WorldWideScience

Sample records for hierarchical event based

  1. A dynamic hierarchical clustering method for trajectory-based unusual video event detection.

    Science.gov (United States)

    Jiang, Fan; Wu, Ying; Katsaggelos, Aggelos K

    2009-04-01

    The proposed unusual video event detection method is based on unsupervised clustering of object trajectories, which are modeled by hidden Markov models (HMM). The novelty of the method includes a dynamic hierarchical process incorporated in the trajectory clustering algorithm to prevent model overfitting and a 2-depth greedy search strategy for efficient clustering.

  2. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

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

  3. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

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

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

    Science.gov (United States)

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

    2016-06-01

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

  5. Unit-Specific Event-Based and Slot-Based Hybrid Model Framework with Hierarchical Structure for Short-Term Scheduling

    Directory of Open Access Journals (Sweden)

    Yue Wang

    2015-01-01

    Full Text Available Unit-specific event-based continuous-time model has inaccurate calculation problems in involving resource constraints, due to the heterogeneous locations of the event points for different units. In order to address this limitation, a continuous-time unit-specific event-based and slot-based hybrid model framework with hierarchical structure is proposed in this work. A unit-specific event-based model without utility constraints is formulated in upper layer, and a slot-based model is introduced in lower layer. In the hierarchical structure, the two layers jointly address the short-term production scheduling problem of batch plants under utility consideration. The key features of this work include the following: (a eliminating overstrict constraints on utility resources, (b solving multiple counting problems, and (c considering duration time of event points in calculating utility utilization level. The effectiveness and advantages of proposed model are illustrated through two benchmark examples from the literatures.

  6. Sparsey™: event recognition via deep hierarchical sparse distributed codes.

    Science.gov (United States)

    Rinkus, Gerard J

    2014-01-01

    The visual cortex's hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally) and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes) in each representational field (which we equate with the cortical macrocolumn, "mac"), at each level. In localism, each represented feature/concept/event (hereinafter "item") is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC) in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac's units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model's core algorithm, which does both storage and retrieval (inference), makes a single pass over all macs on each time step, the overall model's storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge ("Big Data") problems. A 2010 paper described a nonhierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level), describing novel model principles like progressive critical periods, dynamic modulation of principal cells' activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of spatiotemporal patterns.

  7. Spontaneous and Hierarchical Segmentation of Non-functional Events

    DEFF Research Database (Denmark)

    Nielbo, Kristoffer Laigaard

    2012-01-01

    The dissertation, Spontaneous and Hierarchical Segmentation of Non-functional Events (SHSNE henceforth), explores and tests human perception of so-called non-functional events (i.e., events or action sequences that lack a necessary link between sub-actions and sequence goal), which typically...... ritual behavior. Part 1 concludes with five primary theoretical hypotheses: I) non-functional events will increase the human event segmentation rate; II) transitions between events will increase the cognitive prediction error signal independent of event type, but this signal will be chronically high......, consisting of four experiments in total, and four computer simulations. The first set of experiments shows that the event segmentation rate increases for human participants that observe non-functional events compared to functional events. Furthermore, it appears that context information does not have...

  8. Hierarchical Identity-Based Lossy Trapdoor Functions

    CERN Document Server

    Escala, Alex; Libert, Benoit; Rafols, Carla

    2012-01-01

    Lossy trapdoor functions, introduced by Peikert and Waters (STOC'08), have received a lot of attention in the last years, because of their wide range of applications in theoretical cryptography. The notion has been recently extended to the identity-based scenario by Bellare et al. (Eurocrypt'12). We provide one more step in this direction, by considering the notion of hierarchical identity-based lossy trapdoor functions (HIB-LTDFs). Hierarchical identity-based cryptography generalizes identitybased cryptography in the sense that identities are organized in a hierarchical way; a parent identity has more power than its descendants, because it can generate valid secret keys for them. Hierarchical identity-based cryptography has been proved very useful both for practical applications and to establish theoretical relations with other cryptographic primitives. In order to realize HIB-LTDFs, we first build a weakly secure hierarchical predicate encryption scheme. This scheme, which may be of independent interest, is...

  9. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    HOU XueLiang; LU Mei

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction en-gineering projects,a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model.By this new algorithm,local solutions to the first-order transformation of co-adaptability for conflict events can be ob-tained,based upon which,a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction de-gree of local solutions.The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently,but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  10. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction engineering projects, a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model. By this new algorithm, local solutions to the first-order transformation of co-adaptability for conflict events can be obtained, based upon which, a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction degree of local solutions. The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently, but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  11. Hierarchical event selection for video storyboards with a case study on snooker video visualization.

    Science.gov (United States)

    Parry, Matthew L; Legg, Philip A; Chung, David H S; Griffiths, Iwan W; Chen, Min

    2011-12-01

    Video storyboard, which is a form of video visualization, summarizes the major events in a video using illustrative visualization. There are three main technical challenges in creating a video storyboard, (a) event classification, (b) event selection and (c) event illustration. Among these challenges, (a) is highly application-dependent and requires a significant amount of application specific semantics to be encoded in a system or manually specified by users. This paper focuses on challenges (b) and (c). In particular, we present a framework for hierarchical event representation, and an importance-based selection algorithm for supporting the creation of a video storyboard from a video. We consider the storyboard to be an event summarization for the whole video, whilst each individual illustration on the board is also an event summarization but for a smaller time window. We utilized a 3D visualization template for depicting and annotating events in illustrations. To demonstrate the concepts and algorithms developed, we use Snooker video visualization as a case study, because it has a concrete and agreeable set of semantic definitions for events and can make use of existing techniques of event detection and 3D reconstruction in a reliable manner. Nevertheless, most of our concepts and algorithms developed for challenges (b) and (c) can be applied to other application areas.

  12. Sparsey^TM: Spatiotemporal Event Recognition via Deep Hierarchical Sparse Distributed Codes

    Directory of Open Access Journals (Sweden)

    Gerard J Rinkus

    2014-12-01

    Full Text Available The visual cortex’s hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes in each representational field (which we equate with the cortical macrocolumn, mac, at each level. In localism, each represented feature/concept/event (hereinafter item is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac’s units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model’s core algorithm, which does both storage and retrieval (inference, makes a single pass over all macs on each time step, the overall model’s storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge (Big Data problems. A 2010 paper described a non-hierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level, describing novel model principles like progressive critical periods, dynamic modulation of principal cells’ activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of

  13. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

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

    2005-07-01

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

  14. 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.

  15. Hierarchical Classification of Chinese Documents Based on N-grams

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    We explore the techniques of utilizing N-gram informatio n tocategorize Chinese text documents hierarchically so that the classifier can shak e off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classif ier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N-grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.

  16. 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...

  17. EMIR: a configurable hierarchical system for event monitoring and incident response

    Science.gov (United States)

    Deich, William T. S.

    2014-07-01

    The Event Monitor and Incident Response system (emir) is a flexible, general-purpose system for monitoring and responding to all aspects of instrument, telescope, and general facility operations, and has been in use at the Automated Planet Finder telescope for two years. Responses to problems can include both passive actions (e.g. generating alerts) and active actions (e.g. modifying system settings). Emir includes a monitor-and-response daemon, plus graphical user interfaces and text-based clients that automatically configure themselves from data supplied at runtime by the daemon. The daemon is driven by a configuration file that describes each condition to be monitored, the actions to take when the condition is triggered, and how the conditions are aggregated into hierarchical groups of conditions. Emir has been implemented for the Keck Task Library (KTL) keyword-based systems used at Keck and Lick Observatories, but can be readily adapted to many event-driven architectures. This paper discusses the design and implementation of Emir , and the challenges in balancing the competing demands for simplicity, flexibility, power, and extensibility. Emir 's design lends itself well to multiple purposes, and in addition to its core monitor and response functions, it provides an effective framework for computing running statistics, aggregate values, and summary state values from the primitive state data generated by other subsystems, and even for creating quick-and-dirty control loops for simple systems.

  18. Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

    Science.gov (United States)

    Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

    2016-01-01

    Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

  19. Hierarchical Event Descriptors (HED: Semi-structured tagging for real-world events in large-scale EEG

    Directory of Open Access Journals (Sweden)

    Nima Bigdely-Shamlo

    2016-10-01

    Full Text Available Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the HED (Hierarchical Event Descriptor system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab, CTAGGER, is also available to speed the process of tagging existing studies.

  20. A Hierarchical Sensor Network Based on Voronoi Diagram

    Institute of Scientific and Technical Information of China (English)

    SHANG Rui-qiang; ZHAO Jian-li; SUN Qiu-xia; WANG Guang-xing

    2006-01-01

    A hierarchical sensor network is proposed which places the sensing and routing capacity at different layer nodes.It thus simplifies the hardware design and reduces cost. Adopting Voronoi diagram in the partition of backbone network,a mathematical model of data aggregation based on hierarchical architecture is given. Simulation shows that the number of transmission data packages is sharply cut down in the network, thus reducing the needs in the bandwidth and energy resources and is thus well adapted to sensor networks.

  1. Fractal Analysis Based on Hierarchical Scaling in Complex Systems

    CERN Document Server

    Chen, Yanguang

    2016-01-01

    A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and spatial network proved to be associated with one another. This paper is devoted to exploring the theory of fractal analysis of complex systems by means of hierarchical scaling. Two research methods are utilized to make this study, including logic analysis method and empirical analysis method. The main results are as follows. First, a fractal system such as Cantor set is described from the hierarchical angle of view; based on hierarchical structure, three approaches are proposed to estimate fractal dimension. Second, the hierarchical scaling can be generalized to describe multifractals, fractal complementary sets, and self-similar curve such as logarithmic spiral. Third, complex systems such as urban system are demonstrated to be a self-similar hierarchy. The human settlements i...

  2. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

    Directory of Open Access Journals (Sweden)

    Andrew Cron

    Full Text Available Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less. Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing enrichment, and the ability to align cell subsets across multiple data samples for comparative analysis. In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM naturally generates an aligned data model that captures both commonalities and variations across multiple samples. HDPGMM also increases the sensitivity to extremely low frequency events by sharing information across multiple samples analyzed simultaneously. We validate the accuracy and reproducibility of HDPGMM estimates of antigen-specific T cells on clinically relevant reference peripheral blood mononuclear cell (PBMC samples with known frequencies of antigen-specific T cells. These cell samples take advantage of retrovirally TCR-transduced T cells spiked into autologous PBMC samples to give a defined number of antigen-specific T cells detectable by HLA-peptide multimer binding. We provide open source software that can take advantage of both multiple processors and GPU-acceleration to perform the numerically-demanding computations. We show that hierarchical modeling is a useful probabilistic approach that can provide a

  3. Road Network Selection Based on Road Hierarchical Structure Control

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    HE Haiwei

    2015-04-01

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

  4. Naturalizing sense of agency with a hierarchical event-control approach.

    Directory of Open Access Journals (Sweden)

    Devpriya Kumar

    Full Text Available Unraveling the mechanisms underlying self and agency has been a difficult scientific problem. We argue for an event-control approach for naturalizing the sense of agency by focusing on the role of perception-action regularities present at different hierarchical levels and contributing to the sense of self as an agent. The amount of control at different levels of the control hierarchy determines the sense of agency. The current study investigates this approach in a set of two experiments using a scenario containing multiple agents sharing a common goal where one of the agents is partially controlled by the participant. The participant competed with other agents for achieving the goal and subsequently answered questions on identification (which agent was controlled by the participant, the degree to which they are confident about their identification (sense of identification and the degree to which the participant believed he/she had control over his/her actions (sense of authorship. Results indicate a hierarchical relationship between goal-level control (higher level and perceptual-motor control (lower level for sense of agency. Sense of identification ratings increased with perceptual-motor control when the goal was not completed but did not vary with perceptual-motor control when the goal was completed. Sense of authorship showed a similar interaction effect only in experiment 2 that had only one competing agent unlike the larger number of competing agents in experiment 1. The effect of hierarchical control can also be seen in the misidentification pattern and misidentification was greater with the agent affording greater control. Results from the two studies support the event-control approach in understanding sense of agency as grounded in control. The study also offers a novel paradigm for empirically studying sense of agency and self.

  5. Study of chaos based on a hierarchical model

    Energy Technology Data Exchange (ETDEWEB)

    Yagi, Masatoshi; Itoh, Sanae-I. [Kyushu Univ., Fukuoka (Japan). Research Inst. for Applied Mechanics

    2001-12-01

    Study of chaos based on a hierarchical model is briefly reviewed. Here we categorize hierarchical model equations, i.e., (1) a model with a few degrees of freedom, e.g., the Lorenz model, (2) a model with intermediate degrees of freedom like a shell model, and (3) a model with many degrees of freedom such as a Navier-Stokes equation. We discuss the nature of chaos and turbulence described by these models via Lyapunov exponents. The interpretation of results observed in fundamental plasma experiments is also shown based on a shell model. (author)

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

    Science.gov (United States)

    Cui, Yingying; Zou, Suli; Ma, Zhongjing

    2016-01-01

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

  7. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  8. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

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

    Science.gov (United States)

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

    2014-01-01

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

  10. 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.

  11. Event-Based Activity Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2004-01-01

    We present and discuss a modeling approach that supports event-based modeling of information and activity in information systems. Interacting human actors and IT-actors may carry out such activity. We use events to create meaningful relations between information structures and the related activit...

  12. 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.

  13. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    Directory of Open Access Journals (Sweden)

    Rui Sun

    2016-08-01

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

  14. A VV&A evaluation system based on hierarchical evaluation

    Institute of Scientific and Technical Information of China (English)

    FANG Ke; YANG Ming; WANG Zi-cai

    2005-01-01

    Evaluation is the major activity of performing Verification, Validation and Accreditation (VV&A) of a simulation system. Unfortunately, there is a lack of reasonable and operable evaluation methods. Moreover,there are other problems to address in VV&A evaluation, such as index definition, conclusion analysis, etc. In this paper, a VV&A evaluation system is introduced to try to resolve these problems. The system is based on a method called hierarchical evaluation, and it uses a good combination of evaluation processes and indexes.First, a thorough analysis of the VV&A evaluation' s essentials and principles are given, then the uncertainty of the evaluation results caused by various analysis of the evaluators is pointed out, then a hierarchical evaluation mechanism based on evaluator weight and evaluation hierarchy is brought forward, and finally a comprehensive VV&A evaluation system with evaluation flow processing, index management and hierarchical evaluation fulfillment is established. The system gives good consideration to ease of operation, reasonableness of evaluation conclusion, and the ability to comprehensively resolve VV&A problems. Since VV&A is attracting more and more recognition, it is meaningful to provide a good system for implementing credible simulation systems. It is hoped that this VV&A evaluation will provide a good way.

  15. Hierarchical Geometric Constraint Model for Parametric Feature Based Modeling

    Institute of Scientific and Technical Information of China (English)

    高曙明; 彭群生

    1997-01-01

    A new geometric constraint model is described,which is hierarchical and suitable for parametric feature based modeling.In this model,different levels of geometric information are repesented to support various stages of a design process.An efficient approach to parametric feature based modeling is also presented,adopting the high level geometric constraint model.The low level geometric model such as B-reps can be derived automatically from the hig level geometric constraint model,enabling designers to perform their task of detailed design.

  16. Hierarchical control based on Hopfield network for nonseparable optimization problems

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The nonseparable optimization control problem is considered, where the overall objective function is not of an additive form with respect to subsystems. Since there exists the problem that computation is very slow when using iterative algorithms in multiobjective optimization, Hopfield optimization hierarchical network based on IPM is presented to overcome such slow computation difficulty. Asymptotic stability of this Hopfield network is proved and its equilibrium point is the optimal point of the original problem. The simulation shows that the net is effective to deal with the optimization control problem for large-scale nonseparable steady state systems.

  17. Wavelet based hierarchical coding scheme for radar image compression

    Science.gov (United States)

    Sheng, Wen; Jiao, Xiaoli; He, Jifeng

    2007-12-01

    This paper presents a wavelet based hierarchical coding scheme for radar image compression. Radar signal is firstly quantized to digital signal, and reorganized as raster-scanned image according to radar's repeated period frequency. After reorganization, the reformed image is decomposed to image blocks with different frequency band by 2-D wavelet transformation, each block is quantized and coded by the Huffman coding scheme. A demonstrating system is developed, showing that under the requirement of real time processing, the compression ratio can be very high, while with no significant loss of target signal in restored radar image.

  18. Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vishal Krishna Singh

    2016-02-01

    Full Text Available Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs. In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS scheme to reduce the in-network communication during the data gathering process. Co-related sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

  19. 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.

  20. Efficiently dense hierarchical graphene based aerogel electrode for supercapacitors

    Science.gov (United States)

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

    2016-08-01

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

  1. Hierarchically organized soft-materials based on fullerenes

    Science.gov (United States)

    Nakanishi, Takashi

    2009-04-01

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

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

    Science.gov (United States)

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

    2003-04-01

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

  3. Hand Tracking based on Hierarchical Clustering of Range Data

    CERN Document Server

    Cespi, Roberto; Lindner, Marvin

    2011-01-01

    Fast and robust hand segmentation and tracking is an essential basis for gesture recognition and thus an important component for contact-less human-computer interaction (HCI). Hand gesture recognition based on 2D video data has been intensively investigated. However, in practical scenarios purely intensity based approaches suffer from uncontrollable environmental conditions like cluttered background colors. In this paper we present a real-time hand segmentation and tracking algorithm using Time-of-Flight (ToF) range cameras and intensity data. The intensity and range information is fused into one pixel value, representing its combined intensity-depth homogeneity. The scene is hierarchically clustered using a GPU based parallel merging algorithm, allowing a robust identification of both hands even for inhomogeneous backgrounds. After the detection, both hands are tracked on the CPU. Our tracking algorithm can cope with the situation that one hand is temporarily covered by the other hand.

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

    Science.gov (United States)

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

    2014-01-01

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

  5. A Bisimulation-based Hierarchical Framework for Software Development Models

    Directory of Open Access Journals (Sweden)

    Ping Liang

    2013-08-01

    Full Text Available Software development models have been ripen since the emergence of software engineering, like waterfall model, V-model, spiral model, etc. To ensure the successful implementation of those models, various metrics for software products and development process have been developed along, like CMMI, software metrics, and process re-engineering, etc. The quality of software products and processes can be ensured in consistence as much as possible and the abstract integrity of a software product can be achieved. However, in reality, the maintenance of software products is still high and even higher along with software evolution due to the inconsistence occurred by changes and inherent errors of software products. It is better to build up a robust software product that can sustain changes as many as possible. Therefore, this paper proposes a process algebra based hierarchical framework to extract an abstract equivalent of deliverable at the end of phases of a software product from its software development models. The process algebra equivalent of the deliverable is developed hierarchically with the development of the software product, applying bi-simulation to test run the deliverable of phases to guarantee the consistence and integrity of the software development and product in a trivially mathematical way. And an algorithm is also given to carry out the assessment of the phase deliverable in process algebra.  

