

    Directory of Open Access Journals (Sweden)

    Mohammad Sharifi-Tehrani

    2017-09-01

    Full Text Available This research aims to rank the relative performance of tourism websites in terms of e-satisfaction, e-trust, e-quality, and e-loyalty variables. To this end, two major Iranian travel websites providing accommodation (Iran Hotel Online and tour packages (Marcopolo Corporation were chosen and their performances were evaluated based on the four above variables. This research comprises two independent surveys. The first survey administered to a sample of 155 university professors and website designers examined the relative weights of the study variables in explaining the e-performance of these websites through structural equation modeling (SEM. The results indicate that e-quality, e-loyalty, e-trust, and e-satisfaction have the strongest impact on the e-performance, respectively. The second survey examined relative weights of the e-performance based on the websites’ existing e-customers (two categories of 154 and 187 samples and also qualitative content analysis of the websites’ characteristics using fuzzy analytical hierarchical process (AHP. The findings served to inform that Marcopolo website obtained stronger weights for all four variables, compared with Iran Hotel Online, indicating its higher performance in all variables. At the end, the weight values from the SEM and AHP surveys were synthesized (0.580 and 0.418 for Marcopolo and Iran Hotel Online, respectively in order to rank the websites based on their e-performances. According to the findings, Marcopolo website outperforms its counterpart in all four variables. The current paper contributes to the literature by yielding some insights into how to benchmark websites in order to improve their e-performance based on perspectives of both customers and experts.

  3. Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters

    Directory of Open Access Journals (Sweden)

    Muhammad Shahzad Sarfraz

    2014-12-01

    Full Text Available The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.

  4. Hierarchical Power Sharing Control in DC Microgrids

    DEFF Research Database (Denmark)

    Peyghami, Saeed; Mokhtari, Hossein; Blaabjerg, Frede

    2016-01-01

    Because of the advances in power electronics, DC-based power systems, have been used in industrial applications such as data centers [18], space applications [10], aircraft [12], offshore wind farms, electric vehicles [56], DC home systems [5, 20], and high-voltage DC transmission systems....... To provide such sensitive loads with more reliability, efficiency, and controllability for future power systems, AC microgrid and more recently DC microgrid and smart-grid technologies have been employed [ , , , and ]. To obtain stable and optimal operation in DC power systems (microgrids), proper load...... sharing among different energy units and acceptable voltage regulation across the microgrid is required. This can be achieved by use of a hierarchical power management structure. The highest level in this hierarchy (tertiary) is responsible for the power flow control between the microgrid and the utility...

  5. Inferring hierarchical clustering structures by deterministic annealing

    International Nuclear Information System (INIS)

    Hofmann, T.; Buhmann, J.M.

    1996-01-01

    The unsupervised detection of hierarchical structures is a major topic in unsupervised learning and one of the key questions in data analysis and representation. We propose a novel algorithm for the problem of learning decision trees for data clustering and related problems. In contrast to many other methods based on successive tree growing and pruning, we propose an objective function for tree evaluation and we derive a non-greedy technique for tree growing. Applying the principles of maximum entropy and minimum cross entropy, a deterministic annealing algorithm is derived in a meanfield approximation. This technique allows us to canonically superimpose tree structures and to fit parameters to averaged or open-quote fuzzified close-quote trees

  6. Hierarchical Codebook Design for Massive MIMO

    Directory of Open Access Journals (Sweden)

    Xin Su

    2015-02-01

    Full Text Available The Research of Massive MIMO is an emerging area, since the more antennas the transmitters or receivers equipped with, the higher spectral efficiency and link reliability the system can provide. Due to the limited feedback channel, precoding and codebook design are important to exploit the performance of massive MIMO. To improve the precoding performance, we propose a novel hierarchical codebook with the Fourier-based perturbation matrices as the subcodebook and the Kerdock codebook as the main codebook, which could reduce storage and search complexity due to the finite a lphabet. Moreover, t o f urther r educe t he search complexity and feedback overhead without noticeable performance degradation, we use an adaptive selection algorithm to decide whether to use the subcodebook. Simulation results show that the proposed codebook has remarkable performance gain compared to the conventional Kerdock codebook, without significant increase in feedback overhead and search complexity.

  7. Power Efficient Hierarchical Scheduling for DSP Transformations

    Directory of Open Access Journals (Sweden)

    P. K. Merakos

    2002-01-01

    Full Text Available In this paper, the problem of scheduling the computation of partial products in transformational Digital Signal Processing (DSP algorithms, aiming at the minimization of the switching activity in data and address buses, is addressed. The problem is stated as a hierarchical scheduling problem. Two different optimization algorithms, which are based on the Travelling Salesman Problem (TSP, are defined. The proposed optimization algorithms are independent on the target architecture and can be adapted to take into account it. Experimental results obtained from the application of the proposed algorithms in various widely used DSP transformations, like Discrete Cosine Transform (DCT and Discrete Fourier Transform (DFT, show that significant switching activity savings in data and address buses can be achieved, resulting in corresponding power savings. In addition, the differences between the two proposed methods are underlined, providing envisage for their suitable selection for implementation, in particular transformational algorithms and architectures.

  8. BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

    Science.gov (United States)

    Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

    2009-02-15

    BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

  9. Rational design of hierarchically porous birnessite-type manganese dioxides nanosheets on different one-dimensional titania-based nanowires for high performance supercapacitors

    KAUST Repository

    Zhang, Yu Xin

    2014-12-01

    A facile and large-scale strategy of mesoporous birnessite-type manganese dioxide (MnO2) nanosheets on one-dimension (1D) H2Ti 3O7 and anatase/TiO2 (B) nanowires (NWs) is developed for high performance supercapacitors. The morphological characteristics of MnO2 nanoflakes on H2Ti 3O7 and anatase/TiO2 (B) NWs could be rationally designed with various characteristics (e.g., the sheet thickness, surface area). Interestingly, the MnO2/TiO2 NWs exhibit a more optimized electrochemical performance with specific capacitance of 120 F g-1 at current density of 0.1 A g-1 (based on MnO 2 + TiO2) than MnO2/H2Ti 3O7 NWs. An asymmetric supercapacitor of MnO 2/TiO2//activated graphene (AG) yields a better energy density of 29.8 Wh kg-1 than MnO2/H2Ti 3O7//AG asymmetric supercapacitor, while maintaining desirable cycling stability. Indeed, the pseudocapacitive difference is related to the substrates, unique structure and surface area. Especially, the anatase/TiO2 (B) mixed-phase system can provide good electronic conductivity and high utilization of MnO2 nanosheets. © 2014 Elsevier B.V. All rights reserved.

  10. Core Recursive Hierarchical Image Segmentation

    Science.gov (United States)

    Tilton, James

    2011-01-01

    The Recursive Hierarchical Image Segmentation (RHSEG) software has been repackaged to provide a version of the RHSEG software that is not subject to patent restrictions and that can be released to the general public through NASA GSFC's Open Source release process. Like the Core HSEG Software Package, this Core RHSEG Software Package also includes a visualization program called HSEGViewer along with a utility program HSEGReader. It also includes an additional utility program called HSEGExtract. The unique feature of the Core RHSEG package is that it is a repackaging of the RHSEG technology designed to specifically avoid the inclusion of the certain software technology. Unlike the Core HSEG package, it includes the recursive portions of the technology, but does not include processing window artifact elimination technology.

  11. Hierarchical magnetic assembly of nanowires

    International Nuclear Information System (INIS)

    Hangarter, Carlos M; Rheem, Youngwoo; Yoo, Bongyoung; Yang, Eui-Hyeok; Myung, Nosang V

    2007-01-01

    Magnetic alignment is reported as a facile technique for assembling nanowires into hierarchical structures. Cross junction and T junction nanowire networks are demonstrated using a sequential alignment technique on unpatterned substrates and predefined lithographically patterned ferromagnetic electrodes. The formation of T junctions prevails as nanowires from the first alignment behave as ferromagnetic electrodes under the external magnetic field of the second alignment. The presence of prefabricated ferromagnetic electrodes dominates dipole interactions of localized nanowires for preferential alignment. Application of a magnetic field from a cylindrical coaxial magnet has also been utilized to form radially aligned nanowires. The magnetic field of the coaxial cylindrical magnet produced a dense, concentric nanowire configuration at the centre of the magnetic field as a consequence of the radial field gradient, and sparse nanowire arrangements in the peripheral field, which were utilized as interconnects with a concentric electrode design

  12. Microsphere-Based Hierarchically Juxtapositioned Biphasic Scaffolds Prepared from Poly(Lactic-co-Glycolic Acid and Nanohydroxyapatite for Osteochondral Tissue Engineering

    Directory of Open Access Journals (Sweden)

    K. T. Shalumon

    2016-12-01

    Full Text Available This study aims to prepare biphasic osteochondral scaffolds based on seamless joining of sintered polymer and polymer/ceramic microspheres for co-culture of chondrocytes and bone marrow stem cells (BMSCs. Poly(lactide-co-glycolide (PLGA microspheres and 10% nanohydroxyapatite (nHAP-incorporated PLGA (PGA/nHAP microspheres were prepared through the oil-in-water precipitation method. Virgin (V and composite (C scaffolds were prepared from 250–500 µm PLGA and PLGA/nHAP microspheres, respectively, while osteochondral (OC scaffolds were fabricated through the combination of V and C scaffolds. Physico-chemical properties of scaffolds were characterized through microscopic-spectroscopic evaluations. The effect of nHAP in scaffolds was investigated through thermogravimetric analysis and mechanical testing, while surface hydrophobicity was tested through contact angle measurements. Rabbit chondrocytes and BMSCs were used for cell culture, and cell morphology and proliferation were determined from SEM and DNA assays. Alizarin red and Alcian blue stains were used to identify the in vitro bone and cartilage tissue-specific regeneration, while cetylpyridinium chloride was used to quantitatively estimate calcium in mineralized bone. For co-culture in OC scaffolds, BMSCs were first seeded in the bone part of the scaffold and cultured in osteogenic medium, followed by seeding chondrocytes in the cartilage part, and cultured in chondrocyte medium. High cell viability was confirmed from the Live/Dead assays. Actin cytoskeleton organization obtained by DAPI-phalloidin staining revealed proper organization of chondrocytes and BMSCs in OC scaffolds. Immunofluorescent staining of bone (type I collagen and osteocalcin (OCN and cartilage marker proteins (type II collagen (COL II confirmed cellular behavior of osteoblasts and chondrocytes in vitro. Using an ectopic osteochondral defect model by subcutaneous implantation of co-cultured OC scaffolds in nude mice

  13. Adaptive hierarchical multi-agent organizations

    NARCIS (Netherlands)

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

    2010-01-01

    In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the

  14. Hierarchical Rhetorical Sentence Categorization for Scientific Papers

    Science.gov (United States)

    Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.

    2018-03-01

    Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.

  15. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Directory of Open Access Journals (Sweden)

    Zheng eRen

    2013-11-01

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

  16. Hierarchical imaging of the human knee

    Science.gov (United States)

    Schulz, Georg; Götz, Christian; Deyhle, Hans; Müller-Gerbl, Magdalena; Zanette, Irene; Zdora, Marie-Christine; Khimchenko, Anna; Thalmann, Peter; Rack, Alexander; Müller, Bert

    2016-10-01

    Among the clinically relevant imaging techniques, computed tomography (CT) reaches the best spatial resolution. Sub-millimeter voxel sizes are regularly obtained. For investigations on true micrometer level lab-based μCT has become gold standard. The aim of the present study is the hierarchical investigation of a human knee post mortem using hard X-ray μCT. After the visualization of the entire knee using a clinical CT with a spatial resolution on the sub-millimeter range, a hierarchical imaging study was performed using a laboratory μCT system nanotom m. Due to the size of the whole knee the pixel length could not be reduced below 65 μm. These first two data sets were directly compared after a rigid registration using a cross-correlation algorithm. The μCT data set allowed an investigation of the trabecular structures of the bones. The further reduction of the pixel length down to 25 μm could be achieved by removing the skin and soft tissues and measuring the tibia and the femur separately. True micrometer resolution could be achieved after extracting cylinders of several millimeters diameters from the two bones. The high resolution scans revealed the mineralized cartilage zone including the tide mark line as well as individual calcified chondrocytes. The visualization of soft tissues including cartilage, was arranged by X-ray grating interferometry (XGI) at ESRF and Diamond Light Source. Whereas the high-energy measurements at ESRF allowed the simultaneous visualization of soft and hard tissues, the low-energy results from Diamond Light Source made individual chondrocytes within the cartilage visual.