  6. Hierarchical message bus-based software architectural style

    Institute of Scientific and Technical Information of China (English)

    张世琨; 王立福; 杨芙清

    2002-01-01

    As the size and complexity of software systems increase,the design and specification of overall system structure become more significant issues than the choice of algorithms and data structures of computation.An appropriate architecture for a system is a key element of its success.Based on the practice of Jadebird software production line,this paper proposes a software architectural style based on hierarchical message buses,named JB/HMB.In this style,the component model consists of external interfaces,static structure and dynamic behavior,which depicts a component from different aspects.Supported by message buses,components interact with one another by messages,which can be used to describe distributed and concurrent systems well.JB/HMB style supports stepwise decomposition and refinement,and runtime system evolution.Finally,characteristics of JB/HMB style are summarized as a conclusion,and future research directions are specified.``

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

    Science.gov (United States)

    Rajadurai, Priscilla; Sankaranarayanan, Swamynathan

    2012-01-01

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

  8. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

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

    Science.gov (United States)

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

    2009-08-03

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

  10. Coordinate Descent Based Hierarchical Interactive Lasso Penalized Logistic Regression and Its Application to Classification Problems

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2014-01-01

    Full Text Available We present the hierarchical interactive lasso penalized logistic regression using the coordinate descent algorithm based on the hierarchy theory and variables interactions. We define the interaction model based on the geometric algebra and hierarchical constraint conditions and then use the coordinate descent algorithm to solve for the coefficients of the hierarchical interactive lasso model. We provide the results of some experiments based on UCI datasets, Madelon datasets from NIPS2003, and daily activities of the elder. The experimental results show that the variable interactions and hierarchy contribute significantly to the classification. The hierarchical interactive lasso has the advantages of the lasso and interactive lasso.

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

    Science.gov (United States)

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

    2009-04-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  13. Hierarchical Spread Spectrum Fingerprinting Scheme Based on the CDMA Technique

    Directory of Open Access Journals (Sweden)

    Kuribayashi Minoru

    2011-01-01

    Full Text Available Abstract Digital fingerprinting is a method to insert user's own ID into digital contents in order to identify illegal users who distribute unauthorized copies. One of the serious problems in a fingerprinting system is the collusion attack such that several users combine their copies of the same content to modify/delete the embedded fingerprints. In this paper, we propose a collusion-resistant fingerprinting scheme based on the CDMA technique. Our fingerprint sequences are orthogonal sequences of DCT basic vectors modulated by PN sequence. In order to increase the number of users, a hierarchical structure is produced by assigning a pair of the fingerprint sequences to a user. Under the assumption that the frequency components of detected sequences modulated by PN sequence follow Gaussian distribution, the design of thresholds and the weighting of parameters are studied to improve the performance. The robustness against collusion attack and the computational costs required for the detection are estimated in our simulation.

  14. 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.

  15. 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

  16. A Hierarchical Relationship between CME Properties and the Fluence Spectral Index of Large Solar Energetic Particle Events

    Science.gov (United States)

    Gopalswamy, N.; Yashiro, Seiji; Thakur, Neeharika; Makela, Pertti; Xie, Hong; Akiyama, Sachiko

    2017-01-01

    We report on a hierarchical relationship found between properties of white-light coronal mass ejections (CMEs) and the fluence spectral indices of the associated Large Solar Energetic Particle (SEP) Events. We consider 74 large SEP events from the western hemisphere in solar cycles 23 and 24 by multiple spacecraft (SAMPEX, GOES, and STEREO). The associated CMEs are observed by SOHO. We find that CMEs with high initial acceleration are associated with SEP events with the hardest fluence spectra, while those with lowest initial acceleration have SEP events with the softest fluence spectra; CMEs with intermediate initial acceleration result in SEP events with moderately hard fluence spectra. Impulsive acceleration leading to high CME speeds close to the Sun results in shock formation close to the Sun, where the ambient magnetic field and density are high and the particles are energized more efficiently. Slowly accelerating CMEs drive shocks at large distances from the Sun, where the magnetic field and density have fallen off significantly, reducing the efficiency of shock acceleration. These opposite extremes are represented by ground level enhancement (GLE) events that have high speeds early on (high initial acceleration) and the SEP events associated with CMEs from quiescent filament region that have low early speeds (low initial acceleration). This finding strongly supports the idea that CME-driven shocks accelerate SEPs and the heliocentric distance where the acceleration takes place decides the hardness of the SEP fluence spectrum.

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

    Science.gov (United States)

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

    1995-12-01

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

  18. Hierarchical Real-time Network Traffic Classification Based on ECOC

    Directory of Open Access Journals (Sweden)

    Yaou Zhao

    2013-09-01

    Full Text Available Classification of network traffic is basic and essential for manynetwork researches and managements. With the rapid development ofpeer-to-peer (P2P application using dynamic port disguisingtechniques and encryption to avoid detection, port-based and simplepayload-based network traffic classification methods were diminished.An alternative method based on statistics and machine learning hadattracted researchers' attention in recent years. However, most ofthe proposed algorithms were off-line and usually used a single classifier.In this paper a new hierarchical real-time model was proposed which comprised of a three tuple (source ip, destination ip and destination portlook up table(TT-LUT part and layered milestone part. TT-LUT was used to quickly classify short flows whichneed not to pass the layered milestone part, and milestones in layered milestone partcould classify the other flows in real-time with the real-time feature selection and statistics.Every milestone was a ECOC(Error-Correcting Output Codes based model which was usedto improve classification performance. Experiments showed that the proposedmodel can improve the efficiency of real-time to 80%, and themulti-class classification accuracy encouragingly to 91.4% on the datasets which had been captured from the backbone router in our campus through a week.

  19. Room Categorization Based on a Hierarchical Representation of Space

    Directory of Open Access Journals (Sweden)

    Peter Uršič

    2013-02-01

    Full Text Available For successful operation in real‐world environments, a mobile robot requires an effective spatial model. The model should be compact, should possess large expressive power and should scale well with respect to the number of modelled categories. In this paper we propose a new compositional hierarchical representation of space that is based on learning statistically significant observations, in terms of the frequency of occurrence of various shapes in the environment. We have focused on a two‐dimensional space, since many robots perceive their surroundings in two dimensions with the use of a laser range finder or sonar. We also propose a new low‐level image descriptor, by which we demonstrate the performance of our representation in the context of a room categorization problem. Using only the lower layers of the hierarchy, we obtain state‐of‐the‐art categorization results in two different experimental scenarios. We also present a large, freely available, dataset, which is intended for room categorization experiments based on data obtained with a laser range finder.

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

    Directory of Open Access Journals (Sweden)

    Peng Han

    2014-01-01

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

  1. Efficient Sum-Based Hierarchical Smoothing Under \\ell_1-Norm

    CERN Document Server

    Benabbas, Siavosh; Oren, Joel; Ye, Yuli

    2011-01-01

    We introduce a new regression problem which we call the Sum-Based Hierarchical Smoothing problem. Given a directed acyclic graph and a non-negative value, called target value, for each vertex in the graph, we wish to find non-negative values for the vertices satisfying a certain constraint while minimizing the distance of these assigned values and the target values in the lp-norm. The constraint is that the value assigned to each vertex should be no less than the sum of the values assigned to its children. We motivate this problem with applications in information retrieval and web mining. While our problem can be solved in polynomial time using linear programming, given the input size in these applications such a solution might be too slow. We mainly study the \\ell_1-norm case restricting the underlying graphs to rooted trees. For this case we provide an efficient algorithm, running in O(n^2) time. While the algorithm is purely combinatorial, its proof of correctness is an elegant use of linear programming du...

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

    Science.gov (United States)

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

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

  3. Quick Web Services Lookup Model Based on Hierarchical Registration

    Institute of Scientific and Technical Information of China (English)

    谢山; 朱国进; 陈家训

    2003-01-01

    Quick Web Services Lookup (Q-WSL) is a new model to registration and lookup of complex services in the Internet. The model is designed to quickly find complex Web services by using hierarchical registration method. The basic concepts of Web services system are introduced and presented, and then the method of hierarchical registration of services is described. In particular, service query document description and service lookup procedure are concentrated, and it addresses how to lookup these services which are registered in the Web services system. Furthermore, an example design and an evaluation of its performance are presented.Specifically, it shows that the using of attributionbased service query document design and contentbased hierarchical registration in Q-WSL allows service requesters to discover needed services more flexibly and rapidly. It is confirmed that Q-WSL is very suitable for Web services system.

  4. Class hierarchical test case generation algorithm based on expanded EMDPN model

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

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

  5. Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  6. A Tool for Fast Development of Modular and Hierarchic Neural Network-based Systems

    Directory of Open Access Journals (Sweden)

    Francisco Reinaldo

    2006-08-01

    Full Text Available This paper presents PyramidNet tool as a fast and easy way to develop Modular and Hierarchic Neural Network-based Systems. This tool facilitates the fast emergence of autonomous behaviors in agents because it uses a hierarchic and modular control methodology of heterogeneous learning modules: the pyramid. Using the graphical resources of PyramidNet the user is able to specify a behavior system even having little understanding of artificial neural networks. Experimental tests have shown that a very significant speedup is attained in the development of modular and hierarchic neural network-based systems by using this tool.

  7. The chromosome axis controls meiotic events through a hierarchical assembly of HORMA domain proteins.

    Science.gov (United States)

    Kim, Yumi; Rosenberg, Scott C; Kugel, Christine L; Kostow, Nora; Rog, Ofer; Davydov, Vitaliy; Su, Tiffany Y; Dernburg, Abby F; Corbett, Kevin D

    2014-11-24

    Proteins of the HORMA domain family play central, but poorly understood, roles in chromosome organization and dynamics during meiosis. In Caenorhabditis elegans, four such proteins (HIM-3, HTP-1, HTP-2, and HTP-3) have distinct but overlapping functions. Through combined biochemical, structural, and in vivo analysis, we find that these proteins form hierarchical complexes through binding of their HORMA domains to cognate peptides within their partners' C-terminal tails, analogous to the "safety belt" binding mechanism of Mad2. These interactions are critical for recruitment of HIM-3, HTP-1, and HTP-2 to chromosome axes. HTP-3, in addition to recruiting the other HORMA domain proteins to the axis, plays an independent role in sister chromatid cohesion and double-strand break formation. Finally, we find that mammalian HORMAD1 binds a motif found both at its own C terminus and at that of HORMAD2, indicating that this mode of intermolecular association is a conserved feature of meiotic chromosome structure in eukaryotes. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. 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.

  9. 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

    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...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...

  10. Concept Vector for Similarity Measurement Based on Hierarchical Domain Structure

    OpenAIRE

    Hong Zhe Liu; Hong Bao; Xu

    2012-01-01

    The concept vector model generalizes standard representations of similarity concept in terms of tree-like structure. In the model, each concept node in the hierarchical tree has ancestor and descendent concept nodes composing its relevancy nodes, thus a concept node is represented as a concept vector according to its relevancy nodes' density and the similarity of the two concepts is obtained by computing cosine similarity between their vectors. In addition, the model is adjusted in terms of l...

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

    Science.gov (United States)

    Wang, X.; Chien, S.

    1997-01-01

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

  12. 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.

  13. On event based state estimation

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.

    2009-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper

  14. On event based state estimation

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.

    2009-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper

  15. Numerical expression of general relationships in hierarchical data base management systems

    Energy Technology Data Exchange (ETDEWEB)

    Hall, R. C.

    1980-01-01

    The need for a means to express general relationships among entity occurrences in hierarchical data bases is addressed. Integer expression of general path segments is described as a means to meet this need. Operations on the expressions are also described. Two possible implementations are discussed. Both implementations are compatible with the hierarchical data model, and provide a logical extension that permits representation of many-to-many relationships. 4 figures.

  16. Problems in event based engine control

    DEFF Research Database (Denmark)

    Hendricks, Elbert; Jensen, Michael; Chevalier, Alain Marie Roger

    1994-01-01

    Physically a four cycle spark ignition engine operates on the basis of four engine processes or events: intake, compression, ignition (or expansion) and exhaust. These events each occupy approximately 180° of crank angle. In conventional engine controllers, it is an accepted practice to sample...... the engine variables synchronously with these events (or submultiples of them). Such engine controllers are often called event-based systems. Unfortunately the main system noise (or disturbance) is also synchronous with the engine events: the engine pumping fluctuations. Since many electronic engine...... problems on accurate air/fuel ratio control of a spark ignition (SI) engine....

  17. Gesture Recognition Based Mouse Events

    Directory of Open Access Journals (Sweden)

    Rachit Puri

    2013-12-01

    Full Text Available This paper presents the maneuver of mouse pointer a nd performs various mouse operations such as left click, right click, double click, drag etc using ge stures recognition technique. Recognizing gestures is a complex task which involves many aspects such as mo tion modeling, motion analysis, pattern recognition and machine learning. Keeping all the essential factors in mind a system has been created which recognizes the movement of fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it f rom the background color such as skin color. Thus recog nizing the gestures various mouse events have been performed. The application has been created on MATL AB environment with operating system as windows 7.

  18. Multi- Layer Tree Hierarchical Architecture Based on Web Service

    Institute of Scientific and Technical Information of China (English)

    TONG Hengjian; LI Deren; ZHU Xinyan; SHAO Zhenfeng

    2006-01-01

    To solve the problem of the information share and services integration in population information system, we propose a multi-layer tree hierarchical architecture. The com mand (Web Service Call) is recursively multicast from top layer of tree to bottom layer of tree and statistical data are gathered from bottom layer to top layer. We implemented the architecture by using Web Services technology. In our implementation, client program is the requestor of Web Services,and all leaf nodes of the last layer are only the provider of Web Services. For those nodes of intermediate layers, every node is not only the provider of Web Services, but also the dispatcher of Web Services. We take population census as an example to describe the working flow of the architecture.

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

    Science.gov (United States)

    Bi, Xia-an; Zhao, Junxia

    2017-01-01

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

  20. Content Based Image Retrieval using Hierarchical and K-Means Clustering Techniques

    Directory of Open Access Journals (Sweden)

    V.S.V.S. Murthy

    2010-03-01

    Full Text Available In this paper we present an image retrieval system that takes an image as the input query and retrieves images based on image content. Content Based Image Retrieval is an approach for retrieving semantically-relevant images from an image database based on automatically-derived image features. The unique aspect of the system is the utilization of hierarchical and k-means clustering techniques. The proposed procedure consists of two stages. First, here we are going to filter most of the images in the hierarchical clustering and then apply the clustered images to KMeans, so that we can get better favored image results.

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

    Science.gov (United States)

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

    2009-01-01

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

  2. 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...

  3. 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.

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

    Science.gov (United States)

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

    2014-07-15

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

  5. A Framework for Hierarchical Clustering Based Indexing in Search Engines

    Directory of Open Access Journals (Sweden)

    Parul Gupta

    2011-01-01

    Full Text Available Granting efficient and fast accesses to the index is a key issuefor performances of Web Search Engines. In order to enhancememory utilization and favor fast query resolution, WSEs useInverted File (IF indexes that consist of an array of theposting lists where each posting list is associated with a termand contains the term as well as the identifiers of the documentscontaining the term. Since the document identifiers are stored insorted order, they can be stored as the difference between thesuccessive documents so as to reduce the size of the index. Thispaper describes a clustering algorithm that aims atpartitioning the set of documents into ordered clusters so thatthe documents within the same cluster are similar and are beingassigned the closer document identifiers. Thus the averagevalue of the differences between the successive documents willbe minimized and hence storage space would be saved. Thepaper further presents the extension of this clustering algorithmto be applied for the hierarchical clustering in which similarclusters are clubbed to form a mega cluster and similar megaclusters are then combined to form super cluster. Thus thepaper describes the different levels of clustering whichoptimizes the search process by directing the searchto a specific path from higher levels of clustering to the lowerlevels i.e. from super clusters to mega clusters, then to clustersand finally to the individual documents so that the user gets thebest possible matching results in minimum possible time.

  6. A Biological Hierarchical Model Based Underwater Moving Object Detection

    Directory of Open Access Journals (Sweden)

    Jie Shen

    2014-01-01

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

  7. A Hierarchical NeuroBayes-based Algorithm for Full Reconstruction of B Mesons at B Factories

    CERN Document Server

    Feindt, Michael; Kreps, Michal; Kuhr, Thomas; Neubauer, Sebastian; Zander, Daniel; Zupanc, Anze

    2011-01-01

    We describe a new B-meson full reconstruction algorithm designed for the Belle experiment at the B-factory KEKB, an asymmetric e+e- collider. 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 CPU time consumption. In total, 1042 exclusive decay channels were reconstructed, employing 71 neural networks altogether. Overall, we correctly reconstruct one B+/- or B0 candidate in 0.3% or 0.2% of the BBbar events, respectively. This is an improvement in efficiency by roughly a factor of 2, depending on the analysis considered, compared to the cut-based classical reconstruction algorithm used at Belle. The new framework also features the ability to choose the desired purity or efficiency of the fully reconstructed sample. If the same purity as for t...

  8. 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.

  9. An Approach to Assembly Sequence Plannning Based on Hierarchical Strategy and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    Niu Xinwen; Ding Han; Xiong Youlun

    2001-01-01

    Using group and subassembly cluster methods, the hierarchical structure of a product is.generated automatically, which largely reduces the complexity of planning. Based on genetic algofithn the optimal of assembly sequence of each stracture level can be obtained by sequence-bysequence search. As a result, a better assembly sequence of the product can be generated by combining the assembly sequences of all hierarchical structures, which provides more parallelism and flexibility for assembly operations. An industrial example is solved by this new approach.

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

    Science.gov (United States)

    Bacon, Jessica; Ferri, Beth

    2013-01-01

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

  11. Landscape of international event-based biosurveillance.

    Science.gov (United States)

    Hartley, Dm; Nelson, Np; Walters, R; Arthur, R; Yangarber, R; Madoff, L; Linge, Jp; Mawudeku, A; Collier, N; Brownstein, Js; Thinus, G; Lightfoot, N

    2010-01-01

    Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.

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

    Science.gov (United States)

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

    2014-07-01

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

  13. 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

  14. Asynchronous event-based binocular stereo matching.

    Science.gov (United States)

    Rogister, Paul; Benosman, Ryad; Ieng, Sio-Hoi; Lichtsteiner, Patrick; Delbruck, Tobi

    2012-02-01

    We present a novel event-based stereo matching algorithm that exploits the asynchronous visual events from a pair of silicon retinas. Unlike conventional frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of the biological retina. Our algorithm uses the timing information carried by this representation in addressing the stereo-matching problem on moving objects. Using the high temporal resolution of the acquired data stream for the dynamic vision sensor, we show that matching on the timing of the visual events provides a new solution to the real-time computation of 3-D objects when combined with geometric constraints using the distance to the epipolar lines. The proposed algorithm is able to filter out incorrect matches and to accurately reconstruct the depth of moving objects despite the low spatial resolution of the sensor. This brief sets up the principles for further event-based vision processing and demonstrates the importance of dynamic information and spike timing in processing asynchronous streams of visual events.