  17. HIERARCHICAL FRAGMENTATION OF THE ORION MOLECULAR FILAMENTS

    International Nuclear Information System (INIS)

    Takahashi, Satoko; Ho, Paul T. P.; Su, Yu-Nung; Teixeira, Paula S.; Zapata, Luis A.

    2013-01-01

    We present a high angular resolution map of the 850 μm continuum emission of the Orion Molecular Cloud-3 (OMC 3) obtained with the Submillimeter Array (SMA); the map is a mosaic of 85 pointings covering an approximate area of 6.'5 × 2.'0 (0.88 × 0.27 pc). We detect 12 spatially resolved continuum sources, each with an H 2 mass between 0.3-5.7 M ☉ and a projected source size between 1400-8200 AU. All the detected sources are on the filamentary main ridge (n H 2 ≥10 6 cm –3 ), and analysis based on the Jeans theorem suggests that they are most likely gravitationally unstable. Comparison of multi-wavelength data sets indicates that of the continuum sources, 6/12 (50%) are associated with molecular outflows, 8/12 (67%) are associated with infrared sources, and 3/12 (25%) are associated with ionized jets. The evolutionary status of these sources ranges from prestellar cores to protostar phase, confirming that OMC-3 is an active region with ongoing embedded star formation. We detect quasi-periodical separations between the OMC-3 sources of ≈17''/0.035 pc. This spatial distribution is part of a large hierarchical structure that also includes fragmentation scales of giant molecular cloud (≈35 pc), large-scale clumps (≈1.3 pc), and small-scale clumps (≈0.3 pc), suggesting that hierarchical fragmentation operates within the Orion A molecular cloud. The fragmentation spacings are roughly consistent with the thermal fragmentation length in large-scale clumps, while for small-scale cores it is smaller than the local fragmentation length. These smaller spacings observed with the SMA can be explained by either a helical magnetic field, cloud rotation, or/and global filament collapse. Finally, possible evidence for sequential fragmentation is suggested in the northern part of the OMC-3 filament.

  18. Automated tetraploid genotype calling by hierarchical clustering.

    Science.gov (United States)

    Schmitz Carley, Cari A; Coombs, Joseph J; Douches, David S; Bethke, Paul C; Palta, Jiwan P; Novy, Richard G; Endelman, Jeffrey B

    2017-04-01

    New software to make tetraploid genotype calls from SNP array data was developed, which uses hierarchical clustering and multiple F1 populations to calibrate the relationship between signal intensity and allele dosage. SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, the relationship between signal intensity and allele dosage must be calibrated for each marker. We developed an improved computational method to automate this process, which is provided as the R package ClusterCall. In the training phase of the algorithm, hierarchical clustering within an F1 population is used to group samples with similar intensity values, and allele dosages are assigned to clusters based on expected segregation ratios. In the prediction phase, multiple F1 populations and the prediction set are clustered together, and the genotype for each cluster is the mode of the training set samples. A concordance metric, defined as the proportion of training set samples equal to the mode, can be used to eliminate unreliable markers and compare different algorithms. Across three potato families genotyped with an 8K SNP array, ClusterCall scored 5729 markers with at least 0.95 concordance (94.6% of its total), compared to 5325 with the software fitTetra (82.5% of its total). The three families were used to predict genotypes for 5218 SNPs in the SolCAP diversity panel, compared with 3521 SNPs in a previous study in which genotypes were called manually. One of the additional markers produced a significant association for vine maturity near a well-known causal locus on chromosome 5. In conclusion, when multiple F1 populations are available, ClusterCall is an efficient method for accurate, autotetraploid genotype calling that enables the use of SNP data for research and plant breeding.

  19. Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates

    Science.gov (United States)

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

    2015-11-01

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

  20. MULTILEVEL RECURRENT MODEL FOR HIERARCHICAL CONTROL OF COMPLEX REGIONAL SECURITY

    Directory of Open Access Journals (Sweden)

    Andrey V. Masloboev

    2014-11-01

    Full Text Available Subject of research. The research goal and scope are development of methods and software for mathematical and computer modeling of the regional security information support systems as multilevel hierarchical systems. Such systems are characterized by loosely formalization, multiple-aspect of descendent system processes and their interconnectivity, high level dynamics and uncertainty. The research methodology is based on functional-target approach and principles of multilevel hierarchical system theory. The work considers analysis and structural-algorithmic synthesis problem-solving of the multilevel computer-aided systems intended for management and decision-making information support in the field of regional security. Main results. A hierarchical control multilevel model of regional socio-economic system complex security has been developed. The model is based on functional-target approach and provides both formal statement and solving, and practical implementation of the automated information system structure and control algorithms synthesis problems of regional security management optimal in terms of specified criteria. An approach for intralevel and interlevel coordination problem-solving in the multilevel hierarchical systems has been proposed on the basis of model application. The coordination is provided at the expense of interconnection requirements satisfaction between the functioning quality indexes (objective functions, which are optimized by the different elements of multilevel systems. That gives the possibility for sufficient coherence reaching of the local decisions, being made on the different control levels, under decentralized decision-making and external environment high dynamics. Recurrent model application provides security control mathematical models formation of regional socioeconomic systems, functioning under uncertainty. Practical relevance. The model implementation makes it possible to automate synthesis realization of

  1. Hierarchical sets: analyzing pangenome structure through scalable set visualizations

    Science.gov (United States)

    2017-01-01

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

  2. A hierarchical artificial retina architecture

    Science.gov (United States)

    Parker, Alice C.; Azar, Adi N.

    2009-05-01

    Connectivity in the human retina is complex. Over one hundred million photoreceptors transduce light into electrical signals. These electrical signals are sent to the ganglion cells through amacrine and bipolar cells. Lateral connections involving horizontal and amacrine cells span throughout the outer plexiform layer and inner plexiform layer respectively. Horizontal cells are important for photoreceptor regulation by depolarizing them after an illumination occurs. Horizontal cells themselves form an electrical network that communicates by gap junctions, and these cells exhibit plasticity (change in behavior and structure) with respect to glycine receptors. The bipolar and amacrine cells transfer electrical signals from photoreceptors to the ganglion cells. Furthermore, amacrine cells are responsible for further processing the retinal image. Finally, the ganglion cells receive electrical signals from the bipolar and amacrine cells and will spike at a faster rate if there is a change in the overall intensity for a group of photoreceptors, sending a signal to the brain. Dramatic progress is being made with respect to retinal prostheses, raising hope for an entire synthetic retina in the future. We propose a bio-inspired 3D hierarchical pyramidal architecture for a synthetic retina that mimics the overall structure of the human retina. We chose to use a 3D architecture to facilitate connectivity among retinal cells, maintaining a hierarchical structure similar to that of the biological retina. The first layer of the architecture contains electronic circuits that model photoreceptors and horizontal cells. The second layer contains amacrine and bipolar electronic cells, and the third layer contains ganglion cells. Layer I has the highest number of cells, and layer III has the lowest number of cells, resulting in a pyramidal architecture. In our proposed architecture we intend to use photodetectors to transduce light into electrical signals. We propose to employ

  3. Hierarchical decision making for flood risk reduction

    DEFF Research Database (Denmark)

    Custer, Rocco; Nishijima, Kazuyoshi

    2013-01-01

    River flood events often cause large economic damages and casualties requiring stakeholders to manage flood risk. In flood prone areas, flood risk management can be achieved through a series hierarchically integrated protection structures, which together form a hierarchical flood protection system...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...... the hierarchical level on which risk reducing measures are most beneficial might change....

  4. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  5. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  6. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong

    2017-08-03

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

  7. Hierarchically porous carbon nanosheets from waste coffee grounds for supercapacitors.

    Science.gov (United States)

    Yun, Young Soo; Park, Min Hong; Hong, Sung Ju; Lee, Min Eui; Park, Yung Woo; Jin, Hyoung-Joon

    2015-02-18

    The nanostructure design of porous carbon-based electrode materials is key to improving the electrochemical performance of supercapacitors. In this study, hierarchically porous carbon nanosheets (HP-CNSs) were fabricated using waste coffee grounds by in situ carbonization and activation processes using KOH. Despite the simple synthesis process, the HP-CNSs had a high aspect ratio nanostructure (∼20 nm thickness to several micrometers in lateral size), a high specific surface area of 1945.7 m(2) g(-1), numerous heteroatoms, and good electrical transport properties, as well as hierarchically porous characteristics (0.5-10 nm in size). HP-CNS-based supercapacitors showed a specific energy of 35.4 Wh kg(-1) at 11250 W kg(-1) and of 23 Wh kg(-1) for a 3 s charge/discharge current rate corresponding to a specific power of 30000 W kg(-1). Additionally, the HP-CNS supercapacitors demonstrated good cyclic performance over 5000 cycles.

  8. HIERARCHICAL MOTION SYNTHESIS OF MAGNETICALLY LEVITATED TRAINS

    Directory of Open Access Journals (Sweden)

    V. O. Poliakov

    2009-05-01

    Full Text Available The technique of hierarchic construction of magnetic levitated train motion is offered. Its advantages and expediency of three-leveled system regulator were grounded. The global algorithm of its work is constructed.

  9. HIERARCHICAL ORGANIZATION OF INFORMATION, IN RELATIONAL DATABASES

    Directory of Open Access Journals (Sweden)

    Demian Horia

    2008-05-01

    Full Text Available In this paper I will present different types of representation, of hierarchical information inside a relational database. I also will compare them to find the best organization for specific scenarios.

  10. HIERARCHICAL ORGANIZATION OF INFORMATION, IN RELATIONAL DATABASES

    OpenAIRE

    Demian Horia

    2008-01-01

    In this paper I will present different types of representation, of hierarchical information inside a relational database. I also will compare them to find the best organization for specific scenarios.

  11. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau

    2017-08-03

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures extending from the HNWs.

  12. Hierarchical DSE for multi-ASIP platforms

    DEFF Research Database (Denmark)

    Micconi, Laura; Corvino, Rosilde; Gangadharan, Deepak

    2013-01-01

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

  13. Modular networks with hierarchical organization: The dynamical ...

    Indian Academy of Sciences (India)

    constraint optimization as shown by us previously. Keywords. Modular network; hierarchical organization; stability; robustness. PACS Nos 89.75.Hc; 05.45.-a; 89.75.Fb. 1. Introduction. Structural patterns in complex networks occurring in biological, ...

  14. Zeolitic materials with hierarchical porous structures.

    Science.gov (United States)

    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. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Dynamic hierarchical algorithm for accelerated microfossil identification

    Science.gov (United States)

    Wong, Cindy M.; Joseph, Dileepan

    2015-02-01

    Marine microfossils provide a useful record of the Earth's resources and prehistory via biostratigraphy. To study Hydrocarbon reservoirs and prehistoric climate, geoscientists visually identify the species of microfossils found in core samples. Because microfossil identification is labour intensive, automation has been investigated since the 1980s. With the initial rule-based systems, users still had to examine each specimen under a microscope. While artificial neural network systems showed more promise for reducing expert labour, they also did not displace manual identification for a variety of reasons, which we aim to overcome. In our human-based computation approach, the most difficult step, namely taxon identification is outsourced via a frontend website to human volunteers. A backend algorithm, called dynamic hierarchical identification, uses unsupervised, supervised, and dynamic learning to accelerate microfossil identification. Unsupervised learning clusters specimens so that volunteers need not identify every specimen during supervised learning. Dynamic learning means interim computation outputs prioritize subsequent human inputs. Using a dataset of microfossils identified by an expert, we evaluated correct and incorrect genus and species rates versus simulated time, where each specimen identification defines a moment. The proposed algorithm accelerated microfossil identification effectively, especially compared to benchmark results obtained using a k-nearest neighbour method.

  16. Non-hierarchical Structures: How to Model and Index Overlaps?

    OpenAIRE

    Hasibi, Faegheh; Bratsberg, Svein Erik

    2014-01-01

    Overlap is a common phenomenon seen when structural components of a digital object are neither disjoint nor nested inside each other. Overlapping components resist reduction to a structural hierarchy, and tree-based indexing and query processing techniques cannot be used for them. Our solution to this data modeling problem is TGSA (Tree-like Graph for Structural Annotations), a novel extension of the XML data model for non-hierarchical structures. We introduce an algorithm for constructing TG...

  17. Accelerated Hierarchical Collision Detection for Simulation using CUDA

    DEFF Research Database (Denmark)

    Jørgensen, Jimmy Alison; Fugl, Andreas Rune; Petersen, Henrik Gordon

    2011-01-01

    In this article we present a GPU accelerated, hybrid, narrow phase collision detection algorithm for simulation purposes. The algorithm is based on hierarchical bounding volume tree structures of oriented bounding boxes (OBB) that in the past has shown to be efficient for collision detection...... exploiting coarse-grained parallelism in grasping and stacking simulations, requiring all-contacts resolu- tion, a performance gain of up to 7x compared to the collision detection package PQP is obtained....

  18. A hierarchical procedure for calculation of risk importance measures

    International Nuclear Information System (INIS)

    Poern, K.; Dinsmore, S.C.

    1987-01-01

    Starting with a general importance definition based on conditional probabilities, a hierarchical process for calculating risk importance measures from a PSA's numerical results is developed. By the appropriate choice of events in the general definition, measures such as the risk achievement worth and the risk reduction worth can be calculated without requantifying the PSA's models. Required approximations are clearly defined and the subsequent constraints on the applicability of the process discussed. (orig.)

  19. A hierarchical procedure for calculation of risk importance measures

    International Nuclear Information System (INIS)

    Poern, K.; Dinsmore, S.

    1986-01-01

    Starting with a general importance definition based on conditional probabilities, a hierarchical process for calculating such measures from a PRA's numerical results is developed. By the appropriate choice of events in the general definition, measures such as the risk achievement worth and the risk reduction worth can be calculated without requantifying the PRA models. Required approximations are clearly defined and the subsequent constraints on the applicability of the process discussed

  20. Algorithm of parallel: hierarchical transformation and its implementation on FPGA

    Science.gov (United States)

    Timchenko, Leonid I.; Petrovskiy, Mykola S.; Kokryatskay, Natalia I.; Barylo, Alexander S.; Dembitska, Sofia V.; Stepanikuk, Dmytro S.; Suleimenov, Batyrbek; Zyska, Tomasz; Uvaysova, Svetlana; Shedreyeva, Indira

    2017-08-01

    In this paper considers the algorithm of laser beam spots image classification in atmospheric-optical transmission systems. It discusses the need for images filtering using adaptive methods, using, for example, parallel-hierarchical networks. The article also highlights the need to create high-speed memory devices for such networks. Implementation and simulation results of the developed method based on the PLD are demonstrated, which shows that the presented method gives 15-20% better prediction results than similar methods.

  1. A Hierarchical Visualization Analysis Model of Power Big Data

    Science.gov (United States)

    Li, Yongjie; Wang, Zheng; Hao, Yang

    2018-01-01

    Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

  2. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures.

    Science.gov (United States)

    Schargott, M

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  3. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    Energy Technology Data Exchange (ETDEWEB)

    Schargott, M [Institute of Mechanics, Technische Universitaet Berlin, Strd 17 Juni 135, 10623 Berlin (Germany)], E-mail: martin.schargott@tu-berlin.de

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  4. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    International Nuclear Information System (INIS)

    Schargott, M

    2009-01-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface

  5. Translating Management Practices in Hierarchical Organizations

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe

    This study examines how translators in a hierarchical context approach the translation of management practices. Although current translation theory and research emphasize the importance of contextual factors in translation processes, little research has investigated how strongly hierarchical...... structures affect translators’ approaches taken towards management ideas. This paper reports the findings from a longitudinal case study of the translation of Leadership Pipeline in a Danish fire department and how the translators’ approach changed over time from a modifying to a reproducing mode. The study...

  6. Hierarchical organization versus self-organization

    OpenAIRE

    Busseniers, Evo

    2014-01-01

    In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

  7. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

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

    2017-01-01

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

  8. Hierarchical Nanoceramics for Industrial Process Sensors

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-07-15

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

  9. HIERARCHICAL FRAGMENTATION OF THE ORION MOLECULAR FILAMENTS

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Satoko; Ho, Paul T. P.; Su, Yu-Nung [Academia Sinica Institute of Astronomy and Astrophysics, P.O. Box 23-141, Taipei 10617, Taiwan (China); Teixeira, Paula S. [Institut fuer Astrophysik, Universitaet Wien, Tuerkenschanzstrasse 17, A-1180, Wien (Austria); Zapata, Luis A., E-mail: satoko_t@asiaa.sinica.edu.tw [Centro de Radioastronomia y Astrofisica, Universidad Nacional Autonoma de Mexico, Morelia, Michoacan 58090 (Mexico)

    2013-01-20

    We present a high angular resolution map of the 850 {mu}m continuum emission of the Orion Molecular Cloud-3 (OMC 3) obtained with the Submillimeter Array (SMA); the map is a mosaic of 85 pointings covering an approximate area of 6.'5 Multiplication-Sign 2.'0 (0.88 Multiplication-Sign 0.27 pc). We detect 12 spatially resolved continuum sources, each with an H{sub 2} mass between 0.3-5.7 M {sub Sun} and a projected source size between 1400-8200 AU. All the detected sources are on the filamentary main ridge (n{sub H{sub 2}}{>=}10{sup 6} cm{sup -3}), and analysis based on the Jeans theorem suggests that they are most likely gravitationally unstable. Comparison of multi-wavelength data sets indicates that of the continuum sources, 6/12 (50%) are associated with molecular outflows, 8/12 (67%) are associated with infrared sources, and 3/12 (25%) are associated with ionized jets. The evolutionary status of these sources ranges from prestellar cores to protostar phase, confirming that OMC-3 is an active region with ongoing embedded star formation. We detect quasi-periodical separations between the OMC-3 sources of Almost-Equal-To 17''/0.035 pc. This spatial distribution is part of a large hierarchical structure that also includes fragmentation scales of giant molecular cloud ( Almost-Equal-To 35 pc), large-scale clumps ( Almost-Equal-To 1.3 pc), and small-scale clumps ( Almost-Equal-To 0.3 pc), suggesting that hierarchical fragmentation operates within the Orion A molecular cloud. The fragmentation spacings are roughly consistent with the thermal fragmentation length in large-scale clumps, while for small-scale cores it is smaller than the local fragmentation length. These smaller spacings observed with the SMA can be explained by either a helical magnetic field, cloud rotation, or/and global filament collapse. Finally, possible evidence for sequential fragmentation is suggested in the northern part of the OMC-3 filament.

  10. A Review on the Fabrication of Hierarchical ZnO Nanostructures for Photocatalysis Application

    Directory of Open Access Journals (Sweden)

    Yi Xia

    2016-11-01

    Full Text Available Semiconductor photocatalysis provides potential solutions for many energy and environmental-related issues. Recently, various semiconductors with hierarchical nanostructures have been fabricated to achieve efficient photocatalysts owing to their multiple advantages, such as high surface area, porous structures, as well as enhanced light harvesting. ZnO has been widely investigated and considered as the most promising alternative photocatalyst to TiO2. Herein, we present a review on the fabrication methods, growth mechanisms and photocatalytic applications of hierarchical ZnO nanostructures. Various synthetic strategies and growth mechanisms, including multistep sequential growth routes, template-based synthesis, template-free self-organization and precursor or self-templating strategies, are highlighted. In addition, the fabrication of multicomponent ZnO-based nanocomposites with hierarchical structures is also included. Finally, the application of hierarchical ZnO nanostructures and nanocomposites in typical photocatalytic reactions, such as pollutant degradation and H2 evolution, is reviewed.

  11. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    DEFF Research Database (Denmark)

    Custer, Rocco

    measures, allows identifying flexible and robust flood risk management strategies. Based on it, this thesis investigates hierarchical flood protection systems, which encompass two, or more, hierarchically integrated flood protection structures on different spatial scales (e.g. dikes, local flood barriers......Societies around the world are faced with flood risk, prompting authorities and decision makers to manage risk to protect population and assets. With climate change, urbanisation and population growth, flood risk changes constantly, requiring flood risk management strategies that are flexible...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

  12. Hierarchical nanostructure and synergy of multimolecular signalling complexes

    Science.gov (United States)

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

    2016-07-01

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

  13. Poincaré Embeddings for Learning Hierarchical Representations

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Abstracts: Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, while complex symbolic datasets often exhibit a latent hierarchical structure, state-of-the-art methods typically do not account for this property. In this talk, I will discuss a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an n-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows us to learn parsimonious representations of symbolic data by simultaneously capturing hierarchy and similarity. We introduce an efficient algorithm to learn the embeddings based on Riemannian optimization and show experimentally that Poincaré embeddings outperform Euclidean embeddings significantly on data with latent hierarchies, both in terms of representation capacity and in terms of generalization ability.      &...

  14. Nonlinear robust hierarchical control for nonlinear uncertain systems

    Directory of Open Access Journals (Sweden)

    Leonessa Alexander

    1999-01-01

    Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

  15. Hierarchical aggregation for information visualization: overview, techniques, and design guidelines.

    Science.gov (United States)

    Elmqvist, Niklas; Fekete, Jean-Daniel

    2010-01-01

    We present a model for building, visualizing, and interacting with multiscale representations of information visualization techniques using hierarchical aggregation. The motivation for this work is to make visual representations more visually scalable and less cluttered. The model allows for augmenting existing techniques with multiscale functionality, as well as for designing new visualization and interaction techniques that conform to this new class of visual representations. We give some examples of how to use the model for standard information visualization techniques such as scatterplots, parallel coordinates, and node-link diagrams, and discuss existing techniques that are based on hierarchical aggregation. This yields a set of design guidelines for aggregated visualizations. We also present a basic vocabulary of interaction techniques suitable for navigating these multiscale visualizations.

  16. A new hierarchical method to find community structure in networks

    Science.gov (United States)

    Saoud, Bilal; Moussaoui, Abdelouahab

    2018-04-01

    Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

  17. Fluorocarbon adsorption in hierarchical porous frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Motkuri, RK; Annapureddy, HVR; Vijaykumar, M; Schaef, HT; Martin, PF; McGrail, BP; Dang, LX; Krishna, R; Thallapally, PK

    2014-07-09

    Metal-organic frameworks comprise an important class of solid-state materials and have potential for many emerging applications such as energy storage, separation, catalysis and bio-medical. Here we report the adsorption behaviour of a series of fluorocarbon derivatives on a set of microporous and hierarchical mesoporous frameworks. The microporous frameworks show a saturation uptake capacity for dichlorodifluoromethane of >4 mmol g(-1) at a very low relative saturation pressure (P/P-o) of 0.02. In contrast, the mesoporous framework shows an exceptionally high uptake capacity reaching >14 mmol g(-1) at P/P-o of 0.4. Adsorption affinity in terms of mass loading and isosteric heats of adsorption is found to generally correlate with the polarizability and boiling point of the refrigerant, with dichlorodifluoromethane >chlorodifluoromethane >chlorotrifluoromethane >tetrafluoromethane >methane. These results suggest the possibility of exploiting these sorbents for separation of azeotropic mixtures of fluorocarbons and use in eco-friendly fluorocarbon-based adsorption cooling.

  18. AUTOMATIC CONSTRUCTION OF HIERARCHICAL ROAD NETWORKS

    Directory of Open Access Journals (Sweden)

    W. Yang

    2016-06-01

    Full Text Available 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.

  19. Fast approximate hierarchical clustering using similarity heuristics

    Directory of Open Access Journals (Sweden)

    Kull Meelis

    2008-09-01

    Full Text Available Abstract Background Agglomerative hierarchical clustering (AHC is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that all pairwise distances between data objects must be known. With ever-increasing data sizes this quadratic complexity poses problems that cannot be overcome by simply waiting for faster computers. Results We propose an approximate AHC algorithm HappieClust which can output a biologically meaningful clustering of a large dataset more than an order of magnitude faster than full AHC algorithms. The key to the algorithm is to limit the number of calculated pairwise distances to a carefully chosen subset of all possible distances. We choose distances using a similarity heuristic based on a small set of pivot objects. The heuristic efficiently finds pairs of similar objects and these help to mimic the greedy choices of full AHC. Quality of approximate AHC as compared to full AHC is studied with three measures. The first measure evaluates the global quality of the achieved clustering, while the second compares biological relevance using enrichment of biological functions in every subtree of the clusterings. The third measure studies how well the contents of subtrees are conserved between the clusterings. Conclusion The HappieClust algorithm is well suited for large-scale gene expression visualization and analysis both on personal computers as well as public online web applications. The software is available from the URL http://www.quretec.com/HappieClust

  20. Fluorocarbon adsorption in hierarchical porous frameworks

    Science.gov (United States)

    Motkuri, Radha Kishan; Annapureddy, Harsha V. R.; Vijaykumar, M.; Schaef, H. Todd; Martin, Paul F.; McGrail, B. Peter; Dang, Liem X.; Krishna, Rajamani; Thallapally, Praveen K.