  15. Event shape based global event cuts for the LHCb trigger

    CERN Document Server

    Kolchanova, Alena; CERN. Geneva. Department

    2016-01-01

    In 2019 LHCb will have one of the biggest upgrades of all LHC experiments. The project aims to study event shape variables for the LHCb trigger. Event shape variables are used to help identify events as having a higher likelihood of containing a beauty hadron within the LHCb acceptance from Minimum bias. Samples of each process are generated using the Pythia program. Fox Wolfram Moments, sphericity and thrust are applied to the data by selecting events with pseudorapidity $2.2 $ 2 GeV.

  16. An Event Based Approach To Situational Representation

    CERN Document Server

    Ashish, Naveen; Mehrotra, Sharad; Venkatasubramanian, Nalini

    2009-01-01

    Many application domains require representing interrelated real-world activities and/or evolving physical phenomena. In the crisis response domain, for instance, one may be interested in representing the state of the unfolding crisis (e.g., forest fire), the progress of the response activities such as evacuation and traffic control, and the state of the crisis site(s). Such a situation representation can then be used to support a multitude of applications including situation monitoring, analysis, and planning. In this paper, we make a case for an event based representation of situations where events are defined to be domain-specific significant occurrences in space and time. We argue that events offer a unifying and powerful abstraction to building situational awareness applications. We identify challenges in building an Event Management System (EMS) for which traditional data and knowledge management systems prove to be limited and suggest possible directions and technologies to address the challenges.

  17. Spatio-Temporal Story Mapping Animation Based On Structured Causal Relationships Of Historical Events

    Science.gov (United States)

    Inoue, Y.; Tsuruoka, K.; Arikawa, M.

    2014-04-01

    In this paper, we proposed a user interface that displays visual animations on geographic maps and timelines for depicting historical stories by representing causal relationships among events for time series. We have been developing an experimental software system for the spatial-temporal visualization of historical stories for tablet computers. Our proposed system makes people effectively learn historical stories using visual animations based on hierarchical structures of different scale timelines and maps.

  18. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

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

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

    Science.gov (United States)

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

    2011-05-01

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

  20. 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.

  1. Cost of Multicast Logical Key Tree Based on Hierarchical Data Processing

    Institute of Scientific and Technical Information of China (English)

    ZHOU Fucai; XU Jian; LI Ting

    2006-01-01

    How to design a multicast key management system with high performance is a hot issue now. This paper will apply the idea of hierarchical data processing to construct a common analytic model based on directed logical key tree and supply two important metrics to this problem: re-keying cost and key storage cost. The paper gives the basic theory to the hierarchical data processing and the analyzing model to multicast key management based on logical key tree. It has been proved that the 4-ray tree has the best performance in using these metrics. The key management problem is also investigated based on user probability model, and gives two evaluating parameters to re-keying and key storage cost.

  2. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Z Yu

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

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

    Science.gov (United States)

    Park, Jong Hwan; Lee, Dong Hoon

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

  6. Resource discovery algorithm based on hierarchical model and Conscious search in Grid computing system

    Directory of Open Access Journals (Sweden)

    Nasim Nickbakhsh

    2017-03-01

    Full Text Available The distributed system of Grid subscribes the non-homogenous sources at a vast level in a dynamic manner. The resource discovery manner is very influential on the efficiency and of quality the system functionality. The “Bitmap” model is based on the hierarchical and conscious search model that allows for less traffic and low number of messages in relation to other methods in this respect. This proposed method is based on the hierarchical and conscious search model that enhances the Bitmap method with the objective to reduce traffic, reduce the load of resource management processing, reduce the number of emerged messages due to resource discovery and increase the resource according speed. The proposed method and the Bitmap method are simulated through Arena tool. This proposed model is abbreviated as RNTL.

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

    OpenAIRE

    2014-01-01

    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...

  8. Intrusion Detection Method Based on Improved Growing Hierarchical Self-Organizing Map

    Institute of Scientific and Technical Information of China (English)

    张亚平; 布文秀; 苏畅; 王璐瑶; 许涵

    2016-01-01

    Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individ-ual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower, an improved GHSOM method combined with mutual information is proposed. After theoretical analysis, experiments are conducted to illustrate the effectiveness of the proposed method by accurately clustering the input data. Based on different clusters, the complex relationship within the data can be revealed effectively.

  9. Hierarchical Web Page Classification Based on a Topic Model and Neighboring Pages Integration

    OpenAIRE

    Sriurai, Wongkot; Meesad, Phayung; Haruechaiyasak, Choochart

    2010-01-01

    Most Web page classification models typically apply the bag of words (BOW) model to represent the feature space. The original BOW representation, however, is unable to recognize semantic relationships between terms. One possible solution is to apply the topic model approach based on the Latent Dirichlet Allocation algorithm to cluster the term features into a set of latent topics. Terms assigned into the same topic are semantically related. In this paper, we propose a novel hierarchical class...

  10. Does history of childhood maltreatment make a difference in prison? A hierarchical approach on early family events and personality traits.

    Science.gov (United States)

    Sergentanis, Theodoros N; Sakelliadis, Emmanouil I; Vlachodimitropoulos, Dimitrios; Goutas, Nikolaos; Sergentanis, Ioannis N; Spiliopoulou, Chara A; Papadodima, StavroulaA

    2014-12-30

    This study attempts to assess childhood maltreatment in prison through a hierarchical approach. The hierarchical approach principally aims to disentangle the independent effects of childhood maltreatment upon psychiatric morbidity/personality traits, if any, from the burden that the adverse family conditions have already imposed to the mental health of the maltreated individual-prisoner. To this direction, a conceptual framework with five hierarchical levels was constructed, namely: immutable demographic factors; family conditions; childhood maltreatment (physical abuse, neglect and sexual abuse); personality traits, habits and psychiatric morbidity; prison-related variables. A self-administered, anonymous set (battery) of questionnaires was administered to 173 male prisoners in the Chalkida prison, Greece; 26% of prisoners disclosed childhood maltreatment. Psychiatric condition in the family, parental alcoholism and parental divorce correlated with childhood maltreatment. After adjustment for immutable demographic factors and family conditions, childhood maltreatment was associated with aggression (both in terms of Lifetime History of Aggression and Buss–Perry Aggression Questionnaire scores), illicit substance use, personal history of psychiatric condition, current smoking, impulsivity and alcohol abuse. In conclusion, childhood maltreatment represents a pivotal, determining factor in the life course of male prisoners. Delinquents seem to suffer from long-term consequences of childhood maltreatment in terms of numerous mental health aspects.

  11. CORBA-Based Discrete Event Simulation System

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The CORBA technique is an integration of the object-oriented conception and distributed computing technique. It can make the application within distributed heterogeneous environments reusable, portable and interoperable.The architecture of CORBA-based discrete event simulation systems is presented and the interface of distributed simulation objects (DSO) is defined in this paper after the DSO is identified and the sysnchronization mechanism among DSO is discussed.``

  12. Repair approach for DMC images based on hierarchical location using edge curve

    Institute of Scientific and Technical Information of China (English)

    PAN Jun; WANG Mi; LI DeRen; FENG TianTian

    2009-01-01

    The color composite digital mapping camera (DMC) images are produced by the post-processing software of Z/I imaging. But the failure of radiometric correction in post-processing leads to residual radiometric differences between CCD images, which then affect the quality of the images in further applications. This paper, via analyzing the characters and causes of such a phenomenon, proposes a repair approach based on hierarchical location using edge curve. The approach employs a hierarchical strategy to locate the transition area and seam-line automatically and then repair the image through the global reconstruction between CCD images and the local reconstruction in the transition area. Experiments indicate that the approach proposed by this paper is feasible and can improve the quality of images effectively.

  13. A CDMA Based Scalable Hierarchical Architecture for Network-On-Chip

    Directory of Open Access Journals (Sweden)

    Mohamed A. Abd El Ghany

    2012-09-01

    Full Text Available A Scalable hierarchical architecture based Code-Division Multiple Access (CDMA is proposed for high performance Network-on-Chip (NoC. This hierarchical architecture provides the integration of a large number of IPs in a single on-chip system. The network encoding and decoding schemes for CDMA transmission are provided. The proposed CDMA NoC architecture is compared to the conventional architecture in terms of latency, area and power dissipation. The overall area required to implement the proposed CDMA NoC design is reduced by 24.2%. The design decreases the latency of the network by 40%. The total power consumption required to achieve the proposed design is also decreased by 25%.

  14. Scheduling method based on virtual flattened architecture for Hierarchical system-on-chip

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong; ZHANG Jin-yi; YANG Xiao-dong; YANG Yi

    2009-01-01

    As the technology of IP-core-reused has been widely used, a lot of intellectual property (IP) cores have been embedded in different layers of system-on-chip (SOC). Although the cycles of development and overhead are reduced by this method, it is a challenge to the SOC test. This paper proposes a scheduling method based on the virtual flattened architecture for hierarchical SOC, which breaks the hierarchical architecture to the virtual flattened one. Moreover, this method has more advantages compared with the traditional one, which tests the parent cores and child cores separately. Finally, the method is verified by the ITC'02 benchmark, and gives good results that reduce the test time and overhead effectively.

  15. 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.

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

    Science.gov (United States)

    Huang, Weizhang; Kamenski, Lennard; Lang, Jens

    2010-03-01

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

  17. Controlling Torque Distribution for Parallel Hybrid Vehicle Based on Hierarchical Structure Fuzzy Logic

    Institute of Scientific and Technical Information of China (English)

    HuangMiao-hua; JinGuo-dong

    2003-01-01

    The Hierarchical Structure Fuzzy Logic Control(HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mocle of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver's experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.

  18. Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    L. Monika Moskal

    2013-10-01

    Full Text Available The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT in image segmentation, and to apply the object-based image analysis (OBIA approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a methodology to classify hyperspatial (high-spatial imagery to fine detail level of tree crowns, shadows and understory, while still allowing discrimination between density classes and mature forest versus burn classes. At the most detailed hierarchical Level I classification accuracies reached 78.8%, a Level II stand density classification produced accuracies of 89.1% and the same accuracy was achieved by the coarse general classification at Level III. Our interpretation of these results suggests hyperspatial imagery can be applied to post-fire forest density and regeneration mapping.

  19. One-dimensional ZnS-based Hetero-, Core/shell and Hierarchical Nanostructures

    Institute of Scientific and Technical Information of China (English)

    Xiaosheng FANG; Ujjal K.Gautam; Yoshio BANDO; Dmitri GOLBERG

    2008-01-01

    A focus of the current nanotechnology has shifted from routine fabrication of nanostructures to designing functional electronic devices and realizing their immense potentials for applications. Due to infusion of multifunctionality into a single system, the utilization of hetero-, core/shell and hierarchical nanostructures has become the key issue for building such devices. ZnS, due to its direct wide bandgap, high index of refraction, high transparency in the visible range and intrinsic polarity, is one of the most useful semiconductors for a wide range of electronics applications. This article provides a dense review of the state-of-the-art research activities in one-dimensional (1D) ZnS-based hetero-, core/shell and hierarchical nanostructures. The particular emphasis is put on their syntheses and applications.

  20. 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.

  1. 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.

  2. Component-based event composition modeling for CPS

    Science.gov (United States)

    Yin, Zhonghai; Chu, Yanan

    2017-06-01

    In order to combine event-drive model with component-based architecture design, this paper proposes a component-based event composition model to realize CPS’s event processing. Firstly, the formal representations of component and attribute-oriented event are defined. Every component is consisted of subcomponents and the corresponding event sets. The attribute “type” is added to attribute-oriented event definition so as to describe the responsiveness to the component. Secondly, component-based event composition model is constructed. Concept lattice-based event algebra system is built to describe the relations between events, and the rules for drawing Hasse diagram are discussed. Thirdly, as there are redundancies among composite events, two simplification methods are proposed. Finally, the communication-based train control system is simulated to verify the event composition model. Results show that the event composition model we have constructed can be applied to express composite events correctly and effectively.

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

    Directory of Open Access Journals (Sweden)

    Jun Wu

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

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

    Science.gov (United States)

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

    2016-07-01

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

  5. A Fuzzy Logic Based Supervisory Hierarchical Control Scheme for Real Time Pressure Control

    Institute of Scientific and Technical Information of China (English)

    N.Kanagaraj; P.Sivashanmugam; S.Paramasivam

    2009-01-01

    This paper describes a supervisory hierarchical fuzzy controller (SHFC) for regulating pressure in a real-time pilot pressure control system.The input scaling factor tuning of a direct expert controller is made using the error and process input parameters in a closed loop system in order to obtain better controller performance for set-point change and load disturbances.This on-line tuning method reduces operator involvement and enhances the controller performance to a wide operating range.The hierarchical control scheme consists of an intelligent upper level supervisory fuzzy controller and a lower level direct fuzzy controller.The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. The control algorithm for the proposed scheme has been developed and tested using an ARM7 microcontroller-based embedded target board for a nonlinear pressure process having dead time.To demonstrate the effectiveness,the results of the proposed hierarchical controller,fuzzy controller and conventional proportional-integral (PI) controller are analyzed.The results prove that the SHFC performance is better in terms of stability and robustness than the conventional control methods.

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

    Science.gov (United States)

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

    2013-03-01

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

  7. 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.

  8. MAS Based Event-Triggered Hybrid Control for Smart Microgrids

    DEFF Research Database (Denmark)

    Dou, Chunxia; Liu, Bin; Guerrero, Josep M.

    2013-01-01

    This paper is focused on an advanced control for autonomous microgrids. In order to improve the performance regarding security and stability, a hierarchical decentralized coordinated control scheme is proposed based on multi-agents structure. Moreover, corresponding to the multi-mode and the hybr...

  9. Efficient hierarchical identity based encryption scheme in the standard model over lattices

    Institute of Scientific and Technical Information of China (English)

    Feng-he WANG; Chun-xiao WANG; Zhen-hua LIU

    2016-01-01

    Using lattice basis delegation in a fi xed dimension, we propose an efficient lattice-based hierarchical identity based encryption (HIBE) scheme in the standard model whose public key size is only (dm2+mn) log q bits and whose message-ciphertext expansion factor is only log q, where d is the maximum hierarchical depth and (n,m,q) are public parameters. In our construction, a novel public key assignment rule is used to averagely assign one random and public matrix to two identity bits, which implies that d random public matrices are enough to build the proposed HIBE scheme in the standard model, compared with the case in which 2d such public matrices are needed in the scheme proposed at Crypto 2010 whose public key size is (2dm2+mn+m) log q. To reduce the message-ciphertext expansion factor of the proposed scheme to log q, the encryption algorithm of this scheme is built based on Gentry’s encryption scheme, by which m2 bits of plaintext are encrypted into m2 log q bits of ciphertext by a one time encryption operation. Hence, the presented scheme has some advantages with respect to not only the public key size but also the message-ciphertext expansion factor. Based on the hardness of the learning with errors problem, we demonstrate that the scheme is secure under selective identity and chosen plaintext attacks.

  10. Vehicle Detection Based on Visual Saliency and Deep Sparse Convolution Hierarchical Model

    Institute of Scientific and Technical Information of China (English)

    CAI Yingfeng; WANG Hai; CHEN Xiaobo; GAO Li; CHEN Long

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Jie Yang

    2014-01-01

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

  13. Spatial Object Aggregation Based on Data Structure,Local Triangulation and Hierarchical Analyzing Method

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure),the Local Constrained Delaunay Triangulations and semantic hierarchy.The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation.The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects.Several different cases of aggregation have been presented in this paper.

  14. 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.

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

    Science.gov (United States)

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

    2017-02-01

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

  16. 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.

  17. 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.

  18. DD4hep Based Event Reconstruction

    CERN Document Server

    AUTHOR|(SzGeCERN)683529; Frank, Markus; Gaede, Frank-Dieter; Hynds, Daniel; Lu, Shaojun; Nikiforou, Nikiforos; Petric, Marko; Simoniello, Rosa; Voutsinas, Georgios Gerasimos

    The DD4HEP detector description toolkit offers a flexible and easy-to-use solution for the consistent and complete description of particle physics detectors in a single system. The sub-component DDREC provides a dedicated interface to the detector geometry as needed for event reconstruction. With DDREC there is no need to define an additional, separate reconstruction geometry as is often done in HEP, but one can transparently extend the existing detailed simulation model to be also used for the reconstruction. Based on the extension mechanism of DD4HEP, DDREC allows one to attach user defined data structures to detector elements at all levels of the geometry hierarchy. These data structures define a high level view onto the detectors describing their physical properties, such as measurement layers, point resolutions, and cell sizes. For the purpose of charged particle track reconstruction, dedicated surface objects can be attached to every volume in the detector geometry. These surfaces provide the measuremen...

  19. DD4hep Based Event Reconstruction

    CERN Document Server

    Sailer, Andre; Gaede, Frank-Dieter; Hynds, Daniel; Lu, Shaojun; Nikiforou, Nikiforos; Petric, Marko; Simoniello, Rosa; Voutsinas, Georgios Gerasimos

    The DD4HEP detector description toolkit offers a flexible and easy-to-use solution for the consistent and complete description of particle physics detectors in a single system. The sub-component DDREC provides a dedicated interface to the detector geometry as needed for event reconstruction. With DDREC there is no need to define an additional, separate reconstruction geometry as is often done in HEP, but one can transparently extend the existing detailed simulation model to be also used for the reconstruction. Based on the extension mechanism of DD4HEP, DDREC allows one to attach user defined data structures to detector elements at all levels of the geometry hierarchy. These data structures define a high level view onto the detectors describing their physical properties, such as measurement layers, point resolutions, and cell sizes. For the purpose of charged particle track reconstruction, dedicated surface objects can be attached to every volume in the detector geometry. These surfaces provide the measuremen...