    2014-07-01

    Metal-organic frameworks comprise an important class of solid-state materials and have potential for many emerging applications such as energy storage, separation, catalysis and bio-medical. Here we report the adsorption behaviour of a series of fluorocarbon derivatives on a set of microporous and hierarchical mesoporous frameworks. The microporous frameworks show a saturation uptake capacity for dichlorodifluoromethane of >4 mmol g-1 at a very low relative saturation pressure (P/Po) of 0.02. In contrast, the mesoporous framework shows an exceptionally high uptake capacity reaching >14 mmol g-1 at P/Po of 0.4. Adsorption affinity in terms of mass loading and isosteric heats of adsorption is found to generally correlate with the polarizability and boiling point of the refrigerant, with dichlorodifluoromethane >chlorodifluoromethane >chlorotrifluoromethane >tetrafluoromethane >methane. These results suggest the possibility of exploiting these sorbents for separation of azeotropic mixtures of fluorocarbons and use in eco-friendly fluorocarbon-based adsorption cooling.

  1. Hierarchical Bayesian models of subtask learning.

    Science.gov (United States)

    Anglim, Jeromy; Wynton, Sarah K A

    2015-07-01

    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 task, which logged participant actions, enabling measurement of strategy use and subtask performance. Model comparison was performed using deviance information criterion (DIC), posterior predictive checks, plots of model fits, and model recovery simulations. Results showed that although learning tended to be monotonically decreasing and decelerating, and approaching an asymptote for all subtasks, there was substantial inconsistency in learning curves both at the group- and individual-levels. This inconsistency was most apparent when constraining both the rate and the ratio of learning to asymptote to be equal across subtasks, thereby giving learning curves only 1 parameter for scaling. The inclusion of 6 strategy covariates provided improved prediction of subtask performance capturing different subtask learning processes and subtask trade-offs. In addition, strategy use partially explained the inconsistency in subtask learning. Overall, the model provided a more nuanced representation of how complex tasks can be decomposed in terms of simpler learning mechanisms. (c) 2015 APA, all rights reserved.

  2. Mitigating Herding in Hierarchical Crowdsourcing Networks.

    Science.gov (United States)

    Yu, Han; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lesser, Victor R; Yang, Qiang

    2016-12-05

    Hierarchical crowdsourcing networks (HCNs) provide a useful mechanism for social mobilization. However, spontaneous evolution of the complex resource allocation dynamics can lead to undesirable herding behaviours in which a small group of reputable workers are overloaded while leaving other workers idle. Existing herding control mechanisms designed for typical crowdsourcing systems are not effective in HCNs. In order to bridge this gap, we investigate the herding dynamics in HCNs and propose a Lyapunov optimization based decision support approach - the Reputation-aware Task Sub-delegation approach with dynamic worker effort Pricing (RTS-P) - with objective functions aiming to achieve superlinear time-averaged collective productivity in an HCN. By considering the workers' current reputation, workload, eagerness to work, and trust relationships, RTS-P provides a systematic approach to mitigate herding by helping workers make joint decisions on task sub-delegation, task acceptance, and effort pricing in a distributed manner. It is an individual-level decision support approach which results in the emergence of productive and robust collective patterns in HCNs. High resolution simulations demonstrate that RTS-P mitigates herding more effectively than state-of-the-art approaches.

  3. Bayesian Hierarchical Grouping: perceptual grouping as mixture estimation

    Science.gov (United States)

    Froyen, Vicky; Feldman, Jacob; Singh, Manish

    2015-01-01

    We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian Hierarchical Grouping (BHG). In BHG we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters of the mixture components that generated the image, including estimating which image elements are “owned” by which objects. We present a tractable implementation of the framework, based on the hierarchical clustering approach of Heller and Ghahramani (2005). We illustrate it with examples drawn from a number of classical perceptual grouping problems, including dot clustering, contour integration, and part decomposition. Our approach yields an intuitive hierarchical representation of image elements, giving an explicit decomposition of the image into mixture components, along with estimates of the probability of various candidate decompositions. We show that BHG accounts well for a diverse range of empirical data drawn from the literature. Because BHG provides a principled quantification of the plausibility of grouping interpretations over a wide range of grouping problems, we argue that it provides an appealing unifying account of the elusive Gestalt notion of Prägnanz. PMID:26322548

  4. Growth Mechanism of Pumpkin-Shaped Vaterite Hierarchical Structures

    Science.gov (United States)

    Ma, Guobin; Xu, Yifei; Wang, Mu

    2015-03-01

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

  5. Hierarchical sliding mode control for under-actuated cranes design, analysis and simulation

    CERN Document Server

    Qian, Dianwei

    2015-01-01

    This book reports on the latest developments in sliding mode overhead crane control, presenting novel research ideas and findings on sliding mode control (SMC), hierarchical SMC and compensator design-based hierarchical sliding mode. The results, which were previously scattered across various journals and conference proceedings, are now presented in a systematic and unified form. The book will be of interest to researchers, engineers and graduate students in control engineering and mechanical engineering who want to learn the methods and applications of SMC.

  6. Design of Hierarchically Cut Hinges for Highly Stretchable and Reconfigurable Metamaterials with Enhanced Strength.

    Science.gov (United States)

    Tang, Yichao; Lin, Gaojian; Han, Lin; Qiu, Songgang; Yang, Shu; Yin, Jie

    2015-11-25

    Applying hierarchical cuts to thin sheets of elastomer generates super-stretchable and reconfigurable metamaterials, exhibiting highly nonlinear stress-strain behaviors and tunable phononic bandgaps. The cut concept fails on brittle thin sheets due to severe stress concentration in the rotating hinges. By engineering the local hinge shapes and global hierarchical structure, cut-based reconfigurable metamaterials with largely enhanced strength are realized. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Hierarchical regression for analyses of multiple outcomes.

    Science.gov (United States)

    Richardson, David B; Hamra, Ghassan B; MacLehose, Richard F; Cole, Stephen R; Chu, Haitao

    2015-09-01

    In cohort mortality studies, there often is interest in associations between an exposure of primary interest and mortality due to a range of different causes. A standard approach to such analyses involves fitting a separate regression model for each type of outcome. However, the statistical precision of some estimated associations may be poor because of sparse data. In this paper, we describe a hierarchical regression model for estimation of parameters describing outcome-specific relative rate functions and associated credible intervals. The proposed model uses background stratification to provide flexible control for the outcome-specific associations of potential confounders, and it employs a hierarchical "shrinkage" approach to stabilize estimates of an exposure's associations with mortality due to different causes of death. The approach is illustrated in analyses of cancer mortality in 2 cohorts: a cohort of dioxin-exposed US chemical workers and a cohort of radiation-exposed Japanese atomic bomb survivors. Compared with standard regression estimates of associations, hierarchical regression yielded estimates with improved precision that tended to have less extreme values. The hierarchical regression approach also allowed the fitting of models with effect-measure modification. The proposed hierarchical approach can yield estimates of association that are more precise than conventional estimates when one wishes to estimate associations with multiple outcomes. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

    Directory of Open Access Journals (Sweden)

    Chuan-Sheng Wu

    2015-07-01

    Full Text Available 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.

  9. Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

    Science.gov (United States)

    Bai, Hao; Zhang, Xi-wen

    2017-06-01

    While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

  10. Improved gravitation field algorithm and its application in hierarchical clustering.

    Directory of Open Access Journals (Sweden)

    Ming Zheng

    Full Text Available 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.

  11. Music emotion detection using hierarchical sparse kernel machines.

    Science.gov (United States)

    Chin, Yu-Hao; Lin, Chang-Hong; Siahaan, Ernestasia; Wang, Jia-Ching

    2014-01-01

    For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target) side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM) with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET) curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.

  12. Hierarchical morphological segmentation for image sequence coding.

    Science.gov (United States)

    Salembier, P; Pardas, M

    1994-01-01

    This paper deals with a hierarchical morphological segmentation algorithm for image sequence coding. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features such as size, shape, contrast, or connectivity that can be considered as segmentation-oriented features. The algorithm follows a top-down procedure. It first takes into account the global information and produces a coarse segmentation, that is, with a small number of regions. Then, the segmentation quality is improved by introducing regions corresponding to more local information. The algorithm, considering sequences as being functions on a 3-D space, directly segments 3-D regions. A 3-D approach is used to get a segmentation that is stable in time and to directly solve the region correspondence problem. Each segmentation stage relies on four basic steps: simplification, marker extraction, decision, and quality estimation. The simplification removes information from the sequence to make it easier to segment. Morphological filters based on partial reconstruction are proven to be very efficient for this purpose, especially in the case of sequences. The marker extraction identifies the presence of homogeneous 3-D regions. It is based on constrained flat region labeling and morphological contrast extraction. The goal of the decision is to precisely locate the contours of regions detected by the marker extraction. This decision is performed by a modified watershed algorithm. Finally, the quality estimation concentrates on the coding residue, all the information about the 3-D regions that have not been properly segmented and therefore coded. The procedure allows the introduction of the texture and contour coding schemes within the segmentation algorithm. The coding residue is transmitted to the next segmentation stage to improve the segmentation and coding quality. Finally, segmentation and coding examples are presented to show the validity and interest of

  13. [Comparative hierarchic structure of the genetic language].

    Science.gov (United States)

    Ratner, V A

    1993-05-01

    The genetical texts and genetic language are built according to hierarchic principle and contain no less than 6 levels of coding sequences, separated by marks of punctuation, separation and indication: codons, cistrons, scriptons, replicons, linkage groups, genomes. Each level has all the attributes of the language. This hierarchic system expresses some general properties and regularities. The rules of genetic language being determined, the variability of genetical texts is generated by block-modular combinatorics on each level. Between levels there are some intermediate sublevels and module types capable of being combined. The genetic language is compared with two different independent linguistic systems: human natural languages and artificial programming languages. Genetic language is a natural one by its origin, but it is a typical technical language of the functioning genetic regulatory system--by its predestination. All three linguistic systems under comparison have evident similarity of the organization principles and hierarchical structures. This argues for similarity of their principles of appearance and evolution.

  14. Hierarchical machining materials and their performance

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Levashov, Evgeny

    2016-01-01

    Machining is an important technological process in many areas of industry. The efficiency of machining determines the quality of many industrial products. Machining efficiency and cost depend on the properties, strength, and microstructure of the machining materials. One of the promising ways...... to increase the reliability and wear resistance of machining tools is the development and use of hierarchical machining materials. In the area of machining materials, designed typically as binder/reinforcement composites, hierarchical structures are realized as lower-scale secondary reinforcements (such...... as nanoparticles in the binder, or polycrystalline, aggregate-like reinforcements, also at several scale levels). Such materials can ensure better productivity, efficiency, and lower costs of drilling, cutting, grinding, and other technological processes. This article reviews the main groups of hierarchical...

  15. Hierarchical capillary adhesion of microcantilevers or hairs

    International Nuclear Information System (INIS)

    Liu Jianlin; Feng Xiqiao; Xia Re; Zhao Hongping

    2007-01-01

    As a result of capillary forces, animal hairs, carbon nanotubes or nanowires of a periodically or randomly distributed array often assemble into hierarchical structures. In this paper, the energy method is adopted to analyse the capillary adhesion of microsized hairs, which are modelled as clamped microcantilevers wetted by liquids. The critical conditions for capillary adhesion of two hairs, three hairs or two bundles of hairs are derived in terms of Young's contact angle, elastic modulus and geometric sizes of the beams. Then, the hierarchical capillary adhesion of hairs is addressed. It is found that for multiple hairs or microcantilevers, the system tends to take a hierarchical structure as a result of the minimization of the total potential energy of the system. The level number of structural hierarchy increases with the increase in the number of hairs if they are sufficiently long. Additionally, we performed experiments to verify our theoretical solutions for the adhesion of microbeams

  16. Hierarchical Micro-Nano Coatings by Painting

    Science.gov (United States)

    Kirveslahti, Anna; Korhonen, Tuulia; Suvanto, Mika; Pakkanen, Tapani A.

    2016-03-01

    In this paper, the wettability properties of coatings with hierarchical surface structures and low surface energy were studied. Hierarchically structured coatings were produced by using hydrophobic fumed silica nanoparticles and polytetrafluoroethylene (PTFE) microparticles as additives in polyester (PES) and polyvinyldifluoride (PVDF). These particles created hierarchical micro-nano structures on the paint surfaces and lowered or supported the already low surface energy of the paint. Two standard application techniques for paint application were employed and the presented coatings are suitable for mass production and use in large surface areas. By regulating the particle concentrations, it was possible to modify wettability properties gradually. Highly hydrophobic surfaces were achieved with the highest contact angle of 165∘. Dynamic contact angle measurements were carried out for a set of selected samples and low hysteresis was obtained. Produced coatings possessed long lasting durability in the air and in underwater conditions.