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

    Science.gov (United States)

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

    2017-02-01

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

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

    Science.gov (United States)

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

    2016-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Wuyong Qian

    2016-09-01

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

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

    Science.gov (United States)

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

    2016-09-09

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2000-01-01

    The important task for anaesthetists is to provide an adequate degree of neuromuscular block during surgical operations, so that it should not be difficult to antagonize at the end of surgery. Therefore, this study examined the application of a simple technique (i.e., fuzzy logic) to an almost ideal muscle relaxant (i.e., rocuronium) at general anaesthesia in order to control the system more easily, efficiently, intelligently and safely during an operation. The characteristics of neuromuscular blockade induced by rocuronium were studied in 10 ASA I or II adult patients anaesthetized with inhalational (i.e., isoflurane) anaesthesia. A Datex Relaxograph was used to monitor neuromuscular block. And, ulnar nerve was stimulated supramaximally with repeated train-of-four via surface electrodes at the wrist. Initially a notebook personal computer was linked to a Datex Relaxograph to monitor electromyogram (EMG) signals which had been pruned by a three-level hierarchical structure of filters in order to design a controller for administering muscle relaxants. Furthermore, a four-level hierarchical fuzzy logic controller using the fuzzy logic and rule of thumb concept has been incorporated into the system. The Student's test was used to compare the variance between the groups. p control of muscle relaxation with a mean T1% error of -0.19 (SD 0.66) % accommodating a range in mean infusion rate (MIR) of 0.21-0.49 mg x kg(-1) x h(-1). When these results were compared with our previous ones using the same hierarchical structure applied to mivacurium, less variation in the T1% error (p controller activity of these two drugs showed no significant difference (p > 0.5). However, the consistent medium coefficient variance (CV) of the MIR of both rocuronium (i.e., 36.13 (SD 9.35) %) and mivacurium (i.e., 34.03 (SD 10.76) %) indicated a good controller activity. The results showed that a hierarchical rule-based monitoring and fuzzy logic control architecture can provide stable control

  7. Gel-based composite polymer electrolytes with novel hierarchical mesoporous silica network for lithium batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wang Xiaoliang; Cai Qiang [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Fan Lizhen [School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083 (China); Hua Tao; Lin Yuanhua [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Nan Cewen [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China)], E-mail: cwnan@tsinghua.edu.cn

    2008-11-15

    In the present work, novel gel-based composite polymer electrolytes for lithium batteries were prepared by introducing a hierarchical mesoporous silica network to the poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP)-based gel electrolytes. As compared with the PVDF-HFP-based gel electrolytes with/without conventional nano-sized silica fillers, the novel electrolytes have shown more homogeneous microstructure, higher ionic conductivity and better mechanical stability, which could be caused by the strong silica network and the effective interactions among the polymer, the liquid electrolytes and the silica. Moreover, the cell with this kind of electrolytes could achieve a discharge capacity as much as 150 mAh g{sup -1} at room temperature (LiCoO{sub 2} as the cathode active material), with high Coulomb efficiency.

  8. Gel-based composite polymer electrolytes with novel hierarchical mesoporous silica network for lithium batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xiao-Liang; Cai, Qiang; Hua, Tao; Lin, Yuan-Hua; Nan, Ce-Wen [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Fan, Li-Zhen [School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083 (China)

    2008-11-15

    In the present work, novel gel-based composite polymer electrolytes for lithium batteries were prepared by introducing a hierarchical mesoporous silica network to the poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP)-based gel electrolytes. As compared with the PVDF-HFP-based gel electrolytes with/without conventional nano-sized silica fillers, the novel electrolytes have shown more homogeneous microstructure, higher ionic conductivity and better mechanical stability, which could be caused by the strong silica network and the effective interactions among the polymer, the liquid electrolytes and the silica. Moreover, the cell with this kind of electrolytes could achieve a discharge capacity as much as 150 mAh g{sup -1} at room temperature (LiCoO{sub 2} as the cathode active material), with high Coulomb efficiency. (author)

  9. 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.

  10. Superquadric Based Hierarchical Reconstruction for Virtualizing Free Form Objects from 3D Data

    Institute of Scientific and Technical Information of China (English)

    LIU Weibin; YUAN Baozong

    2001-01-01

    The superquadric description is usedin modeling the virtual objects in AVR (from ActualReality to Virtual Reality).However,due to the in-trinsic property,the superquadric and its deforma-tion extensions (DSQ) are not flexible enough to de-scribe precisely the complex objects with asymmetryand free form surface.To solve the problem,a hierar-chical reconstruction approach in AVR for virtualizingthe objects with superquadric based models from 3Ddata is developed.Firstly,an initial approximation isproduced by a superquadric fit to the 3D data.Then,the crude superquadric fit is refined by fitting theresidue (distance map) with global and local DirectManipulation of Free-Form Deformation (DMFFD).The key elements of the hierarchical method,includ-ing superquadric fit to 3D data,mathematical detailsand the recursive-fitting algorithm for DMFFD,com-putation of distance maps,adaptive refinement anddecimation of polygon mesh under DMFFD,are pro-posed.An implementation example of hierarchicalreconstruction is presented.The proposed approachis shown competent and efficient for virtualizing thecomplex objects into virtual environment.

  11. HIERARCHICAL DESIGN BASED INTRUSION DETECTION SYSTEM FOR WIRELESS AD HOC SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Mohammad Saiful Islam Mamun

    2010-07-01

    Full Text Available In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs.However, security is one of the significant challenges for sensor network because of their deploymentin open and unprotected environment. As cryptographic mechanism is not enough to protect sensornetwork from external attacks, intrusion detection system needs to be introduced. Though intrusionprevention mechanism is one of the major and efficient methods against attacks, but there might besome attacks for which prevention method is not known. Besides preventing the system from someknown attacks, intrusion detection system gather necessary information related to attack technique andhelp in the development of intrusion prevention system. In addition to reviewing the present attacksavailable in wireless sensor network this paper examines the current efforts to intrusion detectionsystem against wireless sensor network. In this paper we propose a hierarchical architectural designbased intrusion detection system that fits the current demands and restrictions of wireless ad hocsensor network. In this proposed intrusion detection system architecture we followed clusteringmechanism to build a four level hierarchical network which enhances network scalability to largegeographical area and use both anomaly and misuse detection techniques for intrusion detection. Weintroduce policy based detection mechanism as well as intrusion response together with GSM cellconcept for intrusion detection architecture.

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

    Science.gov (United States)

    Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

    2011-03-01

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

  13. 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.

  14. 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.

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

    Science.gov (United States)

    2012-01-22

    ICES REPORT 12-05 January 2012 An Isogeometric Design-through-analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed...M.J. Borden, E. Rank, T.J.R. Hughes, An Isogeometric Design-through-analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed...analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed Boundary Methods, and T-spline CAD Surfaces 5a. CONTRACT NUMBER 5b

  16. Multicast Address Management and Connection Control Based on Hierarchical Autonomous Structure

    Institute of Scientific and Technical Information of China (English)

    WANG Jian; ZHANG Fuyan

    1999-01-01

    Multicast capability, including multicast address and multicast routing mechanisms, at the network layeris necessary in order to reduce the bandwidth requirements of multiparty, multicast applications. Based on hierarchical autonomous structure in accordance with the self-organization topologies of Internet, the paper puts forward a multicast address management scheme that is shown to be robust and scalable. Connection control hierarchy (CCH) based on master/slave relationship and a simple efficient building algorithm of multi-point connection is also built. The paper also describes the normal operations of multicast address management andmulti-point connection controller. Through simulation experiment, HAM, CM and DDM of Multicast Address Allocation are compared. HAM integrates the merits of CM and DDM, which is efficient as a whole, robust andscalable. CCH raises the efficiency of connection control, and is highly robust, flexible and scalable.

  17. Enforcing Access Control in Virtual Organizations Using Hierarchical Attribute-Based Encryption

    CERN Document Server

    Asim, Muhammad; Petkovic, Milan; Trivellato, Daniel; Zannone, Nicola

    2012-01-01

    Virtual organizations are dynamic, inter-organizational collaborations that involve systems and services belonging to different security domains. Several solutions have been proposed to guarantee the enforcement of the access control policies protecting the information exchanged in a distributed system, but none of them addresses the dynamicity characterizing virtual organizations. In this paper we propose a dynamic hierarchical attribute-based encryption (D-HABE) scheme that allows the institutions in a virtual organization to encrypt information according to an attribute-based policy in such a way that only users with the appropriate attributes can decrypt it. In addition, we introduce a key management scheme that determines which user is entitled to receive which attribute key from which domain authority.

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

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

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

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

    Science.gov (United States)

    Lee, HyunRyong; Kim, JongWon

    2006-10-01

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

  20. 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.

  1. Knowledge-based Approach for Event Extraction from Arabic Tweets

    Directory of Open Access Journals (Sweden)

    Mohammad AL-Smadi

    2016-06-01

    Full Text Available Tweets provide a continuous update on current events. However, Tweets are short, personalized and noisy, thus raises more challenges for event extraction and representation. Extracting events out of Arabic tweets is a new research domain where few examples – if any – of previous work can be found. This paper describes a knowledge-based approach for fostering event extraction out of Arabic tweets. The approach uses an unsupervised rule-based technique for event extraction and provides a named entity disambiguation of event related entities (i.e. person, organization, and location. Extracted events and their related entities are populated to the event knowledge base where tagged tweets’ entities are linked to their corresponding entities represented in the knowledge base. Proposed approach was evaluated on a dataset of 1K Arabic tweets covering different types of events (i.e. instant events and interval events. Results show that the approach has an accuracy of, 75.9% for event trigger extraction, 87.5% for event time extraction, and 97.7% for event type identification.

  2. ESL Based Cylindrical Shell Elements with Hierarchical Shape Functions for Laminated Composite Shells

    Directory of Open Access Journals (Sweden)

    Jae S. Ahn

    2015-01-01

    Full Text Available We introduce higher-order cylindrical shell element based on ESL (equivalent single-layer theory for the analysis of laminated composite shells. The proposed elements are formulated by the dimensional reduction technique from three-dimensional solid to two-dimensional cylindrical surface with plane stress assumption. It allows the first-order shear deformation and considers anisotropic materials due to fiber orientation. The element displacement approximation is established by the integrals of Legendre polynomials with hierarchical concept to ensure the C0-continuity at the interface between adjacent elements as well as C1-continuity at the interface between adjacent layers. For geometry mapping, cylindrical coordinate is adopted to implement the exact mapping of curved shell configuration with a constant curvature with respect to any direction in the plane. The verification and characteristics of the proposed element are investigated through the analyses of three cylindrical shell problems with different shapes, loadings, and boundary conditions.

  3. A hierarchical layout design method based on rubber band potentialenergy descending

    Directory of Open Access Journals (Sweden)

    Ou Cheng Yi

    2016-01-01

    Full Text Available Strip packing problems is one important sub-problem of the Cutting stock problems. Its application domains include sheet metal, ship making, wood, furniture, garment, shoes and glass. In this paper, a hierarchical layout design method based on rubber band potential-energy descending was proposed. The basic concept of the rubber band enclosing model was described in detail. We divided the layout process into three different stages: initial layout stage, rubber band enclosing stage and local adjustment stage. In different stages, the most efficient strategies were employed for further improving the layout solution. Computational results show that the proposed method performed better than the GLSHA algorithm for three out of nine instances in utilization.

  4. Towards a Formal Semantics for UML/MARTE State Machines Based on Hierarchical Timed Automata

    Institute of Scientific and Technical Information of China (English)

    Yu Zhou; Luciano Baresi; Matteo Rossi

    2013-01-01

    UML is a widely-used,general purpose modeling language.But its lack of a rigorous semantics forbids the thorough analysis of designed solution,and thus precludes the discovery of significant problems at design time.To bridge the gap,the paper investigates the underlying semantics of UML state machine diagrams,along with the time-related modeling elements of MARTE,the profile for modeling and analysis of real-time embedded systems,and proposes a formal operational semantics based on extended hierarchical timed automata.The approach is exemplified on a simple example taken from the automotive domain.Verification is accomplished by translating designed models into the input language of the UPPAAL model checker.

  5. A special hierarchical fuzzy neural-networks based reinforcement learning for multi-variables system

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wen-zhi; LU Tian-sheng

    2005-01-01

    Proposes a reinforcement learning scheme based on a special Hierarchical Fuzzy Neural-Networks (HFNN) for solving complicated learning tasks in a continuous multi-variables environment. The output of the previous layer in the HFNN is no longer used as if-part of the next layer, but used only in then-part. Thus it can deal with the difficulty when the output of the previous layer is meaningless or its meaning is uncertain. The proposed HFNN has a minimal number of fuzzy rules and can successfully solve the problem of rules combination explosion and decrease the quantity of computation and memory requirement. In the learning process, two HFNN with the same structure perform fuzzy action composition and evaluation function approximation simultaneously where the parameters of neural-networks are tuned and updated on line by using gradient descent algorithm. The reinforcement learning method is proved to be correct and feasible by simulation of a double inverted pendulum system.

  6. HIERARCHICAL CLASSIFICATION OF POLARIMETRIC SAR IMAGE BASED ON STATISTICAL REGION MERGING

    Directory of Open Access Journals (Sweden)

    F. Lang

    2012-07-01

    Full Text Available Segmentation and classification of polarimetric SAR (PolSAR imagery are very important for interpretation of PolSAR data. This paper presents a new object-oriented classification method which is based on Statistical Region Merging (SRM segmentation algorithm and a two-level hierarchical clustering technique. The proposed method takes full advantage of the polarimetric information contained in the PolSAR data, and takes both effectiveness and efficiency into account according to the characteristic of PolSAR. A modification of over-merging to over-segmentation technique and a post processing of segmentation for SRM is proposed according to the application of classification. And a revised symmetric Wishart distance is derived from the Wishart PDF. Segmentation and classification results of AirSAR L-band PolSAR data over the Flevoland test site is shown to demonstrate the validity of the proposed method.

  7. Identifying rock blocks based on hierarchical rock-mass structure model

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Rock-masses are divided into many closed blocks by deterministic and stochastic discontinuities and engineering interfaces in complex rock-mass engineering. Determining the sizes, shapes, and adjacent relations of blocks is important for stability analysis of fractured rock masses. Here we propose an algorithm for identifying spatial blocks based on a hierarchical 3D Rock-mass Structure Model (RSM). First, a model is built composed of deterministic discontinuities, engineering interfaces, and the earth’s surface, and the deterministic blocks surrounded by these interfaces are traced. Then, in each deter-ministic block, a network model of stochastic discontinuities is built and the stochastic blocks are traced. Building a unitary wire frame that connects all interfaces seamlessly is the key for our algorithm to identify the above two kinds of blocks. Using this algorithm, geometric models can be built for block theory, discrete element method, and discontinuous deformation analysis.

  8. Hierarchical Pathfinding and AI-Based Learning Approach in Strategy Game Design

    Directory of Open Access Journals (Sweden)

    Le Minh Duc

    2008-01-01

    Full Text Available Strategy game and simulation application are an exciting area with many opportunities for study and research. Currently most of the existing games and simulations apply hard coded rules so the intelligence of the computer generated forces is limited. After some time, player gets used to the simulation making it less attractive and challenging. It is also costly and tedious to incorporate new rules for an existing game. The main motivation behind this research project is to improve the quality of artificial intelligence- (AI- based on various techniques such as qualitative spatial reasoning (Forbus et al., 2002, near-optimal hierarchical pathfinding (HPA* (Botea et al., 2004, and reinforcement learning (RL (Sutton and Barto, 1998.

  9. 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.

  10. An Event Grouping Based Algorithm for University Course Timetabling Problem

    OpenAIRE

    Kralev, Velin; Kraleva, Radoslava; Yurukov, Borislav

    2016-01-01

    This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm base...

  11. An Event Grouping Based Algorithm for University Course Timetabling Problem

    OpenAIRE

    Kralev, Velin; Kraleva, Radoslava; Yurukov, Borislav

    2016-01-01

    This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm base...

  12. 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

  13. An event-based model for contracts

    Directory of Open Access Journals (Sweden)

    Tiziana Cimoli

    2013-02-01

    Full Text Available We introduce a basic model for contracts. Our model extends event structures with a new relation, which faithfully captures the circular dependencies among contract clauses. We establish whether an agreement exists which respects all the contracts at hand (i.e. all the dependencies can be resolved, and we detect the obligations of each participant. The main technical contribution is a correspondence between our model and a fragment of the contract logic PCL. More precisely, we show that the reachable events are exactly those which correspond to provable atoms in the logic. Despite of this strong correspondence, our model improves previous work on PCL by exhibiting a finer-grained notion of culpability, which takes into account the legitimate orderings of events.

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2014-08-01

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

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

    Science.gov (United States)

    Gulbis, Michael; Müller, Erika

    2010-05-01

    Content-based audio authentication watermarking techniques extract perceptual relevant audio features, which are robustly embedded into the audio file to protect. Manipulations of the audio file are detected on the basis of changes between the original embedded feature information and the anew extracted features during verification. The main challenges of content-based watermarking are on the one hand the identification of a suitable audio feature to distinguish between content preserving and malicious manipulations. On the other hand the development of a watermark, which is robust against content preserving modifications and able to carry the whole authentication information. The payload requirements are significantly higher compared to transaction watermarking or copyright protection. Finally, the watermark embedding should not influence the feature extraction to avoid false alarms. Current systems still lack a sufficient alignment of watermarking algorithm and feature extraction. In previous work we developed a content-based audio authentication watermarking approach. The feature is based on changes in DCT domain over time. A patchwork algorithm based watermark was used to embed multiple one bit watermarks. The embedding process uses the feature domain without inflicting distortions to the feature. The watermark payload is limited by the feature extraction, more precisely the critical bands. The payload is inverse proportional to segment duration of the audio file segmentation. Transparency behavior was analyzed in dependence of segment size and thus the watermark payload. At a segment duration of about 20 ms the transparency shows an optimum (measured in units of Objective Difference Grade). Transparency and/or robustness are fast decreased for working points beyond this area. Therefore, these working points are unsuitable to gain further payload, needed for the embedding of the whole authentication information. In this paper we present a hierarchical extension

  17. Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Marine information has been increasing quickly. The traditional database technologies have disadvantages in manipulating large amounts of marine information which relates to the position in 3-D with the time. Recently, greater emphasis has been placed on GIS (geographical information system)to deal with the marine information. The GIS has shown great success for terrestrial applications in the last decades, but its use in marine fields has been far more restricted. One of the main reasons is that most of the GIS systems or their data models are designed for land applications. They cannot do well with the nature of the marine environment and for the marine information. And this becomes a fundamental challenge to the traditional GIS and its data structure. This work designed a data model,the raster-based spatio-temporal hierarchical data model (RSHDM), for the marine information system, or for the knowledge discovery from spatio-temporal data, which bases itself on the nature of the marine data and overcomes the shortages of the current spatio-temporal models when they are used in the field. As an experiment, the marine fishery data warehouse (FDW) for marine fishery management was set up, which was based on the RSHDM. The experiment proved that the RSHDM can do well with the data and can extract easily the aggregations that the management needs at different levels.

  18. 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.

  19. 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.

  20. 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.

  1. Hierarchical 3D mechanical parts matching based-on adjustable geometry and topology similarity measurements

    Institute of Scientific and Technical Information of China (English)

    马嵩华; 田凌

    2014-01-01

    A hierarchical scheme of feature-based model similarity measurement was proposed, named CSG_D2, in which both geometry similarity and topology similarity were applied. The features of 3D mechanical part were constructed by a series of primitive features with tree structure, as a form of constructive solid geometry (CSG) tree. The D2 shape distributions of these features were extracted for geometry similarity measurement, and the pose vector and non-disappeared proportion of each leaf node were gained for topology similarity measurement. Based on these, the dissimilarity between the query and the candidate was accessed by level-by-level CSG tree comparisons. With the adjustable weights, our scheme satisfies different comparison emphasis on the geometry or topology similarity. The assessment results from CSG_D2 demonstrate more discriminative than those from D2 in the analysis of precision-recall and similarity matrix. Finally, an experimental search engine is applied for mechanical parts reuse by using CSG_D2, which is convenient for the mechanical design process.

  2. 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.

  3. A hierarchical model for structure learning based on the physiological characteristics of neurons

    Institute of Scientific and Technical Information of China (English)

    WEI Hui

    2007-01-01

    Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability.The characteristics of typical ANN models are fixed connections,with evolved weights,globalized representations,and globalized optimizations,all based on a mathematical approach.This makes those models to be deficient in robustness,efficiency of learning,capacity,anti-jamming between training sets,and correlativity of samples,etc.In this paper,we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing.A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures.The basic characteristics of this model are localized and random connections,field limitations of neuron fan-in and fan-out,dynamic behavior of neurons,and samples represented through different sub-circuits of neurons specialized into different response patterns.At the end of this paper,some important aspects of error correction,capacity,learning efficiency,and soundness of structural representation are analyzed theoretically.This paper has demonstrated the feasibility and advantages of structure learning and representation.This model can serve as a fundamental element of cognitive systems such as perception and associative memory.Key-words structure learning,representation,associative memory,computational neuroscience

  4. Enhancing the Discrete Particle Swarm Optimization based Workflow Grid Scheduling using Hierarchical Structure

    Directory of Open Access Journals (Sweden)

    Ritu Garg

    2013-05-01

    Full Text Available The problem of scheduling dependent tasks (DAG is an important version of scheduling, to efficiently exploit the computational capabilities of grid systems. The problem of scheduling tasks of a graph onto a set of different machines is an NP Complete problem. As a result, a number of heuristic and meta-heuristic approaches are used over the years due to their ability of providing high quality solutions with reasonable computation time. Discrete Particle Swarm Optimization is one such meta-heuristic used for solving the discrete problem of grid scheduling, but this method converge to sub optimal solutions due to premature convergence. To deal with premature convergence, in this paper we proposed the design and implementation of hierarchical discrete particle swarm optimization (H-DPSO for dependent task scheduling in grid environment. In H-DPSO particles are arranged in dynamic hierarchy where good particles lying above in hierarchy are having larger influence on the swarm. We consider the bi-objective version of problem to minimize makespan and total cost simultaneously as the optimization criteria. The H-DPSO based scheduler was evaluated under different application task graphs. Simulation analysis manifests that H-DPSO based scheduling is highly viable and effective approach for grid computing.

  5. 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.

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

    Science.gov (United States)

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

    2002-01-01

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

  7. Grid-Enabling SPMD Applications through Hierarchical Partitioning and a Component-Based Runtime

    Science.gov (United States)

    Mathias, Elton; Cavé, Vincent; Lanteri, Stéphane; Baude, Françoise

    Developing highly communicating scientific applications capable of efficiently use computational grids is not a trivial task. Ideally, these applications should consider grid topology 1) during the mesh partitioning, to balance workload among heterogeneous resources and exploit physical neighborhood, and 2) in communications, to lower the impact of latency and reduced bandwidth. Besides, this should not be a complex matter in end-users applications. These are the central concerns of the DiscoGrid project, which promotes the concept of a hierarchical SPMD programming model, along with a grid-aware multi-level mesh partitioning to enable the treatment of grid issues by the underlying runtime, in a seamless way for programmers. In this paper, we present the DiscoGrid project and the work around the GCM/ProActive-based implementation of the DiscoGrid Runtime. Experiments with a non-trivial computational electromagnetics application show that the component-based approach offers a flexible and efficient support and that the proposed programming model can ease the development of such applications.

  8. 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.

  9. Quality Assured Optimal Resource Provisioning and Scheduling Technique Based on Improved Hierarchical Agglomerative Clustering Algorithm (IHAC

    Directory of Open Access Journals (Sweden)

    A. Meenakshi

    2016-08-01

    Full Text Available Resource allocation is the task of convenient resources to different uses. In the context of an resources, entire economy, can be assigned by different means, such as markets or central planning. Cloud computing has become a new age technology that has got huge potentials in enterprises and markets. Clouds can make it possible to access applications and associated data from anywhere. The fundamental motive of the resource allocation is to allot the available resource in the most effective manner. In the initial phase, a representative resource usage distribution for a group of nodes with identical resource usage patterns is evaluated as resource bundle which can be easily employed to locate a group of nodes fulfilling a standard criterion. In the document, an innovative clustering-based resource aggregation viz. the Improved Hierarchal Agglomerative Clustering Algorithm (IHAC is elegantly launched to realize the compact illustration of a set of identically behaving nodes for scalability. In the subsequent phase concerned with energetic resource allocation procedure, the hybrid optimization technique is brilliantly brought in. The novel technique is devised for scheduling functions to cloud resources which duly consider both financial and evaluation expenses. The efficiency of the novel Resource allocation system is assessed by means of several parameters such the reliability, reusability and certain other metrics. The optimal path choice is the consequence of the hybrid optimization approach. The new-fangled technique allocates the available resource based on the optimal path.

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

    Science.gov (United States)

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

    2017-07-01

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

  11. 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.

  12. A hierarchical algorithm for cyberspace situational awareness based on analytic hierarchy process

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The existing network security management systems are unable either to provide users with useful security situation and risk assessment, or to aid administrators to make right and timely decisions based on the current state of network. These disadvantages always put the whole network security management at high risk. This paper establishes a simulation environment, captures the alerts as the experimental data and adopts statistical analysis to seek the vulnerabilities of the services provided by the hosts in the network. According to the factors of the network, the paper introduces the two concepts: Situational Meta and Situational Weight to depict the total security situation. A novel hierarchical algorithm based on analytic hierarchy process (AHP) is proposed to analyze the hierarchy of network and confirm the weighting coefficients. The algorithm can be utilized for modeling security situation, and determining its mathematical expression. Coupled with the statistical results, this paper simulates the security situational trends.Finally, the analysis of the simulation results proves the algorithm efficient and applicable, and provides us with an academic foundation for the implementation in the security situation.

  13. Hierarchical Clustering Algorithm based on Attribute Dependency for Attention Deficit Hyperactive Disorder

    Directory of Open Access Journals (Sweden)

    J Anuradha

    2014-05-01

    Full Text Available Attention Deficit Hyperactive Disorder (ADHD is a disruptive neurobehavioral disorder characterized by abnormal behavioral patterns in attention, perusing activity, acting impulsively and combined types. It is predominant among school going children and it is tricky to differentiate between an active and an ADHD child. Misdiagnosis and undiagnosed cases are very common. Behavior patterns are identified by the mentors in the academic environment who lack skills in screening those kids. Hence an unsupervised learning algorithm can cluster the behavioral patterns of children at school for diagnosis of ADHD. In this paper, we propose a hierarchical clustering algorithm to partition the dataset based on attribute dependency (HCAD. HCAD forms clusters of data based on the high dependent attributes and their equivalence relation. It is capable of handling large volumes of data with reasonably faster clustering than most of the existing algorithms. It can work on both labeled and unlabelled data sets. Experimental results reveal that this algorithm has higher accuracy in comparison to other algorithms. HCAD achieves 97% of cluster purity in diagnosing ADHD. Empirical analysis of application of HCAD on different data sets from UCI repository is provided.

  14. A spatio-velocity model based semantic event detection algorithm for traffic surveillance video

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Detection of vehicle events is a research hotspot in digital traffic.In this paper,an approach is proposed to detect vehicle events with semantic analysis of traffic surveillance video using spatio-velocity statistic models.The approach includes two successive phases:trajectory clustering and semantic events detection.For trajectory clustering,a statistic model of vehicle trajectories are presented,for which a spatio-velocity model is trained by analyzing the trajectories of moving vehicles in the scene.Based on the trajectory,which represents both the position of the vehicle and its instantaneous velocity,a trajectory similarity measure is proposed.Then,an improved hierarchical clustering algorithm is adopted to cluster the trajectories according to different spatial and velocity distributions.In each cluster,trajectories that are spatially close have similar velocities of motion and represent one type of activity pattern.For the semantic events detection phase,statistic models of semantic regions in the scene are generated by estimating the probability density and velocity distributions of each type of activity pattern.Finally,semantic events are detected by the proposed spatio-velocity statistic models.The paper also presents experiments using real video sequence to verify the effectiveness of the proposed method.

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Jun Ren

    2014-01-01

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

  17. Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2006-06-01

    Full Text Available Abstract Background The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. Results A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. Conclusion This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request.

  18. AERODYNAMIC OPTIMIZATION FOR TURBINE BLADE BASED ON HIERARCHICAL FAIR COMPETITION GENETIC ALGORITHMS WITH DYNAMIC NICHE

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A global optimization approach to turbine blade design based on hierarchical fair competition genetic algorithms with dynamic niche (HFCDN-GAs) coupled with Reynolds-averaged Navier-Stokes (RANS) equation is presented. In order to meet the search theory of GAs and the aerodynamic performances of turbine, Bezier curve is adopted to parameterize the turbine blade profile, and a fitness function pertaining to optimization is designed. The design variables are the control points' ordinates of characteristic polygon of Bezier curve representing the turbine blade profile. The object function is the maximum lift-drag ratio of the turbine blade. The constraint conditions take into account the leading and trailing edge metal angle, and the strength and aerodynamic performances of turbine blade. And the treatment method of the constraint conditions is the flexible penalty function. The convergence history of test function indicates that HFCDN-GAs can locate the global optimum within a few search steps and have high robustness. The lift-drag ratio of the optimized blade is 8.3% higher than that of the original one. The results show that the proposed global optimization approach is effective for turbine blade.

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Science.gov (United States)

    DeSouza, Guilherme N; Kak, Avinash C

    2004-10-01

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

  1. A Dynamic Key Management Scheme Based on Secret Sharing for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Enjian Bai

    2013-01-01

    Full Text Available Since wireless sensor networks (WSN for short are often deployed in hostile environments in many applications, security becomes one of the critical issues in WSN. Moreover, due to the limitation of the sensor nodes, traditional key management schemes are not suitable for it. Thereby,a feasible and efficient key management scheme is an important guarantee for WSN to communicate securely. For the moment, many protocols have been proposed and each has its own advantages. However, these protocols cannot provide sufficient security in many cases, such as node capture attack, which makes WSN more vulnerable than traditional wireless networks. Key protection and revocation issues must be considered with special attention in WSN. To address these two issues, we propose a dynamically clustering key management scheme based on secret sharing for WSN. The scheme combined the hierarchical structure of wireless sensor networks with dynamic key management scheme. The analysis results show that the scheme has strong security and resistance of captured attack, as well as low communicational overhead, and it well meets the requirement of scalability.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-06-05

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

  3. Robust Face Recognition by Hierarchical Kernel Associative Memory Models Based on Spatial Domain Gabor Transforms

    Directory of Open Access Journals (Sweden)

    Bai-ling Zhang

    2006-07-01

    Full Text Available Face recognition can be studied as an associative memory (AM problem and kernel-based AM models have been proven efficient. In this paper, a hierarchical Kernel Associative Memory (KAM face recognition scheme with a multiscale Gabor transform, is proposed. The pyramidal multiscale Gabor decomposition proposed by Nestares, Navarro, Portilla and Tabernero not only provides a very efficient implementation of the Gabor transform in the spatial domain, but also permits a fast reconstruction of images. In our method, face images of each person are first decomposed into their multiscale representations by a quasicomplete Gabor transform, which are then modelled by Kernel Associative Memories. In the recognition stage, a query face image is also represented by a Gabor multiresolution pyramid and the reconstructions from different KAM models corresponding to even Gabor channels are then simply summed to give the recall. The recognition scheme was thoroughly tested using several benchmarking face datasets, including the AR faces, UMIST faces, JAFFE faces and Yale A faces, which include different kind of face variations from occlusions, pose, expression and illumination. The experiment results show that the proposed method demonstrated strong robustness in recognizing faces under different conditions, particularly under occlusions, pose alterations and expression changes.

  4. 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.

  5. A new Hierarchical Group Key Management based on Clustering Scheme for Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Ayman EL-SAYED

    2014-05-01

    Full Text Available The migration from wired network to wireless network has been a global trend in the past few decades because they provide anytime-anywhere networking services. The wireless networks are rapidly deployed in the future, secure wireless environment will be mandatory. As well, The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks,Mobile Ad hoc Networks (MANET is one of the most important and unique applications. MANET is a collection of autonomous nodes or terminals which communicate with each other by forming a multihop radio network and maintaining connectivity in a decentralized manner. Due to the nature of unreliable wireless medium data transfer is a major problem in MANET and it lacks security and reliability of data. The most suitable solution to provide the expected level of security to these services is the provision of a key management protocol. A Key management is vital part of security. This issue is even bigger in wireless network compared to wired network. The distribution of keys in an authenticated manner is a difficult task in MANET. When a member leaves or joins the group, it needs to generate a new key to maintain forward and backward secrecy. In this paper, we propose a new group key management schemes namely a Hierarchical, Simple, Efficient and Scalable Group Key (HSESGK based on clustering management scheme for MANETs and different other schemes are classified. Group members deduce the group key in a distributed manner.

  6. Mobile Agent Based Hierarchical Intrusion Detection System in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Surraya Khanum

    2012-01-01

    Full Text Available Security mechanism is a fundamental requirement of wireless networks in general and Wireless Sensor Networks (WSN in particular. Therefore, it is necessary that this security concern must be articulate right from the beginning of the network design and deployment. WSN needs strong security mechanism as it is usually deployed in a critical, hostile and sensitive environment where human labour is usually not involved. However, due to inbuilt resource and computing restriction, security in WSN needs a special consideration. Traditional security techniques such as encryption, VPN, authentication and firewalls cannot be directly applied to WSN as it provides defence only against external threats. The existing literature shows that there seems an inverse relationship between strong security mechanism and efficient network resource utilization. In this research article, we have proposed a Mobile Agent Based Hierarchical Intrusion Detection System (MABHIDS for WSN. The Proposed scheme performs two levels of intrusion detection by utilizing minimum possible network resources. Our proposed idea enhance network lifetime by reducing the work load on Cluster Head (CH and it also provide enhanced level of security in WSN.

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

    Science.gov (United States)

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

    2017-02-01

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

  8. Automatic Curve Fitting Based on Radial Basis Functions and a Hierarchical Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    G. Trejo-Caballero

    2015-01-01

    Full Text Available Curve fitting is a very challenging problem that arises in a wide variety of scientific and engineering applications. Given a set of data points, possibly noisy, the goal is to build a compact representation of the curve that corresponds to the best estimate of the unknown underlying relationship between two variables. Despite the large number of methods available to tackle this problem, it remains challenging and elusive. In this paper, a new method to tackle such problem using strictly a linear combination of radial basis functions (RBFs is proposed. To be more specific, we divide the parameter search space into linear and nonlinear parameter subspaces. We use a hierarchical genetic algorithm (HGA to minimize a model selection criterion, which allows us to automatically and simultaneously determine the nonlinear parameters and then, by the least-squares method through Singular Value Decomposition method, to compute the linear parameters. The method is fully automatic and does not require subjective parameters, for example, smooth factor or centre locations, to perform the solution. In order to validate the efficacy of our approach, we perform an experimental study with several tests on benchmarks smooth functions. A comparative analysis with two successful methods based on RBF networks has been included.

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

    Science.gov (United States)

    Hu, Jinyan; Li, Li; Yang, Yunfeng

    2017-06-01

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

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

    Directory of Open Access Journals (Sweden)

    M. Kalpana

    2014-01-01

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

  11. An event-based account of conformity.

    Science.gov (United States)

    Kim, Diana; Hommel, Bernhard

    2015-04-01

    People often change their behavior and beliefs when confronted with deviating behavior and beliefs of others, but the mechanisms underlying such phenomena of conformity are not well understood. Here we suggest that people cognitively represent their own actions and others' actions in comparable ways (theory of event coding), so that they may fail to distinguish these two categories of actions. If so, other people's actions that have no social meaning should induce conformity effects, especially if those actions are similar to one's own actions. We found that female participants adjusted their manual judgments of the beauty of female faces in the direction consistent with distracting information without any social meaning (numbers falling within the range of the judgment scale) and that this effect was enhanced when the distracting information was presented in movies showing the actual manual decision-making acts. These results confirm that similarity between an observed action and one's own action matters. We also found that the magnitude of the standard conformity effect was statistically equivalent to the movie-induced effect.

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

    Science.gov (United States)

    Liu, Ning; Wu, Hefeng; Lin, Liang

    2015-01-01

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

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

    Science.gov (United States)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2008-06-01

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

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

    Science.gov (United States)

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

    2014-10-01

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

  16. Hierarchical hybrid testability modeling and evaluation method based on information fusion

    Institute of Scientific and Technical Information of China (English)

    Xishan Zhang; Kaoli Huang; Pengcheng Yan; Guangyao Lian

    2015-01-01

    In order to meet the demand of testability analysis and evaluation for complex equipment under a smal sample test in the equipment life cycle, the hierarchical hybrid testability model-ing and evaluation method (HHTME), which combines the testabi-lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo-logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob-ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in-formation. Final y, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accurate.

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

    Science.gov (United States)

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

    2017-03-01

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

  18. 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.

  19. Analysis of acoustic cardiac signals for heart rate variability and murmur detection using nonnegative matrix factorization-based hierarchical decomposition

    DEFF Research Database (Denmark)

    Shah, Ghafoor; Koch, Peter; Papadias, Constantinos B.

    2014-01-01

    . A novel method based on hierarchical decomposition of the single channel mixture using various nonnegative matrix factorization techniques is proposed, which provides unsupervised clustering of the underlying component signals. HRV is determined over the recovered normal cardiac acoustic signals....... This novel decomposition technique is compared against the state-of-the-art techniques; experiments are performed using real-world clinical data, which show the potential significance of the proposed technique....