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

    Science.gov (United States)

    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. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Hierarchical Sheet-on-Sheet ZnIn2S4/g-C3N4 Heterostructure with Highly Efficient Photocatalytic H2 production Based on Photoinduced Interfacial Charge Transfer

    OpenAIRE

    Zhang, Zhenyi; Liu, Kuichao; Feng, Zhiqing; Bao, Yanan; Dong, Bin

    2016-01-01

    We have realized in-situ growth of ultrathin ZnIn2S4 nanosheets on the sheet-like g-C3N4 surfaces to construct a ?sheet-on-sheet? hierarchical heterostructure. The as-synthesized ZnIn2S4/g-C3N4 heterojunction nanosheets exhibit remarkably enhancement on the photocatalytic activity for H2 production. This enhanced photoactivity is mainly attributed to the efficient interfacial transfer of photoinduced electrons and holes from g-C3N4 to ZnIn2S4 nanosheets, resulting in the decreased charge reco...

  19. Dual hierarchical biomimic superhydrophobic surface with three energy states

    Science.gov (United States)

    Chen, Ming-Hung; Hsu, Tsung-Hsing; Chuang, Yun-Ju; Tseng, Fan-Gang

    2009-07-01

    A low hysteresis surface prepared by two-length-scaled hierarchical textures to mimic the Lotus effect is proposed. The fabricated textures incorporate self-masked nanorods on microextrusions. A high static contact angle (160°) and low hysteresis (˜2.7°) are obtained and comparable to the surface properties of a natural lotus leaf. The stability of hydrophobicity is described with respect to three energy states (nonwetting, microwetting, and nanowetting) based on dynamic contact angle analysis by droplet impinging onto the surface. The estimated texture-induced energy barrier based on the principle of energy conservation is in good agreement to those estimated from Laplace's law.

  20. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  1. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

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

  2. Hierarchical control of electron-transfer

    DEFF Research Database (Denmark)

    Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis

    1997-01-01

    In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

  3. Comparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site

    Science.gov (United States)

    Gavish, Yoni; O'Connell, Jerome; Marsh, Charles J.; Tarantino, Cristina; Blonda, Palma; Tomaselli, Valeria; Kunin, William E.

    2018-02-01

    The increasing need for high quality Habitat/Land-Cover (H/LC) maps has triggered considerable research into novel machine-learning based classification models. In many cases, H/LC classes follow pre-defined hierarchical classification schemes (e.g., CORINE), in which fine H/LC categories are thematically nested within more general categories. However, none of the existing machine-learning algorithms account for this pre-defined hierarchical structure. Here we introduce a novel Random Forest (RF) based application of hierarchical classification, which fits a separate local classification model in every branching point of the thematic tree, and then integrates all the different local models to a single global prediction. We applied the hierarchal RF approach in a NATURA 2000 site in Italy, using two land-cover (CORINE, FAO-LCCS) and one habitat classification scheme (EUNIS) that differ from one another in the shape of the class hierarchy. For all 3 classification schemes, both the hierarchical model and a flat model alternative provided accurate predictions, with kappa values mostly above 0.9 (despite using only 2.2-3.2% of the study area as training cells). The flat approach slightly outperformed the hierarchical models when the hierarchy was relatively simple, while the hierarchical model worked better under more complex thematic hierarchies. Most misclassifications came from habitat pairs that are thematically distant yet spectrally similar. In 2 out of 3 classification schemes, the additional constraints of the hierarchical model resulted with fewer such serious misclassifications relative to the flat model. The hierarchical model also provided valuable information on variable importance which can shed light into "black-box" based machine learning algorithms like RF. We suggest various ways by which hierarchical classification models can increase the accuracy and interpretability of H/LC classification maps.

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

    Science.gov (United States)

    Nitta, Tohru

    2017-10-01

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

  5. Crystal networks in silk fibrous materials: from hierarchical structure to ultra performance.

    Science.gov (United States)

    Nguyen, Anh Tuan; Huang, Qiao-Ling; Yang, Zhen; Lin, Naibo; Xu, Gangqin; Liu, Xiang Yang

    2015-03-01

    This review provides a comprehensive survey of the structural characteristics of crystal networks of silk soft fibrous materials in correlation with the macroscopic properties/performance and the network formation mechanisms. The correlation between the hierarchical mesoscopic structures and the mechanical properties of silk soft fibrous materials including silk fibroin hydrogels and naturally spun silk fibers are addressed based on the hierarchical crystal network models. Namely, two types of hierarchical networks are identified: the weak nanofibril-nanofibril interaction case (i.e., silk fibroin hydrogels), and the strong nanofibril-nanofibril interaction case (i.e., silk fibers). The macroscopic properties, i.e., the rheological/mechanical properties, can be controlled in terms of tuning different levels of hierarchical network structures by ultrasonication-induced gelation, introducing the initial nucleation centers, etc. Such controls take effect by different mesoscale assembly pathways, which are found to occur via different routes of the nucleation and growth processes. Furthermore, the hierarchical network model of soft fibrous materials can be applied to explain the superior mechanical properties and the unique strain-hardening behaviors of spider silk fibers within the framework of hierarchical breaking mechanism. Obviously, a knowledge of crystal networks will allow the prediction of the performance and engineering strategy of silk fibrous materials in generals. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

    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

  7. Hierarchical Optimization of Material and Structure

    DEFF Research Database (Denmark)

    Rodrigues, Helder C.; Guedes, Jose M.; Bendsøe, Martin P.

    2002-01-01

    This paper describes a hierarchical computational procedure for optimizing material distribution as well as the local material properties of mechanical elements. The local properties are designed using a topology design approach, leading to single scale microstructures, which may be restricted in...

  8. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    This may represent, for instance, the computational capacity of an internet router. Weighted networks carry more informa- tion and they are ... (i = 1, 2,...,M). The hub node in Gg always has label A. (4) Repeating the replication and connection steps, we obtain the weighted hierarchical networks. According to the weighted ...

  9. Widening the Schedulability Hierarchical Scheduling Systems

    DEFF Research Database (Denmark)

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

    2014-01-01

    This paper presents a compositional approach for schedula- bility analysis of hierarchical systems, which enables to prove more sys- tems schedulable by having richer and more detailed scheduling models. We use a lightweight method (statistical model checking) for design ex- ploration, easily ass...

  10. [Use of hierarchical models in nephrology].

    Science.gov (United States)

    Hogan, Julien; Couchoud, Cécile

    2014-07-01

    The use of hierarchical models in public health research is recently increasing in order to study all the factors explaining health outcomes. Thus, a better understanding of those models is needed first to identify questions that may be answered by using them and also to be aware of there limitations. On the one hand, hierarchical models managed to take into account the hierarchical structure of the data allowing a better estimation of the effects of the explanatory variables and the study of the impact of the "environment" (i.e.: neighborhood, treatment center, same clinical trial…) on health outcomes. They also allow the study of factors that may explain this impact of the "environment". On the other hand, they are more complex and a reflection on which determinant to include and how the environment is supposed to impact patients' health is much needed. This article reviews the rationale for using hierarchical models in public health research and especially in nephrologic research. We attempt to give a simple presentation of these models and to illustrate their results and potential use in the field of nephrology, as well as their limits. Copyright © 2014 Association Société de néphrologie. Published by Elsevier SAS. All rights reserved.

  11. Hierarchical control of aerial manipulation vehicle

    Science.gov (United States)

    Kannan, Somasundar; Bezzaoucha, Souad; Guzman, Serket Quintanar; Dentler, Jan; Olivares-Mendez, Miguel A.; Voos, Holger

    2017-01-01

    Hierarchical Control of the Aerial Manipulator is treated here. The modelling aspect of the highly coupled Aerial Vehicle which includes Quadrotor and manipulator is discussed. The control design to perform tasks in operational space is addressed along with stability discussion. The simulation studies are successfully performed to validate the design methodology.

  12. Hierarchical spatial organization of geographical networks

    Energy Technology Data Exchange (ETDEWEB)

    Travencolo, Bruno A N; Costa, Luciano da F [Cybernetic Vision Research Group, GII-IFSC, Universidade de Sao Paulo, Caixa Postal 369, Sao Carlos, SP, 13560-970 (Brazil)], E-mail: luciano@if.sc.usp.br

    2008-06-06

    In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

  13. Modular networks with hierarchical organization: The dynamical ...

    Indian Academy of Sciences (India)

    For both of these, we find that, increasing modularity or the number of hierarchical levels tends to increase the probability of instability. As both hierarchy and modularity are seen in natural systems, which necessarily have to be robust against environmental fluctuations, we conclude that additional constraints are necessary ...

  14. Hierarchical Broadcasting in the Future Mobile Internet

    NARCIS (Netherlands)

    Hesselman, C.E.W.; Eertink, E.H.; Fernandez, Milagros; Crnkovic, Ivica; Fohler, Gerhard; Griwodz, Carsten; Plagemann, Thomas; Gruenbacher, Paul

    2002-01-01

    We describe an architecture for the hierarchical distribution of multimedia broadcasts in the future mobile Internet. The architecture supports network as well as application-layer mobility solutions, and uses stream control functions that are influenced by available network resources, user-defined

  15. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    hierarchical network. Here, we focus on a particular case with the trap located at the node with the highest degree. We derive rigorous solution to the MFPT that characterizes the trapping process. Moreover ..... The weighted networks can mimic some real-world natural and social systems to some extent [20–22]. We focus ...

  16. Ultrafast Hierarchical OTDM/WDM Network

    Directory of Open Access Journals (Sweden)

    Hideyuki Sotobayashi

    2003-12-01

    Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

  17. Tanzania: A Hierarchical Cluster Analysis Approach | Ngaruko ...

    African Journals Online (AJOL)

    Using survey data from Kibondo district, west Tanzania, we use hierarchical cluster analysis to classify borrower farmers according to their borrowing behaviour into four distinctive clusters. The appreciation of the existence of heterogeneous farmer clusters is vital in forging credit delivery policies that are not only ...

  18. Types of Online Hierarchical Repository Structures

    Science.gov (United States)

    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…

  19. A hierarchical classification scheme of psoriasis images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    A two-stage hierarchical classification scheme of psoriasis lesion images is proposed. These images are basically composed of three classes: normal skin, lesion and background. The scheme combines conventional tools to separate the skin from the background in the first stage, and the lesion from...

  20. Hierarchical silica particles by dynamic multicomponent assembly

    DEFF Research Database (Denmark)

    Wu, Z. W.; Hu, Q. Y.; Pang, J. B.

    2005-01-01

    Abstract: Aerosol-assisted assembly of mesoporous silica particles with hierarchically controllable pore structure has been prepared using cetyltrimethylammonium bromide (CTAB) and poly(propylene oxide) (PPO, H[OCH(CH3)CH2],OH) as co-templates. Addition of the hydrophobic PPO significantly...

  1. Hierarchical regression analysis in structural Equation Modeling

    NARCIS (Netherlands)

    de Jong, P.F.

    1999-01-01

    In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main

  2. Hierarchical drivers of reef-fish metacommunity structure.

    Science.gov (United States)

    MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

    2009-01-01

    Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at

  3. Hierarchical Control for Smart Grids

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2011-01-01

    on one hand from varying consumption, and on the other hand by natural variations in power production e.g. from wind turbines. The high-level MPC problem is solved using quadratic optimisation, while the aggregator level can either involve quadratic optimisation or simple sorting-based min-max solutions...

  4. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  5. Hierarchical self-organization of non-cooperating individuals.

    Directory of Open Access Journals (Sweden)

    Tamás Nepusz

    Full Text Available Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.

  6. Hierarchical clustering techniques for image database organization and summarization

    Science.gov (United States)

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

    1998-10-01

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

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

    Science.gov (United States)

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

    2014-05-01

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

  8. Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

    DEFF Research Database (Denmark)

    He, W.; Min, D.D.; Zhang, X.D.

    2014-01-01

    Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...... and products of catalytic reactions can freely diffuse through open mesopores (2–40 nm). The formation mechanism of hierarchically structured porous bioactive glasses, the immobilization mechanism of enzyme and the catalysis mechanism of immobilized enzyme are then discussed. The novel nanostructure...

  9. Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles Management System

    DEFF Research Database (Denmark)

    Hu, Junjie; Si, Chengyong; Lind, Morten

    2016-01-01

    In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control...... system where the upper level controller directly controls the lower level subordinated nodes, this study aims to integrate two common indirect control methods:market-based control and price-based control into the hierarchical electric vehicles management system. Specifically, on the lower level...... of the hierarchy, the FOs coordinate the charging behaviors of their EV users using a price-based control method. A parametric utility model is used on the lower level to characterize price elasticity of electric vehicles and thus used by the FO to coordinate the individual EV charging. On the upper level...