  20. Event-Based Corpuscular Model for Quantum Optics Experiments

    NARCIS (Netherlands)

    Michielsen, K.; Jin, F.; Raedt, H. De

    2011-01-01

    A corpuscular simulation model of optical phenomena that does not require the knowledge of the solution of a wave equation of the whole system and reproduces the results of Maxwell's theory by generating detection events one-by-one is presented. The event-based corpuscular model is shown to give a u

  1. Event-Based Corpuscular Model for Quantum Optics Experiments

    NARCIS (Netherlands)

    Michielsen, K.; Jin, F.; Raedt, H. De

    A corpuscular simulation model of optical phenomena that does not require the knowledge of the solution of a wave equation of the whole system and reproduces the results of Maxwell's theory by generating detection events one-by-one is presented. The event-based corpuscular model is shown to give a

  2. Event-based Simulation Model for Quantum Optics Experiments

    NARCIS (Netherlands)

    De Raedt, H.; Michielsen, K.; Jaeger, G; Khrennikov, A; Schlosshauer, M; Weihs, G

    2011-01-01

    We present a corpuscular simulation model of optical phenomena that does not require the knowledge of the solution of a wave equation of the whole system and reproduces the results of Maxwell's theory by generating detection events one-by-one. The event-based corpuscular model gives a unified

  3. Application of Parallel Tabu Search Based Hierarchical Optimization to Distribution System Service Restoration

    Science.gov (United States)

    Furuta, Atsuhiro; Mori, Hiroyuki

    This paper proposes a hybrid method of hierarchical optimization and Parallel Tabu Search (PTS) for distribution system service restoration with distributed generators. The objective is to evaluate the optimal route to recover the service. The improvement of power quality makes the service restoration more important. Distribution system service restoration is one of complicated combinational optimization problems that are expressed as nonlinear mixed integer programming. In this paper, an efficient method is proposed to restore the service in a hierarchical optimization with Parallel Tabu Search. The proposed method is tested in a sample system.

  4. AN HMM BASED ANALYSIS FRAMEWORK FOR SEMANTIC VIDEO EVENTS

    Institute of Scientific and Technical Information of China (English)

    You Junyong; Liu Guizhong; Zhang Yaxin

    2007-01-01

    Semantic video analysis plays an important role in the field of machine intelligence and pattern recognition. In this paper, based on the Hidden Markov Model (HMM), a semantic recognition framework on compressed videos is proposed to analyze the video events according to six low-level features. After the detailed analysis of video events, the pattern of global motion and five features in foreground--the principal parts of videos, are employed as the observations of the Hidden Markov Model to classify events in videos. The applications of the proposed framework in some video event detections demonstrate the promising success of the proposed framework on semantic video analysis.

  5. Event-based processing of neutron scattering data

    Science.gov (United States)

    Peterson, Peter F.; Campbell, Stuart I.; Reuter, Michael A.; Taylor, Russell J.; Zikovsky, Janik

    2015-12-01

    Many of the world's time-of-flight spallation neutrons sources are migrating to recording individual neutron events. This provides for new opportunities in data processing, the least of which is to filter the events based on correlating them with logs of sample environment and other ancillary equipment. This paper will describe techniques for processing neutron scattering data acquired in event mode which preserve event information all the way to a final spectrum, including any necessary corrections or normalizations. This results in smaller final uncertainties compared to traditional methods, while significantly reducing processing time and memory requirements in typical experiments. Results with traditional histogramming techniques will be shown for comparison.

  6. 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.

  7. A Social Marketing Based Strategy For Planning Diversity Events

    Directory of Open Access Journals (Sweden)

    Sambhavi Lakshminarayanan

    2011-07-01

    Full Text Available Organizations are both enriched and challenged by diversity. Organizational diversity management is based on several factors such as strategy, competitive positioning and internal culture. Most organizations hold events of various kinds as part of their diversity strategy. Although participation in events is often mandated, such as in training programs, providing opportunities for voluntary participation is also important. In particular, organizing events in which participation is voluntary signals that management is willing to be responsive and flexible. Events, in general, are a highly visible aspect of diversity programs and serve many purposes, such as providing information, building awareness and creating social capital. On the other hand, there are associated costs. Consequently, organizations need to plan events carefully in order to obtain their full benefit. This paper presents a comprehensive strategy for planning, publicising and organizing diversity related events. The strategy addresses the interests and needs of all individuals in the organization with a goal of maximizing voluntary participation.  A simple yet powerful method from (social marketing is used in constructing the comprehensive strategy: that of market segmentation. In this paper, individuals in an organization are classified into four segments. Events, too, are classified into four types – support, celebratory, educational and training. Each segment responds best to a specific type of event. This link between segments and events is used to formulate the strategy that recommends organizing all four types of events, during a planning period, as part of the diversity management effort. 

  8. 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.

  9. Discharges of past flood events based on historical river profiles

    Directory of Open Access Journals (Sweden)

    D. Sudhaus

    2008-10-01

    Full Text Available This paper presents a case study on the estimation of peak discharges of extreme flood events during the 19th century of the Neckar River located in south-western Germany. It was carried out as part of the BMBF (German Federal Ministry of Education and Research research project RIMAX (Risk Management of Extreme Flood Events. The discharge estimations were made for the 1824 and 1882 flood events, and are based on historical cross profiles. The 1-D model Hydrologic Engineering Centers River Analysis System (HEC-RAS was applied with different roughness coefficients to determine these estimations. The results are compared (i with contemporary historical calculations for the 1824 and 1882 flood events and (ii in the case of the flood event in 1824, with the discharge simulation by the water balance model LARSIM (Large Area Runoff Simulation Model. These calculations are matched by the HEC-RAS simulation based on the standard roughness coefficients.

  10. 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 a

  11. 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

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

    Science.gov (United States)

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

    2013-09-15

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

  13. UV-Enhanced Room Temperature Ozone Sensor Based on Hierarchical SnO2-In2O3

    Institute of Scientific and Technical Information of China (English)

    SUN Jian-bo; XU Jing; WANG Biao; SUN Peng; LIU Feng-min; LU Ge-yu

    2012-01-01

    SnO2-In2O3 hierarchical microspheres were prepared by the hydrothcrmal and solvothermal method.The morphology,phase crystallinity of the obtained SnO2-In2O3 were measured by X-ray diffraction(XRD),scan electron microscopy(SEM),respectively.A room temperature ozone sensor based on SnO2-In2O3 hierarchical microsphcres was fabricated and investigated.The gas sensing properties of the sensor using SnO2-In2O3 strongly depended on the proportion of SnO2 and In2O3.The sensitivity and response/recovery speed were greatly enhanced by UV illumination.A gas sensing mechanism related to oxygen defect was suggested.

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

    Science.gov (United States)

    Chatterjee, Tirtha

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

  15. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

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

    2015-02-11

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

  16. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

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

    2015-02-01

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

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

    Science.gov (United States)

    Haq, Mahmoodul

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

  18. Power quality events recognition using a SVM-based method

    Energy Technology Data Exchange (ETDEWEB)

    Cerqueira, Augusto Santiago; Ferreira, Danton Diego; Ribeiro, Moises Vidal; Duque, Carlos Augusto [Department of Electrical Circuits, Federal University of Juiz de Fora, Campus Universitario, 36036 900, Juiz de Fora MG (Brazil)

    2008-09-15

    In this paper, a novel SVM-based method for power quality event classification is proposed. A simple approach for feature extraction is introduced, based on the subtraction of the fundamental component from the acquired voltage signal. The resulting signal is presented to a support vector machine for event classification. Results from simulation are presented and compared with two other methods, the OTFR and the LCEC. The proposed method shown an improved performance followed by a reasonable computational cost. (author)

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

    Science.gov (United States)

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

    2014-06-01

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

  20. 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...... proportionally and directly proportionally, respectively, to the state of charge (SoC) of each battery unit during discharging and charging mode. To evaluate this decentralized method based on the IEC/ISO 62264 standard, PSCAD/EMTDC software is used....

  1. Internet-based event synchronization communication driven telerobotics

    Institute of Scientific and Technical Information of China (English)

    Xie Xiaohui; Sun Lining; Du Zhijiang; Cai Hegao

    2005-01-01

    Based on QoS (quality of service) parameters: time delay, jitter, bandwidth and package loss. As time delay in the Internet is variable, it is hard to compensate it by traditional methods. Event synchronization communication driven method is proposed to overcome the negative effects induced by time delay. This method is a non-time based method and it can get rid of the effects of time in the control loop of telerobotics. Stability, transparency and synchronization can be maintained in it by event-driven method. Multimodal enhanced telerobotics is put forward with its feedback including force, video, audio and temperature etc. The use of multimodal feedback improves the efficiency and safety of the whole system. Synchronization in multimodal feedback is hard to ensure and event-driven method is also good for it. Experiments on an Internet-based shaft-hole assemblage system show good results by using event synchronization communication driven method and UDP protocol.

  2. 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

  3. Spatiotemporal Features for Asynchronous Event-based Data

    Directory of Open Access Journals (Sweden)

    Xavier eLagorce

    2015-02-01

    Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

  4. Static Analysis for Event-Based XML Processing

    DEFF Research Database (Denmark)

    Møller, Anders

    2008-01-01

    Event-based processing of XML data - as exemplified by the popular SAX framework - is a powerful alternative to using W3C's DOM or similar tree-based APIs. The event-based approach is a streaming fashion with minimal memory consumption. This paper discusses challenges for creating program analyses...... for SAX applications. In particular, we consider the problem of statically guaranteeing the a given SAX program always produces only well-formed and valid XML output. We propose an analysis technique based on ecisting anglyses of Servlets, string operations, and XML graphs....

  5. Ontology-based prediction of surgical events in laparoscopic surgery

    Science.gov (United States)

    Katić, Darko; Wekerle, Anna-Laura; Gärtner, Fabian; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

    2013-03-01

    Context-aware technologies have great potential to help surgeons during laparoscopic interventions. Their underlying idea is to create systems which can adapt their assistance functions automatically to the situation in the OR, thus relieving surgeons from the burden of managing computer assisted surgery devices manually. To this purpose, a certain kind of understanding of the current situation in the OR is essential. Beyond that, anticipatory knowledge of incoming events is beneficial, e.g. for early warnings of imminent risk situations. To achieve the goal of predicting surgical events based on previously observed ones, we developed a language to describe surgeries and surgical events using Description Logics and integrated it with methods from computational linguistics. Using n-Grams to compute probabilities of followup events, we are able to make sensible predictions of upcoming events in real-time. The system was evaluated on professionally recorded and labeled surgeries and showed an average prediction rate of 80%.

  6. HIERARCHICAL ACCESS CONTROL IN DYNAMIC PEER GROUPS USING SYMMETRIC POLYNOMIAL AND TREE BASED GROUP ELLIPTIC CURVE DIFFIE HELLMAN SCHEME

    Directory of Open Access Journals (Sweden)

    Nafeesa Begum Jeddy

    2014-01-01

    Full Text Available Hierarchical Access Control in group communication is an active area of research which is difficult to achieve it. Its primary objective is to allow users of a higher authority group to access information or resource held by lower group users and preventing the lower group users to access information held by higher class users. Large collection of collaborative applications in organizations inherently has hierarchical structures for functioning, where providing security by efficient group key management is a big challenging issue. While preserving centralized methods for hierarchical access control, it is difficult to achieve efficiency as a single membership change will result in lot of changes which are difficult to maintain. So, using distributed key agreement techniques is more appropriate for this scenario. This study explore on novel group key agreement approach, which combines both the symmetric polynomial scheme and Tree Based Group elliptic Curve key exchange. Also, it yields a secure protocol suite that is good in fault-tolerant and simple. The efficiency of SP-TGECDH is better than many other schemes. Using TGECDH makes the scheme suitable small Low powered devices.

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

    Science.gov (United States)

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

    2015-01-19

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

  8. Towards an Efficient Hierarchical Codebooks for Content-Based Images Retrieval

    Institute of Scientific and Technical Information of China (English)

    Z.Elleuch; K.Marzouki

    2014-01-01

    In space feature quantization, the most important problem is designing an efficient and compact codebook. The hierarchical clustering approach successfully solves the problem of quantifying the feature space in a large vocabulary size. In this paper we propose to use a tree structure of hierarchical self-organizing-map (H-SOM) with the depth length equal to two and a high size of branch factors (50, 100, 200, 400, and 500). Moreover, an incremental learning process of H-SOM is used to overcome the problem of the curse of the dimensionality of space. The method is evaluated on three public datasets. Results exceed the current state-of-art retrieval performance on Kentucky and Oxford5k dataset. However, it is with less performance on the Holidays dataset. The experiment results indicate that the proposed tree structure shows significant improvement with a large number of branch factors.

  9. 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

  10. 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.

  11. Event-based incremental updating of spatio-temporal database

    Institute of Scientific and Technical Information of China (English)

    周晓光; 陈军; 蒋捷; 朱建军; 李志林

    2004-01-01

    Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as event-based incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building's incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.

  12. Semantic Units Based Event Detection in Soccer Videos

    Institute of Scientific and Technical Information of China (English)

    TONGXiao-Feng; LIUQing-Shan; LUHan-Qing; JINHong-Liang

    2005-01-01

    A semantic unit based event detection scheme in soccer videos is proposed in this paper.The scheme can be characterized as a three-layer framework. At the lowest layer, low-level features including color, texture, edge, shape, and motion are extracted. High-level semantic events are defined at the highest layer. In order to connect low-level features and high-level semantics, we design and define some semantic units at the intermediate layer. A semantic unit is composed of a sequence of consecutives frames with the same cue that is deduced from low-level features. Based on semantic units, a Bayesian network is used to reason the probabilities of events. The experiments for shoot and card event detection in soccer videos show that the proposed method has an encouraging performance.

  13. 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.

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

    Science.gov (United States)

    Wirawati, Ika; Iriawan, Nur; Irhamah

    2017-06-01

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

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

    Science.gov (United States)

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

    2016-11-01

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

  16. Topic Modeling Based Image Clustering by Events in Social Media

    OpenAIRE

    2016-01-01

    Social event detection in large photo collections is very challenging and multimodal clustering is an effective methodology to deal with the problem. Geographic information is important in event detection. This paper proposed a topic model based approach to estimate the missing geographic information for photos. The approach utilizes a supervised multimodal topic model to estimate the joint distribution of time, geographic, content, and attached textual information. Then we annotate the missi...

  17. Uncertainty Analysis of Method-Based Operating Event Groups Ranking

    Directory of Open Access Journals (Sweden)

    Zdenko Šimić

    2014-01-01

    Full Text Available Safe operation and industrial improvements are coming from the technology development and operational experience (OE feedback. A long life span for many industrial facilities makes OE very important. Proper assessment and understanding of OE remains a challenge because of organization system relations, complexity, and number of OE events acquired. One way to improve OE events understanding is to focus their investigation and analyze in detail the most important. The OE ranking method is developed to select the most important events based on the basic event parameters and the analytical hierarchy process applied at the level of event groups. This paper investigates further how uncertainty in the model affects ranking results. An analysis was performed on the set of the two databases from the 20 years of nuclear power plants in France and Germany. From all uncertainties the presented analysis selected ranking indexes as the most relevant for consideration. Here the presented analysis of uncertainty clearly shows that considering uncertainty is important for all results, especially for event groups ranked closely and next to the most important one. Together with the previously performed sensitivity analysis, uncertainty assessment provides additional insights and a better judgment of the event groups’ importance in further detailed investigation.

  18. An Oracle-based Event Index for ATLAS

    CERN Document Server

    Gallas, Elizabeth; The ATLAS collaboration; Petrova, Petya Tsvetanova; Baranowski, Zbigniew; Canali, Luca; Formica, Andrea; Dumitru, Andrei

    2016-01-01

    The ATLAS EventIndex System has amassed a set of key quantities for a large number of ATLAS events into a Hadoop based infrastructure for the purpose of providing the experiment with a number of event-wise services. Collecting this data in one place provides the opportunity to investigate various storage formats and technologies and assess which best serve the various use cases as well as consider what other benefits alternative storage systems provide. In this presentation we describe how the data are imported into an Oracle RDBMS, the services we have built based on this architecture, and our experience with it. We've indexed about 15 billion real data events and about 25 billion simulated events thus far and have designed the system to accommodate future data which has expected rates of 5 and 20 billion events per year for real data and simulation, respectively. We have found this system offers outstanding performance for some fundamental use cases. In addition, profiting from the co-location of this data ...

  19. Event-based Implicit Invocation Decentralized in Ada

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Nowadays more and more attraction is drawn by the event-basedimplicit invocation - one of useful architectural patterns, because of its loose couplin g between components in the architecture and reactive integration in software sys tems. Analyzing object-oriented interaction with objects, this paper, based upo n the principle of software architecture, presents an approach on event-based ob j ect model with Ada exception handler. Consequently it is possible for us to impr ove, with adding specific architectural patterns, traditional programming langua ges into architectural description languages.

  20. Event-based prospective memory among veterans: The role of posttraumatic stress disorder symptom severity in executing intentions.

    Science.gov (United States)

    McFarland, Craig P; Clark, Justin B; Lee, Lewina O; Grande, Laura J; Marx, Brian P; Vasterling, Jennifer J

    2016-01-01

    Posttraumatic stress disorder (PTSD) has been linked with neuropsychological deficits in several areas, including attention, learning and memory, and cognitive inhibition. Although memory dysfunction is among the most commonly documented deficits associated with PTSD, our existing knowledge pertains only to retrospective memory. The current study investigated the relationship between PTSD symptom severity and event-based prospective memory (PM). Forty veterans completed a computerized event-based PM task, a self-report measure of PTSD, and measures of retrospective memory. Hierarchical regression analysis results revealed that PTSD symptom severity accounted for 16% of the variance in PM performance, F(3, 36) = 3.47, p memory. Additionally, each of the three PTSD symptom clusters was related, to varying degrees, with PM performance. Results suggest that elevated PTSD symptoms may be associated with more difficulties completing tasks requiring PM. Further examination of PM in PTSD is warranted, especially in regard to its impact on everyday functioning.

  1. Cluster based hierarchical resource searching model in P2P network

    Institute of Scientific and Technical Information of China (English)

    Yang Ruijuan; Liu Jian; Tian Jingwen

    2007-01-01

    For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer (P2P) network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network,auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

  2. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2016-02-01

    Full Text Available The 9th ARRCN Symposium 2015 was held during 21st–25th October 2015 at the Novotel Hotel, Chumphon, Thailand, one of the most favored travel destinations in Asia. The 10th ARRCN Symposium 2017 will be held during October 2017 in the Davao, Philippines. International Symposium on the Montagu's Harrier (Circus pygargus «The Montagu's Harrier in Europe. Status. Threats. Protection», organized by the environmental organization «Landesbund für Vogelschutz in Bayern e.V.» (LBV was held on November 20-22, 2015 in Germany. The location of this event was the city of Wurzburg in Bavaria.

  3. Using the DOE Knowledge Base for Special Event Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, H.M.; Harris, J.M.; Young, C.J.