  10. Spatial hierarchical Bayes estimation of mean years of schooling

    Science.gov (United States)

    Wahyuni, Dwi A. S.; Wage, Sutarman; Darnius, Open

    2018-01-01

    A spatial hierarchical bayes for estimating mean years of schooling district level is proposed. We developed spatial hierarchical bayes within a Monte Carlo simulation study with R software. The simulation generated posterior distribution invers gamma. The spatial correlation used rook contiguity for each district. Hierarchical bayes method with spatial weighted provides smaller relative bias and relative root mean square.

  11. Global considerations in hierarchical clustering reveal meaningful patterns in data.

    Science.gov (United States)

    Varshavsky, Roy; Horn, David; Linial, Michal

    2008-05-21

    A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide insights in erroneous and missed annotations.

  12. Global considerations in hierarchical clustering reveal meaningful patterns in data.

    Directory of Open Access Journals (Sweden)

    Roy Varshavsky

    Full Text Available BACKGROUND: A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative algorithm is used as a default and is often the only method applied. METHODOLOGY/PRINCIPAL FINDINGS: We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive, or glocal (global-local algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. CONCLUSIONS: Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can

  13. Hierarchical resilience with lightweight threads

    International Nuclear Information System (INIS)

    Wheeler, Kyle Bruce

    2011-01-01

    This paper proposes methodology for providing robustness and resilience for a highly threaded distributed- and shared-memory environment based on well-defined inputs and outputs to lightweight tasks. These inputs and outputs form a failure 'barrier', allowing tasks to be restarted or duplicated as necessary. These barriers must be expanded based on task behavior, such as communication between tasks, but do not prohibit any given behavior. One of the trends in high-performance computing codes seems to be a trend toward self-contained functions that mimic functional programming. Software designers are trending toward a model of software design where their core functions are specified in side-effect free or low-side-effect ways, wherein the inputs and outputs of the functions are well-defined. This provides the ability to copy the inputs to wherever they need to be - whether that's the other side of the PCI bus or the other side of the network - do work on that input using local memory, and then copy the outputs back (as needed). This design pattern is popular among new distributed threading environment designs. Such designs include the Barcelona STARS system, distributed OpenMP systems, the Habanero-C and Habanero-Java systems from Vivek Sarkar at Rice University, the HPX/ParalleX model from LSU, as well as our own Scalable Parallel Runtime effort (SPR) and the Trilinos stateless kernels. This design pattern is also shared by CUDA and several OpenMP extensions for GPU-type accelerators (e.g. the PGI OpenMP extensions).

  14. Logistic versus hierarchical modeling: an analysis of a statewide inpatient sample.

    Science.gov (United States)

    Alexandrescu, Roxana; Jen, Min-Hua; Bottle, Alex; Jarman, Brian; Aylin, Paul

    2011-09-01

    Although logistic regression is traditionally used to calculate hospital standardized mortality ratio (HSMR), it ignores the hierarchical structure of the data that can exist within a given database. Hierarchical models allow examination of the effect of data clustering on outcomes. Traditional logistic regression and random intercepts fixed slopes hierarchical models were fitted to a dataset of patients hospitalized between 2005 and 2007 in Massachusetts. We compared the observed to expected (O/E) in-hospital death ratios between the 2 modeling techniques, a restricted HSMR using only those diagnosis models that converged in both methods and a full hybrid HSMR using a combination of the hierarchical diagnosis models when they converge, plus the remaining diagnoses using standard logistic regression models. We restricted the analysis to the 36 diagnoses accounting for 80% of in-hospital deaths nationally, based on 1,043,813 admissions (59 hospitals). A failure of the hierarchical models to converge in 15 of 36 diagnosis groups hindered full HSMR comparisons. A restricted HSMR, derived from a dataset based on the 21 diagnosis groups that converged (552,933 admissions) showed very high correlation (Pearson r = 0.99). Both traditional logistic regression and hierarchical model identified 12 statistical outliers in common, 7 with high O/E values and 5 with low O/E values. In addition, the multilevel analysis identified 5 additional unique high outliers and 1 additional unique low outlier, and the conventional model identified 2 additional unique low outliers. Similar results were obtained from the 2 modeling techniques in terms of O/E ratios. However, because a hierarchical model is associated with convergence problems, traditional logistic regression remains our recommended procedure for computing HSMRs. Copyright © 2011 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  15. Noise enhances information transfer in hierarchical networks.

    Science.gov (United States)

    Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

    2013-01-01

    We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

  16. Quantum Ising model on hierarchical structures

    International Nuclear Information System (INIS)

    Lin Zhifang; Tao Ruibao.

    1989-11-01

    A quantum Ising chain with both the exchange couplings and the transverse fields arranged in a hierarchical way is considered. Exact analytical results for the critical line and energy gap are obtained. It is shown that when R 1 not= R 2 , where R 1 and R 2 are the hierarchical parameters for the exchange couplings and the transverse fields, respectively, the system undergoes a phase transition in a different universality class from the pure quantum Ising chain with R 1 =R 2 =1. On the other hand, when R 1 =R 2 =R, there exists a critical value R c dependent on the furcating number of the hierarchy. In case of R > R c , the system is shown to exhibit as Ising-like critical point with the critical behaviour the same as in the pure case, while for R c the system belongs to another universality class. (author). 19 refs, 2 figs

  17. Application of hierarchical matrices for partial inverse

    KAUST Repository

    Litvinenko, Alexander

    2013-11-26

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

  18. Hierarchical control system of advanced robot manipulator

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  19. Hierarchical antifouling brushes for biosensing applications

    Czech Academy of Sciences Publication Activity Database

    de los Santos Pereira, Andres; Riedel, Tomáš; Brynda, Eduard; Rodriguez-Emmenegger, Cesar

    2014-01-01

    Roč. 202, 31 October (2014), s. 1313-1321 ISSN 0925-4005 R&D Projects: GA ČR GAP205/12/1702; GA MŠk(CZ) EE2.3.30.0029; GA MŠk(CZ) ED1.1.00/02.0109 Institutional support: RVO:61389013 Keywords : hierarchically structured brushes * affinity biosensors * fouling Subject RIV: CE - Biochemistry Impact factor: 4.097, year: 2014

  20. Internet advertising effectiveness by using hierarchical model

    OpenAIRE

    RAHMANI, Samaneh

    2015-01-01

    Abstract. Present paper has been developed with the title of internet advertising effectiveness by using hierarchical model. Presenting the question: Today Internet is an important channel in marketing and advertising. The reason for this could be the ability of the Internet to reduce costs and people’s access to online services[1]. Also advertisers can easily access a multitude of users and communicate with them at low cost [9]. On the other hand, compared to traditional advertising, interne...

  1. Hierarchical morphological segmentation for image sequence coding

    OpenAIRE

    Salembier Clairon, Philippe Jean; Pardàs Feliu, Montse

    1994-01-01

    This paper deals with a hierarchical morphological segmentation algorithm for image sequence coding. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features such as size, shape, contrast, or connectivity that can be considered as segmentation-oriented features. The algorithm follows a top-down procedure. It first takes into account the global information and produces a coarse segmentation, that is, with a small number of regions. Then...

  2. Hierarchical Archimedean Copulae: The HAC Package

    Directory of Open Access Journals (Sweden)

    Ostap Okhrin

    2014-06-01

    Full Text Available This paper presents the R package HAC, which provides user friendly methods for dealing with hierarchical Archimedean copulae (HAC. Computationally efficient estimation procedures allow to recover the structure and the parameters of HAC from data. In addition, arbitrary HAC can be constructed to sample random vectors and to compute the values of the corresponding cumulative distribution plus density functions. Accurate graphics of the HAC structure can be produced by the plot method implemented for these objects.

  3. Hierarchically structured materials for lithium batteries

    Science.gov (United States)

    Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

    2013-10-01

    The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg-1), new energy storage systems, such as lithium-oxygen (Li-O2) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li-O2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime.

  4. Hierarchical unilamellar vesicles of controlled compositional heterogeneity.

    Directory of Open Access Journals (Sweden)

    Maik Hadorn

    Full Text Available Eukaryotic life contains hierarchical vesicular architectures (i.e. organelles that are crucial for material production and trafficking, information storage and access, as well as energy production. In order to perform specific tasks, these compartments differ among each other in their membrane composition and their internal cargo and also differ from the cell membrane and the cytosol. Man-made structures that reproduce this nested architecture not only offer a deeper understanding of the functionalities and evolution of organelle-bearing eukaryotic life but also allow the engineering of novel biomimetic technologies. Here, we show the newly developed vesicle-in-water-in-oil emulsion transfer preparation technique to result in giant unilamellar vesicles internally compartmentalized by unilamellar vesicles of different membrane composition and internal cargo, i.e. hierarchical unilamellar vesicles of controlled compositional heterogeneity. The compartmentalized giant unilamellar vesicles were subsequently isolated by a separation step exploiting the heterogeneity of the membrane composition and the encapsulated cargo. Due to the controlled, efficient, and technically straightforward character of the new preparation technique, this study allows the hierarchical fabrication of compartmentalized giant unilamellar vesicles of controlled compositional heterogeneity and will ease the development of eukaryotic cell mimics that resemble their natural templates as well as the fabrication of novel multi-agent drug delivery systems for combination therapies and complex artificial microreactors.

  5. Hierarchically structured materials for lithium batteries

    International Nuclear Information System (INIS)

    Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

    2013-01-01

    The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg −1 ), new energy storage systems, such as lithium–oxygen (Li–O 2 ) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li–O 2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime. (paper)

  6. Hierarchical Cd4SiS6/SiO2 Heterostructure Nanowire Arrays.

    Science.gov (United States)

    Liu, Jian; Wang, Chunrui; Xie, Qingqing; Cai, Junsheng; Zhang, Jing

    2009-10-29

    Novel hierarchical Cd4SiS6/SiO2 based heterostructure nanowire arrays were fabricated on silicon substrates by a one-step thermal evaporation of CdS powder. The as-grown products were characterized using scanning electron microscopy, X-ray diffraction, and transmission electron microscopy. Studies reveal that a typical hierarchical Cd4SiS6/SiO2 heterostructure nanowire is composed of a single crystalline Cd4SiS6 nanowire core sheathed with amorphous SiO2 sheath. Furthermore, secondary nanostructures of SiO2 nanowires are highly dense grown on the primary Cd4SiS6 core-SiO2 sheath nanowires and formed hierarchical Cd4SiS6/SiO2 based heterostructure nanowire arrays which stand vertically on silicon substrates. The possible growth mechanism of hierarchical Cd4SiS6/SiO2 heterostructure nanowire arrays is proposed. The optical properties of hierarchical Cd4SiS6/SiO2 heterostructure nanowire arrays are investigated using Raman and Photoluminescence spectroscopy.

  7. Hierarchical Cd4SiS6/SiO2 Heterostructure Nanowire Arrays

    Directory of Open Access Journals (Sweden)

    Liu Jian

    2009-01-01

    Full Text Available Abstract Novel hierarchical Cd4SiS6/SiO2 based heterostructure nanowire arrays were fabricated on silicon substrates by a one-step thermal evaporation of CdS powder. The as-grown products were characterized using scanning electron microscopy, X-ray diffraction, and transmission electron microscopy. Studies reveal that a typical hierarchical Cd4SiS6/SiO2 heterostructure nanowire is composed of a single crystalline Cd4SiS6 nanowire core sheathed with amorphous SiO2 sheath. Furthermore, secondary nanostructures of SiO2 nanowires are highly dense grown on the primary Cd4SiS6 core-SiO2 sheath nanowires and formed hierarchical Cd4SiS6/SiO2 based heterostructure nanowire arrays which stand vertically on silicon substrates. The possible growth mechanism of hierarchical Cd4SiS6/SiO2 heterostructure nanowire arrays is proposed. The optical properties of hierarchical Cd4SiS6/SiO2 heterostructure nanowire arrays are investigated using Raman and Photoluminescence spectroscopy.

  8. Music Emotion Detection Using Hierarchical Sparse Kernel Machines

    Directory of Open Access Journals (Sweden)

    Yu-Hao Chin

    2014-01-01

    Full Text Available For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.

  9. Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

    Science.gov (United States)

    Spivak, David I.; Giesa, Tristan; Wood, Elizabeth; Buehler, Markus J.

    2011-01-01

    Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine. PMID:21931622

  10. Hierarchical image segmentation via recursive superpixel with adaptive regularity

    Science.gov (United States)

    Nakamura, Kensuke; Hong, Byung-Woo

    2017-11-01

    A fast and accurate segmentation algorithm in a hierarchical way based on a recursive superpixel technique is presented. We propose a superpixel energy formulation in which the trade-off between data fidelity and regularization is dynamically determined based on the local residual in the energy optimization procedure. We also present an energy optimization algorithm that allows a pixel to be shared by multiple regions to improve the accuracy and appropriate the number of segments. The qualitative and quantitative evaluations demonstrate that our algorithm, combining the proposed energy and optimization, outperforms the conventional k-means algorithm by up to 29.10% in F-measure. We also perform comparative analysis with state-of-the-art algorithms in the hierarchical segmentation. Our algorithm yields smooth regions throughout the hierarchy as opposed to the others that include insignificant details. Our algorithm overtakes the other algorithms in terms of balance between accuracy and computational time. Specifically, our method runs 36.48% faster than the region-merging approach, which is the fastest of the comparing algorithms, while achieving a comparable accuracy.

  11. Hierarchical Matrices Method and Its Application in Electromagnetic Integral Equations

    Directory of Open Access Journals (Sweden)

    Han Guo

    2012-01-01

    Full Text Available Hierarchical (H- matrices method is a general mathematical framework providing a highly compact representation and efficient numerical arithmetic. When applied in integral-equation- (IE- based computational electromagnetics, H-matrices can be regarded as a fast algorithm; therefore, both the CPU time and memory requirement are reduced significantly. Its kernel independent feature also makes it suitable for any kind of integral equation. To solve H-matrices system, Krylov iteration methods can be employed with appropriate preconditioners, and direct solvers based on the hierarchical structure of H-matrices are also available along with high efficiency and accuracy, which is a unique advantage compared to other fast algorithms. In this paper, a novel sparse approximate inverse (SAI preconditioner in multilevel fashion is proposed to accelerate the convergence rate of Krylov iterations for solving H-matrices system in electromagnetic applications, and a group of parallel fast direct solvers are developed for dealing with multiple right-hand-side cases. Finally, numerical experiments are given to demonstrate the advantages of the proposed multilevel preconditioner compared to conventional “single level” preconditioners and the practicability of the fast direct solvers for arbitrary complex structures.

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

    Science.gov (United States)

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

    2014-01-01

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

  13. A hierarchical SVG image abstraction layer for medical imaging

    Science.gov (United States)

    Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

    2010-03-01

    As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

  14. A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures.

    Science.gov (United States)

    Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A; Huang, Yonggang; Zhang, Yihui

    2016-05-01

    Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for

  15. Hierarchical Sheet-on-Sheet ZnIn2S4/g-C3N4 Heterostructure with Highly Efficient Photocatalytic H2 production Based on Photoinduced Interfacial Charge Transfer

    Science.gov (United States)

    Zhang, Zhenyi; Liu, Kuichao; Feng, Zhiqing; Bao, Yanan; Dong, Bin

    2016-01-01

    We have realized in-situ growth of ultrathin ZnIn2S4 nanosheets on the sheet-like g-C3N4 surfaces to construct a “sheet-on-sheet” hierarchical heterostructure. The as-synthesized ZnIn2S4/g-C3N4 heterojunction nanosheets exhibit remarkably enhancement on the photocatalytic activity for H2 production. This enhanced photoactivity is mainly attributed to the efficient interfacial transfer of photoinduced electrons and holes from g-C3N4 to ZnIn2S4 nanosheets, resulting in the decreased charge recombination on g-C3N4 nanosheets and the increased amount of photoinduced charge carriers in ZnIn2S4 nanosheets. Meanwhile, the increased surface-active-sites and extended light absorption of g-C3N4 nanosheets after the decoration of ZnIn2S4 nanosheets may also play a certain role for the enhancement of photocatalytic activity. Further investigations by the surface photovoltage spectroscopy and transient photoluminescence spectroscopy demonstrate that ZnIn2S4/g-C3N4 heterojunction nanosheets considerable boost the charge transfer efficiency, therefore improve the probability of photoinduced charge carriers to reach the photocatalysts surfaces for highly efficient H2 production. PMID:26753795

  16. Hierarchical Sheet-on-Sheet ZnIn2S4/g-C3N4 Heterostructure with Highly Efficient Photocatalytic H2 production Based on Photoinduced Interfacial Charge Transfer.

    Science.gov (United States)

    Zhang, Zhenyi; Liu, Kuichao; Feng, Zhiqing; Bao, Yanan; Dong, Bin

    2016-01-12

    We have realized in-situ growth of ultrathin ZnIn2S4 nanosheets on the sheet-like g-C3N4 surfaces to construct a "sheet-on-sheet" hierarchical heterostructure. The as-synthesized ZnIn2S4/g-C3N4 heterojunction nanosheets exhibit remarkably enhancement on the photocatalytic activity for H2 production. This enhanced photoactivity is mainly attributed to the efficient interfacial transfer of photoinduced electrons and holes from g-C3N4 to ZnIn2S4 nanosheets, resulting in the decreased charge recombination on g-C3N4 nanosheets and the increased amount of photoinduced charge carriers in ZnIn2S4 nanosheets. Meanwhile, the increased surface-active-sites and extended light absorption of g-C3N4 nanosheets after the decoration of ZnIn2S4 nanosheets may also play a certain role for the enhancement of photocatalytic activity. Further investigations by the surface photovoltage spectroscopy and transient photoluminescence spectroscopy demonstrate that ZnIn2S4/g-C3N4 heterojunction nanosheets considerable boost the charge transfer efficiency, therefore improve the probability of photoinduced charge carriers to reach the photocatalysts surfaces for highly efficient H2 production.

  17. Clinical fracture risk evaluated by hierarchical agglomerative clustering

    DEFF Research Database (Denmark)

    Kruse, C; Eiken, P; Vestergaard, P

    2017-01-01

    reimbursement, primary healthcare sector use and comorbidity of female subjects were combined. Standardized variable means, Euclidean distances and Ward's D2 method of hierarchical agglomerative clustering (HAC), were used to form the clustering object. K number of clusters was selected with the lowest cluster...... included in this study. Nine (k = 9) clusters were identified. Four clusters (n = 2886) were identified based on low to very low BMD with differences in comorbidity, anthropometrics and future bisphosphonate compliance. Two clusters of younger subjects (n = 1058, mean ages 30 and 51 years) were identified...... containing less than 250 subjects. Clusters were identified as high, average or low fracture risk based on bone mineral density (BMD) characteristics. Cluster-based descriptive statistics and relative Z-scores for variable means were computed. RESULTS: Ten thousand seven hundred seventy-five women were...

  18. A hierarchical approach for speech-instrumental-song classification.

    Science.gov (United States)

    Ghosal, Arijit; Chakraborty, Rudrasis; Dhara, Bibhas Chandra; Saha, Sanjoy Kumar

    2013-01-01

    Audio classification acts as the fundamental step for lots of applications like content based audio retrieval and audio indexing. In this work, we have presented a novel scheme for classifying audio signal into three categories namely, speech, music without voice (instrumental) and music with voice (song). A hierarchical approach has been adopted to classify the signals. At the first stage, signals are categorized as speech and music using audio texture derived from simple features like ZCR and STE. Proposed audio texture captures contextual information and summarizes the frame level features. At the second stage, music is further classified as instrumental/song based on Mel frequency cepstral co-efficient (MFCC). A classifier based on Random Sample and Consensus (RANSAC), capable of handling wide variety of data has been utilized. Experimental result indicates the effectiveness of the proposed scheme.

  19. Fabrication and properties of dual-level hierarchical structures mimicking gecko foot hairs.

    Science.gov (United States)

    Zhang, Peng; Liu, Shiyuan; Lv, Hao

    2013-02-01

    In nature, geckos have extraordinary adhesive capabilities. The multi-scale hierarchical structure of the gecko foot hairs, especially the high-aspect-ratio structure of its micro-scale seta and nano-scale spatulae is the critical factor of the gecko's ability to adopt and stick to any different surface with powerful adhesion force. In this paper, we present a simple and effective approach to fabricate dual-level hierarchical structures mimicking gecko foot hairs. Polydimethyl-siloxane (PDMS) hierarchical arrays were fabricated by demolding from a double stack mold that was composed of an SU-8 mold by thick film photolithography and a silicon mold by inductively coupled plasma (ICP) etching. Top pillars of the fabricated structures have 3 micom diameter and 18 microm in height, while base pillars have 25 microm diameter and 40 microm in height. The water droplet contact angle tests indicate that the hierarchical structures increase the hydrophobic property significantly compared with the single-level arrays and the unstructured polymers, exhibiting superhydrophobicity (154.2 degrees) like the Tokay gecko's (160.9 degrees). The shear force tests show that the top pillars make attachment through side contact with a value of about 0.25 N/cm2, and moreover, the hierarchical structures are demonstrated to be more suitable for contacting with rough surfaces.

  20. Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

    Science.gov (United States)

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

  1. Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

    Science.gov (United States)

    Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

    2013-11-20

    Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

  2. Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

    Science.gov (United States)

    Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

    2016-01-01

    The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

  3. Hierarchical ferroelectric and ferrotoroidic polarizations coexistent in nano-metamaterials.

    Science.gov (United States)

    Shimada, Takahiro; Lich, Le Van; Nagano, Koyo; Wang, Jie; Kitamura, Takayuki

    2015-10-01

    Tailoring materials to obtain unique, or significantly enhanced material properties through rationally designed structures rather than chemical constituents is principle of metamaterial concept, which leads to the realization of remarkable optical and mechanical properties. Inspired by the recent progress in electromagnetic and mechanical metamaterials, here we introduce the concept of ferroelectric nano-metamaterials, and demonstrate through an experiment in silico with hierarchical nanostructures of ferroelectrics using sophisticated real-space phase-field techniques. This new concept enables variety of unusual and complex yet controllable domain patterns to be achieved, where the coexistence between hierarchical ferroelectric and ferrotoroidic polarizations establishes a new benchmark for exploration of complexity in spontaneous polarization ordering. The concept opens a novel route to effectively tailor domain configurations through the control of internal structure, facilitating access to stabilization and control of complex domain patterns that provide high potential for novel functionalities. A key design parameter to achieve such complex patterns is explored based on the parity of junctions that connect constituent nanostructures. We further highlight the variety of additional functionalities that are potentially obtained from ferroelectric nano-metamaterials, and provide promising perspectives for novel multifunctional devices. This study proposes an entirely new discipline of ferroelectric nano-metamaterials, further driving advances in metamaterials research.

  4. Hierarchical self-assembly of complex polyhedral microcontainers

    International Nuclear Information System (INIS)

    Filipiak, David J; Leong, Timothy G; Gracias, David H; Azam, Anum

    2009-01-01

    The concept of self-assembly of a two-dimensional (2D) template to a three-dimensional (3D) structure has been suggested as a strategy to enable highly parallel fabrication of complex, patterned microstructures. We have previously studied the surface-tension-based self-assembly of patterned, microscale polyhedral containers (cubes, square pyramids and tetrahedral frusta). In this paper, we describe the observed hierarchical self-assembly of more complex, patterned polyhedral containers in the form of regular dodecahedra and octahedra. The hierarchical design methodology, combined with the use of self-correction mechanisms, was found to greatly reduce the propagation of self-assembly error that occurs in these more complex systems. It is a highly effective way to mass-produce patterned, complex 3D structures on the microscale and could also facilitate encapsulation of cargo in a parallel and cost-effective manner. Furthermore, the behavior that we have observed may be useful in the assembly of complex systems with large numbers of components

  5. A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

    Directory of Open Access Journals (Sweden)

    Shaoning Li

    2017-01-01

    Full Text Available In the fields of geographic information systems (GIS and remote sensing (RS, the clustering algorithm has been widely used for image segmentation, pattern recognition, and cartographic generalization. Although clustering analysis plays a key role in geospatial modelling, traditional clustering methods are limited due to computational complexity, noise resistant ability and robustness. Furthermore, traditional methods are more focused on the adjacent spatial context, which makes it hard for the clustering methods to be applied to multi-density discrete objects. In this paper, a new method, cell-dividing hierarchical clustering (CDHC, is proposed based on convex hull retraction. The main steps are as follows. First, a convex hull structure is constructed to describe the global spatial context of geospatial objects. Then, the retracting structure of each borderline is established in sequence by setting the initial parameter. The objects are split into two clusters (i.e., “sub-clusters” if the retracting structure intersects with the borderlines. Finally, clusters are repeatedly split and the initial parameter is updated until the terminate condition is satisfied. The experimental results show that CDHC separates the multi-density objects from noise sufficiently and also reduces complexity compared to the traditional agglomerative hierarchical clustering algorithm.