    1998-10-20

    The DOE Knowledge Base is a library of detailed information whose purpose is to support the United States National Data Center (USNDC) in its mission to monitor compliance with the Comprehensive Test Ban Treaty (CTBT). One of the important tasks which the USNDC must accomplish is to periodically perform detailed analysis of events of high interest, so-called "Special Events", to provide the national authority with information needed to make policy decisions. In this paper we investigate some possible uses of the Knowledge Base for Special Event Analysis (SEA), and make recommendations for improving Knowledge Base support for SEA. To analyze an event in detail, there are two basic types of data which must be used sensor-derived data (wave- forms, arrivals, events, etc.) and regiohalized contextual data (known sources, geological characteristics, etc.). Cur- rently there is no single package which can provide full access to both types of data, so for our study we use a separate package for each MatSeis, the Sandia Labs-developed MATLAB-based seismic analysis package, for wave- form data analysis, and ArcView, an ESRI product, for contextual data analysis. Both packages are well-suited to pro- totyping because they provide a rich set of currently available functionality and yet are also flexible and easily extensible, . Using these tools and Phase I Knowledge Base data sets, we show how the Knowledge Base can improve both the speed and the quality of SEA. Empirically-derived interpolated correction information can be accessed to improve both location estimates and associated error estimates. This information can in turn be used to identi~ any known nearby sources (e.g. mines, volcanos), which may then trigger specialized processing of the sensor data. Based on the location estimate, preferred magnitude formulas and discriminants can be retrieved, and any known blockages can be identified to prevent miscalculations. Relevant historic events can be identilled either by

  4. Elastic properties of chiral, anti-chiral, and hierarchical honeycombs:A simple energy-based approach

    Institute of Scientific and Technical Information of China (English)

    Davood Mousanezhad; Babak Haghpanah; Ranajay Ghosh; Abdel Magid Hamouda; Hamid Nayeb-Hashemi; Ashkan Vaziri

    2016-01-01

    The effects of two geometric refinement strategies widespread in natural structures, chirality and self-similar hierarchy, on the in-plane elastic response of two-dimensional honeycombs were studied systematically. Simple closed-form expressions were derived for the elastic moduli of several chiral, anti-chiral, and hierarchical honeycombs with hexagon and square based networks. Finite element analysis was employed to validate the analytical estimates of the elastic moduli. The results were also compared with the numerical and experimental data available in the literature. We found that introducing a hier-archical refinement increases the Young’s modulus of hexagon based honeycombs while decreases their shear modulus. For square based honeycombs, hierarchy increases the shear modulus while decreasing their Young’s modulus. Introducing chirality was shown to always decrease the Young’s modulus and Poisson’s ratio of the structure. However, chirality remains the only route to auxeticity. In particular, we found that anti-tetra-chiral structures were capable of simultaneously exhibiting anisotropy, auxeticity, and remarkably low shear modulus as the magnitude of the chirality of the unit cell increases.

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

    Science.gov (United States)

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

    2016-08-01

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

  6. An Integrated Metric Based Hierarchical Routing Algorithm in Broadband Communication System

    Institute of Scientific and Technical Information of China (English)

    SHI Chengge; HU Jiajun; Milton Chang

    2001-01-01

    We give an integrated metric basedhierarchical routing algorithm - FMRSF (FunctionFi(.) minimum routing selected first) algorithm inbroadband communication system in this paper. Withthe authors' analysis strategy, this paper gives a rout-ing solution for hierarchical communication system,and the solution is suited to both ATM network andIP network. Due to the highMevel logic network map-ping in a hierarchical communication system, a largecommunication network can be described as a moresimple logic network on a high level. But, it is dif-ficult to evaluate the QoS parameters of the relativefactors of a logic network (For example: the time de-lay and the bandwidth of logic nodes or logic links).We develop our strategy with FMRSF - algorithm fordifferent routing path, and select the reasonable pathfor one communication session. After designing an in-tegrated metric function describing the QoS metrics ofthe relative factors of a logic network on the high lev-els in a broadband communication system, we provethat the new routing algorithm - FMRSF algorithm ismore simple and applicable, compared with the globaloptimum algorithm.

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

    Science.gov (United States)

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

    2017-05-01

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

  8. SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

    Directory of Open Access Journals (Sweden)

    KwangHee Choi

    2014-10-01

    Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.

  9. An Oracle-based Event Index for ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00083337; The ATLAS collaboration; Dimitrov, Gancho

    2017-01-01

    The ATLAS EventIndex System has amassed a set of key quantities for a large number of ATLAS events into a Hadoop based infrastructure for the purpose of providing the experiment with a number of event-wise services. Collecting this data in one place provides the opportunity to investigate various storage formats and technologies and assess which best serve the various use cases as well as consider what other benefits alternative storage systems provide. In this presentation we describe how the data are imported into an Oracle RDBMS, the services we have built based on this architecture, and our experience with it. We've indexed about 26 billion real data events thus far and have designed the system to accommodate future data which has expected rates of 5 and 20 billion events per year. We have found this system offers outstanding performance for some fundamental use cases. In addition, profiting from the co-location of this data with other complementary metadata in ATLAS, the system has been easily extended t...

  10. Simulation of quantum computation : A deterministic event-based approach

    NARCIS (Netherlands)

    Michielsen, K; De Raedt, K; De Raedt, H

    2005-01-01

    We demonstrate that locally connected networks of machines that have primitive learning capabilities can be used to perform a deterministic, event-based simulation of quantum computation. We present simulation results for basic quantum operations such as the Hadamard and the controlled-NOT gate, and

  11. Training Team Problem Solving Skills: An Event-Based Approach.

    Science.gov (United States)

    Oser, R. L.; Gualtieri, J. W.; Cannon-Bowers, J. A.; Salas, E.

    1999-01-01

    Discusses how to train teams in problem-solving skills. Topics include team training, the use of technology, instructional strategies, simulations and training, theoretical framework, and an event-based approach for training teams to perform in naturalistic environments. Contains 68 references. (Author/LRW)

  12. Shadow-Based Hierarchical Matching for the Automatic Registration of Airborne LiDAR Data and Space Imagery

    Directory of Open Access Journals (Sweden)

    Alireza Safdarinezhad

    2016-06-01

    Full Text Available The automatic registration of LiDAR data and optical images, which are heterogeneous data sources, has been a major research challenge in recent years. In this paper, a novel hierarchical method is proposed in which the least amount of interaction of a skilled operator is required. Thereby, two shadow extraction schemes, one from LiDAR and the other from high-resolution satellite images, were used, and the obtained 2D shadow maps were then considered as prospective matching entities. Taken as the base, the reconstructed LiDAR shadows were transformed to image shadows using a four-step hierarchical method starting from a coarse 2D registration model and leading to a fine 3D registration model. In the first step, a general matching was performed in the frequency domain that yielded a rough 2D similarity model that related the LiDAR and image shadow masks. This model was further improved by modeling and compensating for the local geometric distortions that existed between the two heterogeneous data sources. In the third step, shadow masks, which were organized as segmented matched patches, were the subjects of a coinciding procedure that resulted in a coarse 3D registration model. In the last hierarchical step, that model was ultimately reinforced via a precise matching between the LiDAR and image edges. The evaluation results, which were conducted on six datasets and from different relative and absolute aspects, demonstrated the efficiency of the proposed method, which had a very promising accuracy on the order of one pixel.

  13. 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.

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

    Science.gov (United States)

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

    2016-03-28

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

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

    Science.gov (United States)

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

    2017-08-01

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

  16. 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, work leads to an areal capacitance of 62.4 mF·cm(-2) and a volumetric capacitance of 10.4 F·cm(-3), exceeding that of graphene based flexible MSCs by a factor of 26 and 3, respectively. As a noncarbon based flexible MSC, hierarchically nanostructured WO3 in the narrow finger electrode is essential to such enhancement in energy density due to its pseudocapacitive property. The effects of WO3/PVDF/MWCNTs composite composition and the dimensions of interdigital structure on the performance of the flexible MSCs are investigated.

  17. Event Recognition Based on Deep Learning in Chinese Texts

    Science.gov (United States)

    Zhang, Yajun; Liu, Zongtian; Zhou, Wen

    2016-01-01

    Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%. PMID:27501231

  18. Event-based Corpuscular Model for Quantum Optics Experiments

    CERN Document Server

    Michielsen, K; De Raedt, H

    2010-01-01

    A corpuscular simulation model of optical phenomena that does not require the knowledge of the solution of a wave equation of the whole system and reproduces the results of Maxwell's theory by generating detection events one-by-one is presented. The event-based corpuscular model is shown to give a unified description of multiple-beam fringes of a plane parallel plate, single-photon Mach-Zehnder interferometer, Wheeler's delayed choice, photon tunneling, quantum erasers, two-beam interference, double-slit, and Einstein-Podolsky-Rosen-Bohm and Hanbury Brown-Twiss experiments.

  19. Topic Modeling Based Image Clustering by Events in Social Media

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2016-01-01

    Full Text Available Social event detection in large photo collections is very challenging and multimodal clustering is an effective methodology to deal with the problem. Geographic information is important in event detection. This paper proposed a topic model based approach to estimate the missing geographic information for photos. The approach utilizes a supervised multimodal topic model to estimate the joint distribution of time, geographic, content, and attached textual information. Then we annotate the missing geographic photos with a predicted geographic coordinate. Experimental results indicate that the clustering performance improved by annotated geographic information.

  20. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  1. Development of a GCR Event-based Risk Model

    Science.gov (United States)

    Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

    2009-01-01

    A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how

  2. Event-Based control of depth of hypnosis in anesthesia.

    Science.gov (United States)

    Merigo, Luca; Beschi, Manuel; Padula, Fabrizio; Latronico, Nicola; Paltenghi, Massimiliano; Visioli, Antonio

    2017-08-01

    In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients. The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase. The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Event- and interval-based measurement of stuttering: a review.

    Science.gov (United States)

    Valente, Ana Rita S; Jesus, Luis M T; Hall, Andreia; Leahy, Margaret

    2015-01-01

    Event- and interval-based measurements are two different ways of computing frequency of stuttering. Interval-based methodology emerged as an alternative measure to overcome problems associated with reproducibility in the event-based methodology. No review has been made to study the effect of methodological factors in interval-based absolute reliability data or to compute the agreement between the two methodologies in terms of inter-judge, intra-judge and accuracy (i.e., correspondence between raters' scores and an established criterion). To provide a review related to reproducibility of event-based and time-interval measurement, and to verify the effect of methodological factors (training, experience, interval duration, sample presentation order and judgment conditions) on agreement of time-interval measurement; in addition, to determine if it is possible to quantify the agreement between the two methodologies The first two authors searched for articles on ERIC, MEDLINE, PubMed, B-on, CENTRAL and Dissertation Abstracts during January-February 2013 and retrieved 495 articles. Forty-eight articles were selected for review. Content tables were constructed with the main findings. Articles related to event-based measurements revealed values of inter- and intra-judge greater than 0.70 and agreement percentages beyond 80%. The articles related to time-interval measures revealed that, in general, judges with more experience with stuttering presented significantly higher levels of intra- and inter-judge agreement. Inter- and intra-judge values were beyond the references for high reproducibility values for both methodologies. Accuracy (regarding the closeness of raters' judgements with an established criterion), intra- and inter-judge agreement were higher for trained groups when compared with non-trained groups. Sample presentation order and audio/video conditions did not result in differences in inter- or intra-judge results. A duration of 5 s for an interval appears to be

  4. Event-based state estimation a stochastic perspective

    CERN Document Server

    Shi, Dawei; Chen, Tongwen

    2016-01-01

    This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs ...

  5. Saliency-based abnormal event detection in crowded scenes

    Science.gov (United States)

    Shi, Yanjiao; Liu, Yunxiang; Zhang, Qing; Yi, Yugen; Li, Wenju

    2016-11-01

    Abnormal event detection plays a critical role for intelligent video surveillance, and detection in crowded scenes is a challenging but more practical task. We present an abnormal event detection method for crowded video. Region-wise modeling is proposed to address the inconsistent detected motion of the same object due to different depths of field. Comparing to traditional block-wise modeling, the region-wise method not only can reduce heavily the number of models to be built but also can enrich the samples for training the normal events model. In order to reduce the computational burden and make the region-based anomaly detection feasible, a saliency detection technique is adopted in this paper. By identifying the salient parts of the image sequences, the irrelevant blocks are ignored, which removes the disturbance and improves the detection performance further. Experiments on the benchmark dataset and comparisons with the state-of-the-art algorithms validate the advantages of the proposed method.

  6. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  7. Knowledge Discovery for Event Series Decision Based on Rough Set

    Institute of Scientific and Technical Information of China (English)

    ZENG Chuan-hua; PEI Zheng; XU Yang

    2006-01-01

    To make decisions about event series is part of our life, and to discover knowledge from these decisions is of great significance in the field of controlling and decision-making.The paper takes event series as the exterior form of movements with the dynamic attributes, and gets the Markov transition probabilities matrix to express those attributes with statistics. First, according to the matrix,the decision table is constructed. Then, by reducing attributes based on rough set theory, the decision table is reduced, and the decision rules are acquired as well. Finally we make the decision through defining rule distance and taking the minimum rule distance as decision principle.Followed is an example, which proves that the algorithm is feasible and effective to the event series decision.

  8. Decentralized Event-Based Communication Strategy on Leader-Follower Consensus Control

    OpenAIRE

    Duosi Xie; Xiaochun Yin; Jianquan Xie

    2016-01-01

    This paper addresses the leader-follower consensus problem of networked systems by using a decentralized event-based control strategy. The event-based control strategy makes the controllers of agents update at aperiodic event instants. Two decentralized event functions are designed to generate these event instants. In particular, the second event function only uses its own information and the neighbors’ states at their latest event instants. By using this event function, no continuous communi...

  9. Climate information based streamflow and rainfall forecasts for Huai River Basin using Hierarchical Bayesian Modeling

    Directory of Open Access Journals (Sweden)

    X. Chen

    2013-09-01

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

  10. 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.

  11. A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

    Directory of Open Access Journals (Sweden)

    Farshad Faezy Razi

    2014-06-01

    Full Text Available Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers.

  12. 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

  13. Time Synchronization in Hierarchical TESLA Wireless Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Jason L. Wright; Milos Manic

    2009-08-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

  15. Event Driven Messaging with Role-Based Subscriptions

    Science.gov (United States)

    Bui, Tung; Bui, Bach; Malhotra, Shantanu; Chen, Fannie; Kim, rachel; Allen, Christopher; Luong, Ivy; Chang, George; Zendejas, Silvino; Sadaqathulla, Syed

    2009-01-01

    Event Driven Messaging with Role-Based Subscriptions (EDM-RBS) is a framework integrated into the Service Management Database (SMDB) to allow for role-based and subscription-based delivery of synchronous and asynchronous messages over JMS (Java Messaging Service), SMTP (Simple Mail Transfer Protocol), or SMS (Short Messaging Service). This allows for 24/7 operation with users in all parts of the world. The software classifies messages by triggering data type, application source, owner of data triggering event (mission), classification, sub-classification and various other secondary classifying tags. Messages are routed to applications or users based on subscription rules using a combination of the above message attributes. This program provides a framework for identifying connected users and their applications for targeted delivery of messages over JMS to the client applications the user is logged into. EDMRBS provides the ability to send notifications over e-mail or pager rather than having to rely on a live human to do it. It is implemented as an Oracle application that uses Oracle relational database management system intrinsic functions. It is configurable to use Oracle AQ JMS API or an external JMS provider for messaging. It fully integrates into the event-logging framework of SMDB (Subnet Management Database).

  16. 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 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...... control loop consists of voltage and current inner loops, conventional droop control and virtual impedance loop while the secondary control loop is based on positive/negative sequence droop control which can achieve power injection under voltage sags. Experimental results with asymmetrical voltage sags...

  17. Hierarchical Fault Diagnosis for a Hybrid System Based on a Multidomain Model

    Directory of Open Access Journals (Sweden)

    Jiming Ma

    2015-01-01

    Full Text Available The diagnosis procedure is performed by integrating three steps: multidomain modeling, event identification, and failure event classification. Multidomain model can describe the normal and fault behaviors of hybrid systems efficiently and can meet the diagnosis requirements of hybrid systems. Then the multidomain model is used to simulate and obtain responses under different failure events; the responses are further utilized as a priori information when training the event identification library. Finally, a brushless DC motor is selected as the study case. The experimental result indicates that the proposed method could identify the known and unknown failure events of the studied system. In particular, for a system with less response information under a failure event, the accuracy of diagnosis seems to be higher. The presented method integrates the advantages of current quantitative and qualitative diagnostic procedures and can distinguish between failures caused by parametric and abrupt structure faults. Another advantage of our method is that it can remember unknown failure types and automatically extend the adaptive resonance theory neural network library, which is extremely useful for complex hybrid systems.

  18. Mars Science Laboratory; A Model for Event-Based EPO

    Science.gov (United States)

    Mayo, Louis; Lewis, E.; Cline, T.; Stephenson, B.; Erickson, K.; Ng, C.

    2012-10-01

    The NASA Mars Science Laboratory (MSL) and its Curiosity Rover, a part of NASA's Mars Exploration Program, represent the most ambitious undertaking to date to explore the red planet. MSL/Curiosity was designed primarily to determine whether Mars ever had an environment capable of supporting microbial life. NASA's MSL education program was designed to take advantage of existing, highly successful event based education programs to communicate Mars science and education themes to worldwide audiences through live webcasts, video interviews with scientists, TV broadcasts, professional development for teachers, and the latest social media frameworks. We report here on the success of the MSL education program and discuss how this methodological framework can be used to enhance other event based education programs.

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

    Science.gov (United States)

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

    2016-05-31

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

  20. Track-based event recognition in a realistic crowded environment

    Science.gov (United States)

    van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

    2014-10-01

    Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

  1. 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.

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

    Science.gov (United States)

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

    2012-08-30

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

  3. AN OPTIMUM VEHICULAR PATH ALGORITHM FOR TRAFFIC NETWORK BASED ON HIERARCHICAL SPATIAL REASONING

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.

  4. 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.

  5. 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.

  6. Multiple Computing Task Scheduling Method Based on Dynamic Data Replication and Hierarchical Strategy

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    2014-02-01

    Full Text Available As for the problem of how to carry out task scheduling and data replication effectively in the grid and to reduce task’s execution time, this thesis proposes the task scheduling algorithm and the optimum dynamic data replication algorithm and builds a scheme to effectively combine these two algorithms. First of all, the scheme adopts the ISS algorithm considering the number of tasks waiting queue, the location of task demand data and calculation capacity of site by adopting the method of network structure’s hierarchical scheduling to calculate the cost of comprehensive task with the proper weight efficiency and search out the best compute node area. And then the algorithm of ODHRA is adopted to analyze the data transmission time, memory access latency, waiting copy requests in the queue and the distance between nodes, choose out the best replications location in many copies combined with copy placement and copy management to reduce the file access time. The simulation results show that the proposed scheme compared with other algorithm has better performance in terms of average task execution time. 

  7. Structural system identification using degree of freedom-based reduction and hierarchical clustering algorithm

    Science.gov (United States)

    Chang, Seongmin; Baek, Sungmin; Kim, Ki-Ook; Cho, Maenghyo

    2015-06-01

    A system identification method has been proposed to validate finite element models of complex structures using measured modal data. Finite element method is used for the system identification as well as the structural analysis. In perturbation methods, the perturbed system is expressed as a combination of the baseline structure and the related perturbations. The changes in dynamic responses are applied to determine the structural modifications so that the equilibrium may be satisfied in the perturbed system. In practical applications, the dynamic measurements are carried out on a limited number of accessible nodes and associated degrees of freedom. The equilibrium equation is, in principle, expressed in terms of the measured (master, primary) and unmeasured (slave, secondary) degrees of freedom. Only the specified degrees of freedom are included in the equation formulation for identification and the unspecified degrees of freedom are eliminated through the iterative improved reduction scheme. A large number of system parameters are included as the unknown variables in the system identification of large-scaled structures. The identification problem with large number of system parameters requires a large amount of computation time and resources. In the present study, a hierarchical clustering algorithm is applied to reduce the number of system parameters effectively. Numerical examples demonstrate that the proposed method greatly improves the accuracy and efficiency in the inverse problem of identification.