  6. Hierarchical structure of the otolith of adult wild carp

    Energy Technology Data Exchange (ETDEWEB)

    Li Zhuo; Gao Yonghua [State key laboratory of new ceramics and fine processing, Department of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Feng Qingling, E-mail: biomater@mail.tsinghua.edu.cn [State key laboratory of new ceramics and fine processing, Department of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China)

    2009-04-30

    The otolith of adult wild carp contains a pair of asterisci, a pair of lappilli and a pair of sagittae. Current research works are mainly restricted to the field of the daily ring structure. The purpose of this work is to explore the structural characteristics of carp's otolith in terms of hierarchy from nanometer to millimeter scale by transmission election microscope (TEM) and scanning electron microscope (SEM). Based on the observation, carp's lapillus is composed of ordered aragonite crystals. Seven hierarchical levels of the microstructure were proposed and described with the scheme representing a complete organization in detail. SEM studies show not only the clear daily growth increment, but also the morphology within the single daily increment. The domain structure of crystal orientation in otolith was observed for the first time. Furthermore, TEM investigation displays that the lapillus is composed of aragonite crystals with nanometer scale. Four hierarchical levels of the microstructure of the sagitta are also proposed. The asteriscus which is composed of nanometer scale vaterite crystals is considered to have a uniform structure.

  7. Hierarchical structure of the otolith of adult wild carp

    International Nuclear Information System (INIS)

    Li Zhuo; Gao Yonghua; Feng Qingling

    2009-01-01

    The otolith of adult wild carp contains a pair of asterisci, a pair of lappilli and a pair of sagittae. Current research works are mainly restricted to the field of the daily ring structure. The purpose of this work is to explore the structural characteristics of carp's otolith in terms of hierarchy from nanometer to millimeter scale by transmission election microscope (TEM) and scanning electron microscope (SEM). Based on the observation, carp's lapillus is composed of ordered aragonite crystals. Seven hierarchical levels of the microstructure were proposed and described with the scheme representing a complete organization in detail. SEM studies show not only the clear daily growth increment, but also the morphology within the single daily increment. The domain structure of crystal orientation in otolith was observed for the first time. Furthermore, TEM investigation displays that the lapillus is composed of aragonite crystals with nanometer scale. Four hierarchical levels of the microstructure of the sagitta are also proposed. The asteriscus which is composed of nanometer scale vaterite crystals is considered to have a uniform structure.

  8. Multiresolution with Hierarchical Modulations for Long Term Evolution of UMTS

    Directory of Open Access Journals (Sweden)

    Américo Correia

    2009-01-01

    Full Text Available In the Long Term Evolution (LTE of UMTS the Interactive Mobile TV scenario is expected to be a popular service. By using multiresolution with hierarchical modulations this service is expected to be broadcasted to larger groups achieving significant reduction in power transmission or increasing the average throughput. Interactivity in the uplink direction will not be affected by multiresolution in the downlink channels, since it will be supported by dedicated uplink channels. The presence of interactivity will allow for a certain amount of link quality feedback for groups or individuals. As a result, an optimization of the achieved throughput will be possible. In this paper system level simulations of multi-cellular networks considering broadcast/multicast transmissions using the OFDM/OFDMA based LTE technology are presented to evaluate the capacity, in terms of number of TV channels with given bit rates or total spectral efficiency and coverage. multiresolution with hierarchical modulations is presented to evaluate the achievable throughput gain compared to single resolution systems of Multimedia Broadcast/Multicast Service (MBMS standardised in Release 6.

  9. Hierarchical ferroelectric and ferrotoroidic polarizations coexistent in nano-metamaterials

    Science.gov (United States)

    Shimada, Takahiro; Lich, Le Van; Nagano, Koyo; Wang, Jie; Kitamura, Takayuki

    2015-10-01

    Tailoring materials to obtain unique, or significantly enhanced material properties through rationally designed structures rather than chemical constituents is principle of metamaterial concept, which leads to the realization of remarkable optical and mechanical properties. Inspired by the recent progress in electromagnetic and mechanical metamaterials, here we introduce the concept of ferroelectric nano-metamaterials, and demonstrate through an experiment in silico with hierarchical nanostructures of ferroelectrics using sophisticated real-space phase-field techniques. This new concept enables variety of unusual and complex yet controllable domain patterns to be achieved, where the coexistence between hierarchical ferroelectric and ferrotoroidic polarizations establishes a new benchmark for exploration of complexity in spontaneous polarization ordering. The concept opens a novel route to effectively tailor domain configurations through the control of internal structure, facilitating access to stabilization and control of complex domain patterns that provide high potential for novel functionalities. A key design parameter to achieve such complex patterns is explored based on the parity of junctions that connect constituent nanostructures. We further highlight the variety of additional functionalities that are potentially obtained from ferroelectric nano-metamaterials, and provide promising perspectives for novel multifunctional devices. This study proposes an entirely new discipline of ferroelectric nano-metamaterials, further driving advances in metamaterials research.

  10. The Realized Hierarchical Archimedean Copula in Risk Modelling

    Directory of Open Access Journals (Sweden)

    Ostap Okhrin

    2017-06-01

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

  11. Discovering market basket patterns using hierarchical association rules

    Directory of Open Access Journals (Sweden)

    Marijana Zekić-Sušac

    2015-10-01

    Full Text Available Association rules are a data mining method for discovering patterns of frequent item sets, such as products in a store that are frequently purchased at the same time by a customer (market basket analysis. A number of interestingness measures for association rules have been developed to date, but research has shown that there a dominant measure does not exist. Authors have mostly used objective measures, whereas subjective measures have rarely been investigated. This paper aims to combine objective measures such as support, confidence and lift with a subjective approach based on human expert selection in order to extract interesting rules from a real dataset collected from a large Croatian retail chain. Hierarchical association rules were used to enhance the efficiency of the extraction rule. The results show that rules that are more interesting were extracted using the hierarchical method, and that a hybrid approach of combining objective and subjective measures succeeds in extracting certain unexpected and actionable rules. The research can be useful for retail and marketing managers in planning marketing strategies, as well as for researchers investigating this field.

  12. Cities and regions in Britain through hierarchical percolation

    Science.gov (United States)

    Arcaute, Elsa; Molinero, Carlos; Hatna, Erez; Murcio, Roberto; Vargas-Ruiz, Camilo; Masucci, A. Paolo; Batty, Michael

    2016-04-01

    Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations which are the outcome of complex geographical, political and historical processes which leave almost indelible footprints on infrastructure such as the street network. In this work, we uncover a set of hierarchies in Britain at different scales using percolation theory on the street network and on its intersections which are the primary points of interaction and urban agglomeration. At the larger scales, the observed hierarchical structures can be interpreted as regional fractures of Britain, observed in various forms, from natural boundaries, such as National Parks, to regional divisions based on social class and wealth such as the well-known North-South divide. At smaller scales, cities are generated through recursive percolations on each of the emerging regional clusters. We examine the evolution of the morphology of the system as a whole, by measuring the fractal dimension of the clusters at each distance threshold in the percolation. We observe that this reaches a maximum plateau at a specific distance. The clusters defined at this distance threshold are in excellent correspondence with the boundaries of cities recovered from satellite images, and from previous methods using population density.

  13. UNCERTAINTY HANDLING IN DISASTER MANAGEMENT USING HIERARCHICAL ROUGH SET GRANULATION

    Directory of Open Access Journals (Sweden)

    H. Sheikhian

    2015-08-01

    Full Text Available Uncertainty is one of the main concerns in geospatial data analysis. It affects different parts of decision making based on such data. In this paper, a new methodology to handle uncertainty for multi-criteria decision making problems is proposed. It integrates hierarchical rough granulation and rule extraction to build an accurate classifier. Rough granulation provides information granules with a detailed quality assessment. The granules are the basis for the rule extraction in granular computing, which applies quality measures on the rules to obtain the best set of classification rules. The proposed methodology is applied to assess seismic physical vulnerability in Tehran. Six effective criteria reflecting building age, height and material, topographic slope and earthquake intensity of the North Tehran fault have been tested. The criteria were discretized and the data set was granulated using a hierarchical rough method, where the best describing granules are determined according to the quality measures. The granules are fed into the granular computing algorithm resulting in classification rules that provide the highest prediction quality. This detailed uncertainty management resulted in 84% accuracy in prediction in a training data set. It was applied next to the whole study area to obtain the seismic vulnerability map of Tehran. A sensitivity analysis proved that earthquake intensity is the most effective criterion in the seismic vulnerability assessment of Tehran.

  14. A hierarchical framework for air traffic control

    Science.gov (United States)

    Roy, Kaushik

    Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation

  15. A Hierarchical Transactive Energy Management System for Energy Sharing in Residential Microgrids

    Directory of Open Access Journals (Sweden)

    Most Nahida Akter

    2017-12-01

    Full Text Available This paper presents an analytical framework to develop a hierarchical energy management system (EMS for energy sharing among neighbouring households in residential microgrids. The houses in residential microgrids are categorized into three different types, traditional, proactive and enthusiastic, based on the inclusion of solar photovoltaic (PV systems and battery energy storage systems (BESSs. Each of these three houses has an individual EMS, which is defined as the primary EMS. Two other EMSs (secondary and tertiary are also considered in the proposed hierarchical energy management framework for the purpose of effective energy sharing. The intelligences of each EMS are presented in this paper for the purpose of energy sharing in a residential microgrid along with the priorities. The effectiveness of the proposed hierarchical framework is evaluated on a residential microgrid in Australia. The analytical results clearly reflect that the proposed scheme effectively and efficiently shares the energy among neighbouring houses in a residential microgrid.

  16. A novel snowflake-like SnO2 hierarchical architecture with superior gas sensing properties

    Science.gov (United States)

    Li, Yanqiong

    2018-02-01

    Snowflake-like SnO2 hierarchical architecture has been synthesized via a facile hydrothermal method and followed by calcination. The SnO2 hierarchical structures are assembled with thin nanoflakes blocks, which look like snowflake shape. A possible mechanism for the formation of the SnO2 hierarchical structures is speculated. Moreover, gas sensing tests show that the sensor based on snowflake-like SnO2 architectures exhibited excellent gas sensing properties. The enhancement may be attributed to its unique structures, in which the porous feature on the snowflake surface could further increase the active surface area of the materials and provide facile pathways for the target gas.

  17. Hierarchical and hybrid energy storage devices in data centers: Architecture, control and provisioning

    Science.gov (United States)

    Xue, Yuankun; Bogdan, Paul; Tang, Jian; Wang, Yanzhi; Lin, Xue

    2018-01-01

    Recently, a new approach has been introduced that leverages and over-provisions energy storage devices (ESDs) in data centers for performing power capping and facilitating capex/opex reductions, without performance overhead. To fully realize the potential benefits of the hierarchical ESD structure, we propose a comprehensive design, control, and provisioning framework including (i) designing power delivery architecture supporting hierarchical ESD structure and hybrid ESDs for some levels, as well as (ii) control and provisioning of the hierarchical ESD structure including run-time ESD charging/discharging control and design-time determination of ESD types, homogeneous/hybrid options, ESD provisioning at each level. Experiments have been conducted using real Google data center workloads based on realistic data center specifications. PMID:29351553

  18. Hierarchical and hybrid energy storage devices in data centers: Architecture, control and provisioning.

    Science.gov (United States)

    Sun, Mengshu; Xue, Yuankun; Bogdan, Paul; Tang, Jian; Wang, Yanzhi; Lin, Xue

    2018-01-01

    Recently, a new approach has been introduced that leverages and over-provisions energy storage devices (ESDs) in data centers for performing power capping and facilitating capex/opex reductions, without performance overhead. To fully realize the potential benefits of the hierarchical ESD structure, we propose a comprehensive design, control, and provisioning framework including (i) designing power delivery architecture supporting hierarchical ESD structure and hybrid ESDs for some levels, as well as (ii) control and provisioning of the hierarchical ESD structure including run-time ESD charging/discharging control and design-time determination of ESD types, homogeneous/hybrid options, ESD provisioning at each level. Experiments have been conducted using real Google data center workloads based on realistic data center specifications.

  19. A Hierarchical Approach to Persistent Scatterer Network Construction and Deformation Time Series Estimation

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2014-12-01

    Full Text Available This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data.

  20. Fuzzy hierarchical model for risk assessment principles, concepts, and practical applications

    CERN Document Server

    Chan, Hing Kai

    2013-01-01

    Risk management is often complicated by situational uncertainties and the subjective preferences of decision makers. Fuzzy Hierarchical Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and quantitative criteria to tackle imprecise information.   This approach is illustrated through number of case studies using examples from the food, fashion and electronics sectors to cover a range of applications including supply chain management, green product design and green initiatives. These practical examples explore how this method can be adapted and fine tuned to fit other industries as well.   Supported by an extensive literature review, Fuzzy Hierarchical Model for Risk Assessment  comprehensively introduces a new method for project managers across all industries as well as researchers in risk management.