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

    Science.gov (United States)

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

    2014-02-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Burghardt, Irene [Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt (Germany); Martinazzo, Rocco [Dipartimento di Chimica, Universita degli Studi di Milano, v. Golgi 19, 20133 Milano (Italy); Hughes, Keith H. [School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2UW (United Kingdom)

    2012-10-14

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

  10. 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.

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

    Science.gov (United States)

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

    2015-07-01

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

  12. Transfer of Trust in Event-based Reputation Systems

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Krukow, Karl

    2012-01-01

    choice of model from concurrency theory. In this paper, we continue this line of research, addressing the problem on how to transfer trust from one behavioural context to another. Our proposed frameworks build on morphisms between event structures, and we prove some generic results guaranteeing formal......In the Global Computing scenario, trust-based systems have been proposed and studied as an alternative to traditional security mechanisms. A promising line of research concerns the so-called reputation-based computational trust. The approach here is that trust in a computing agent is defined...... properties of transfers in the frameworks....

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

    Science.gov (United States)

    Ohlberger, Mario; Smetana, Kathrin

    2016-09-01

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

  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.

  15. 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.

  16. 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.

  17. A novel 300 kW arc plasma inverter system based on hierarchical controlled building block structure

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    To date, the high power arc plasma technology is widely used. A next generation high power arc plasma system based on building block structure is presented. The whole arc plasma inverter system is composed of 12 paralleled units to increase the system output capability. The hierarchical control system is adopted to improve the reliability and flexibility of the high power arc plasma inverter. To ensure the reliable turn on and off of the IGBT module in each building block unit, a special pulse drive circuit is designed by using pulse transformer. The experimental result indicates that the high power arc plasma inverter system can transfer 300 kW arc plasma energy reliably with high efficiency.

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

    Science.gov (United States)

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

    2016-03-01

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

  19. Hierarchical hybrid control network design based on LON and master-slave RS-422/485 protocol

    Institute of Scientific and Technical Information of China (English)

    彭可; 陈际达; 陈岚

    2002-01-01

    Aiming at the weaknesses of LON bus, combining the coexistence of fieldbus and DCS (Distribu-ted Control Systems) in control networks, the authors introduce a hierarchical hybrid control network design based on LON and master-slave RS-422/485 protocol. This design adopts LON as the trunk, master-slave RS-422/485 control networks are connected to LON as special subnets by dedicated gateways. It is an implementation method for isomerous control network integration. Data management is ranked according to real-time requirements for different network data. The core components, such as control network nodes, router and gateway, are detailed in the paper. The design utilizes both communication advantage of LonWorks technology and the more powerful control ability of universal MCUs or PLCs, thus it greatly increases system response speed and performance-cost ratio.

  20. Rainfall events prediction using rule-based fuzzy inference system

    Science.gov (United States)

    Asklany, Somia A.; Elhelow, Khaled; Youssef, I. K.; Abd El-wahab, M.

    2011-07-01

    We are interested in rainfall events prediction by applying rule-based reasoning and fuzzy logic. Five parameters: relative humidity, total cloud cover, wind direction, temperature and surface pressure are the input variables for our model, each has three membership functions. The data used is twenty years METAR data for Cairo airport station (HECA) [1972-1992] 30° 3' 29″ N, 31° 13' 44″ E. and five years METAR data for Mersa Matruh station (HEMM) 31° 20' 0″ N, 27° 13' 0″ E. Different models for each station were constructed depending on the available data sets. Among the overall 243 possibilities we have based our models on one hundred eighteen fuzzy IF-THEN rules and fuzzy reasoning. The output variable which has four membership functions, takes values from zero to one hundred corresponding to the percentage for rainfall events given for every hourly data. We used two skill scores to verify our results, the Brier score and the Friction score. The results are in high agreements with the recorded data for the stations with increasing in output values towards the real time rain events. All implementation are done with MATLAB 7.9.

  1. Human visual system-based smoking event detection

    Science.gov (United States)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  2. Multi Agent System Based Wide Area Protection against Cascading Events

    DEFF Research Database (Denmark)

    Liu, Zhou; Chen, Zhe; Liu, Leo;

    2012-01-01

    In this paper, a multi-agent system based wide area protection scheme is proposed in order to prevent long term voltage instability induced cascading events. The distributed relays and controllers work as a device agent which not only executes the normal function automatically but also can...... the effectiveness of proposed protection strategy. The simulation results indicate that the proposed multi agent control system can effectively coordinate the distributed relays and controllers to prevent the long term voltage instability induced cascading events....... be modified to fulfill the extra function according to external requirements. The control center is designed as a highest level agent in MAS to coordinate all the lower agents to prevent the system wide voltage disturbance. A hybrid simulation platform with MATLAB and RTDS is set up to demonstrate...

  3. Temporal and Location Based RFID Event Data Management and Processing

    Science.gov (United States)

    Wang, Fusheng; Liu, Peiya

    Advance of sensor and RFID technology provides significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management. RFID data are temporal and history oriented, multi-dimensional, and carrying implicit semantics. Moreover, RFID applications are heterogeneous. RFID data management or data warehouse systems need to support generic and expressive data modeling for tracking and monitoring physical objects, and provide automated data interpretation and processing. We develop a powerful temporal and location oriented data model for modeling and queryingRFID data, and a declarative event and rule based framework for automated complex RFID event processing. The approach is general and can be easily adapted for different RFID-enabled applications, thus significantly reduces the cost of RFID data integration.

  4. Spatio-temporal GIS Data Model Based on Event Semantics

    Institute of Scientific and Technical Information of China (English)

    XU Zhihong; BIAN Fuling

    2003-01-01

    There are mainly four kinds of models to record and deal with historical information. By taking them as reference, the spatio-temporal model based on event semantics is proposed. In this model, according to the way for describing an event, all the information are divided into five domains. This paper describes the model by using the land parcel change in the cadastral information system, and expounds the model by using five tables corresponding to the five domains.With the aid of this model, seven examples are given on historical query,trace back and recurrence. This model can be implemented either in the extended relational database or in the object-oriented database.

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

  6. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  7. Hierarchical construction of PbS architectures based on the adsorption and sustained release of H{sub 2}S by TBAB

    Energy Technology Data Exchange (ETDEWEB)

    Li Guowei [College of Material Science and Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013 (China); Li Changsheng, E-mail: changshengli@ujs.edu.cn [College of Material Science and Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013 (China); Yang Xiaofei [College of Material Science and Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013 (China); Ng Dikon, H.L. [Department of Physics, Chinese University of Hong Kong, Shatin (Hong Kong); Tang Hua [College of Material Science and Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013 (China)

    2011-10-03

    Graphical abstract: PbS uniform hierarchical microstars were grown on a large scale by a simple hydrothermal method with the help of a new surfactant: tetrabutyl ammonium bromide (C{sub 16}H{sub 36}BrN). A possible new formation mechanism of hierarchical hollow PbS structures based on the adsorption and sustained release of S{sup 2+} by TBAB is presented. Highlights: {yields} Multi-arm PbS hierarchical structures were successfully synthesized by a simple hydrothermal method at low temperature: 90 deg. C. {yields} A new surfactant: tetrabutyl ammonium bromide (TBAB) was used in the process, a possible new formation mechanism of hierarchical hollow PbS structures based on the adsorption and sustained release of S{sup 2+} by TBAB is presented. - Abstract: Multi-arm PbS architectures were successfully synthesized in high yield by a facile hydrothermal process at 90 deg. C for 48 h, employing lead nitrate (Pb(NO{sub 3}){sub 2}) and thioacetamide (TAA) as precursors. A new surfactant: tetrabutyl ammonium bromide (TBAB), was used in this process. The as-prepared PbS products are characterized by X-ray powder diffraction (XRD), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), and Fourier transform infrared (FT-IR) spectroscopy. The results showed that the concentration of TBAB, as well as the molar ratio of Pb(NO{sub 3}){sub 2} to TAA are crucial factors on the morphologies and sizes of the hierarchical PbS microcrystals. A reasonable possible new formation mechanism of hierarchical PbS structures based on the adsorption and sustained release of H{sub 2}S by TBAB has been presented.

  8. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

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

    Science.gov (United States)

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

    2016-04-28

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-12-28

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

  11. Event-based internet biosurveillance: relation to epidemiological observation

    Directory of Open Access Journals (Sweden)

    Nelson Noele P

    2012-06-01

    Full Text Available Abstract Background The World Health Organization (WHO collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data. Methods We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1 2009 (April 2009 – January 2010 from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information. Results Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p  Conclusion Confirmed pandemic (H1N1 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events.

  12. Supervisory Control of Fuzzy Discrete Event Systems Based on Agent

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    FDES (fuzzy discrete event systems) can effectively represent a kind of complicated systems involving deterministic uncertainties and vagueness as well as human subjective observation and judgement from the view of discrete events, here the information system is divided into some independent intelligent entitative Agents. The concept of information processing state based on Agents was proposed. The processing state of Agent can be judged by some assistant observation parameters about the Agent and its environment around, and the transition among these states can be represented by FDES based on rules. In order to ensure the harmony of the Agents for information processing, its upstream and downstream buffers are considered in the modeling of the Agent system,and the supervisory controller based on FDES is constructed. The processing state of Agent can be adjusted by the supervisory controller to improve the stability of the system and the efficiency of resource utilization during the process according to the control policies. The result of its application was provided to illustrate the validity of the supervisory adjustment.

  13. Intelligent Transportation Control based on Proactive Complex Event Processing

    Directory of Open Access Journals (Sweden)

    Wang Yongheng

    2016-01-01

    Full Text Available Complex Event Processing (CEP has become the key part of Internet of Things (IoT. Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.

  14. Event-based image recognition applied in tennis training assistance

    Science.gov (United States)

    Wawrzyniak, Zbigniew M.; Kowalski, Adam

    2016-09-01

    This paper presents a concept of a real-time system for individual tennis training assistance. The system is supposed to provide user (player) with information on his strokes accuracy as well as other training quality parameters such as velocity and rotation of the ball during its flight. The method is based on image processing methods equipped with developed explorative analysis of the events and their description by parameters of the movement. There has been presented the concept for further deployment to create a complete system that could assist tennis player during individual training.

  15. 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.

  16. Analysis of manufacturing based on object oriented discrete event simulation

    Directory of Open Access Journals (Sweden)

    Eirik Borgen

    1990-01-01

    Full Text Available This paper describes SIMMEK, a computer-based tool for performing analysis of manufacturing systems, developed at the Production Engineering Laboratory, NTH-SINTEF. Its main use will be in analysis of job shop type of manufacturing. But certain facilities make it suitable for FMS as well as a production line manufacturing. This type of simulation is very useful in analysis of any types of changes that occur in a manufacturing system. These changes may be investments in new machines or equipment, a change in layout, a change in product mix, use of late shifts, etc. The effects these changes have on for instance the throughput, the amount of VIP, the costs or the net profit, can be analysed. And this can be done before the changes are made, and without disturbing the real system. Simulation takes into consideration, unlike other tools for analysis of manufacturing systems, uncertainty in arrival rates, process and operation times, and machine availability. It also shows the interaction effects a job which is late in one machine, has on the remaining machines in its route through the layout. It is these effects that cause every production plan not to be fulfilled completely. SIMMEK is based on discrete event simulation, and the modeling environment is object oriented. The object oriented models are transformed by an object linker into data structures executable by the simulation kernel. The processes of the entity objects, i.e. the products, are broken down to events and put into an event list. The user friendly graphical modeling environment makes it possible for end users to build models in a quick and reliable way, using terms from manufacturing. Various tests and a check of model logic are helpful functions when testing validity of the models. Integration with software packages, with business graphics and statistical functions, is convenient in the result presentation phase.

  17. 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

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

    Science.gov (United States)

    2010-01-01

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

  19. Hydrocarbon Seepage during the Boreal Base Cretaceous Hot Shale Event

    Science.gov (United States)

    Hammer, Ø.; Hryniewicz, K.; Nakrem, H. A.; Little, C.

    2014-12-01

    We have identified a number of carbonate bodies interpreted as seep-related from near the Jurassic-Cretaceous boundary in Svalbard, arctic Norway. The paleoseeps discovered so far occur over 50 km along strike, representing a seepage field of considerable extent. Ammonites indicate a base Cretaceous (Late Volgian to Late Ryazanian) age. The carbonate bodies are highly fossiliferous, with a very diverse fauna consisting mainly of normal-marine species but also seep-restricted taxa. Carbonate d13C isotopes reach -46‰, which, considering mixture with seawater-derived carbon, is interpreted as indicating a biogenic methane source. It is of interest to note the correlation of this paleoseepage with an episode of extremely high burial of organic matter near the Jurassic-Cretaceous boundary, noted both in Svalbard (top Slottsmøya Member of the Agardhfjellet Formation), in the Barents Sea (Hekkingen Formation) and in the North Sea (Mandal Formation), possibly providing a shallow source for biogenic gas. Together with near contemporaneous events in the Boreal Realm such as ongoing rifting, the base Cretaceous unconformity, the Mjølnir meteorite impact and a possible minor extinction event, these finds contribute to the impression of the Jurassic-Cretaceous boundary as a highly dynamic and interesting time in the North Atlantic area.

  20. Event-triggered hybrid control based on multi-Agent systems for Microgrids

    DEFF Research Database (Denmark)

    Dou, Chun-xia; Liu, Bin; Guerrero, Josep M.

    2014-01-01

    of distributed energy resources, thus it is typical hybrid dynamic network. Considering the complex hybrid behaviors, a hierarchical decentralized coordinated control scheme is firstly constructed based on multi-agent sys-tem, then, the hybrid model of the microgrid is built by using differential hybrid Petri...

  1. 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.

  2. Hierarchical Group Based Mutual Authentication and Key Agreement for Machine Type Communication in LTE and Future 5G Networks

    Directory of Open Access Journals (Sweden)

    Probidita Roychoudhury

    2017-01-01

    Full Text Available In view of the exponential growth in the volume of wireless data communication among heterogeneous devices ranging from smart phones to tiny sensors across a wide range of applications, 3GPP LTE-A has standardized Machine Type Communication (MTC which allows communication between entities without any human intervention. The future 5G cellular networks also envisage massive deployment of MTC Devices (MTCDs which will increase the total number of connected devices hundredfold. This poses a huge challenge to the traditional cellular system processes, especially the traditional Mutual Authentication and Key Agreement (AKA mechanism currently used in LTE systems, as the signaling load caused by the increasingly large number of devices may have an adverse effect on the regular Human to Human (H2H traffic. A solution in the literature has been the use of group based architecture which, while addressing the authentication traffic, has their share of issues. This paper introduces Hierarchical Group based Mutual Authentication and Key Agreement (HGMAKA protocol to address those issues and also enables the small cell heterogeneous architecture in line with 5G networks to support MTC services. The aggregate Message Authentication Code based approach has been shown to be lightweight and significantly efficient in terms of resource usage compared to the existing protocols, while being robust to authentication message failures, and scalable to heterogeneous network architectures.

  3. A Bayesian Model for Event-based Trust

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Krukow, Karl; Sassone, Vladimiro

    2007-01-01

    relationships, i.e., via systems for computational trust. We focus here on systems where trust in a computational entity is interpreted as the expectation of certain future behaviour based on behavioural patterns of the past, and concern ourselves with the foundations of such probabilistic systems....... In particular, we aim at establishing formal probabilistic models for computational trust and their fundamental properties. In the paper we define a mathematical measure for quantitatively comparing the effectiveness of probabilistic computational trust systems in various environments. Using it, we compare some...... of the systems from the computational trust literature; the comparison is derived formally, rather than obtained via experimental simulation as traditionally done. With this foundation in place, we formalise a general notion of information about past behaviour, based on event structures. This yields a flexible...

  4. Metacognitive awareness of event-based prospective memory.

    Science.gov (United States)

    Thadeus Meeks, J; Hicks, Jason L; Marsh, Richard L

    2007-12-01

    This study examined people's ability to predict and postdict their performance on an event-based prospective memory task. Using nonfocal cues, one group of participants predicted their success at finding animal words and a different group predicted their ability to find words with a particular syllable in it. The authors also administered a self-report questionnaire on everyday prospective and retrospective memory failures. Based on the different strategies adopted by the two groups and correlations among the dependent variables, the authors concluded that people do have a basic awareness of their prospective memory abilities, but that this awareness is far from accurate. The importance of metamemory concerning one's prospective memory is discussed in terms of how it influences the strategies that people might choose for actually completing their various everyday intentions.

  5. Hierarchical Model-Based Activity Recognition With Automatic Low-Level State Discovery

    Directory of Open Access Journals (Sweden)

    Justin Muncaster

    2007-09-01

    Full Text Available Activity recognition in video streams is increasingly important for both the computer vision and artificial intelligence communities. Activity recognition has many applications in security and video surveillance. Ultimately in such applications one wishes to recognize complex activities, which can be viewed as combination of simple activities. In this paper, we present a general framework of a Dlevel dynamic Bayesian network to perform complex activity recognition. The levels of the network are constrained to enforce state hierarchy while the Dth level models the duration of simplest event. Moreover, in this paper we propose to use the deterministic annealing clustering method to automatically define the simple activities, which corresponds to the low level states of observable levels in a Dynamic Bayesian Networks. We used real data sets for experiments. The experimental results show the effectiveness of our proposed method.

  6. Multi-Agent System based Event-Triggered Hybrid Controls for High-Security Hybrid Energy Generation Systems

    DEFF Research Database (Denmark)

    Dou, Chun-Xia; Yue, Dong; Guerrero, Josep M.

    2017-01-01

    This paper proposes multi-agent system based event- triggered hybrid controls for guaranteeing energy supply of a hybrid energy generation system with high security. First, a mul-ti-agent system is constituted by an upper-level central coordi-nated control agent combined with several lower...... switching control, distributed dynamic regulation and coordinated switching con-trol are designed fully dependent on the hybrid behaviors of all distributed energy resources and the logical relationships be-tween them, and interact with each other by means of the mul-ti-agent system to form hierarchical......-level unit agents. Each lower-level unit agent is responsible for dealing with internal switching control and distributed dynamic regula-tion for its unit system. The upper-level agent implements coor-dinated switching control to guarantee the power supply of over-all system with high security. The internal...

  7. Hierarchical Self-Assembly of a Biomimetic Light-Harvesting Antenna Based on DNA G-Quadruplexes

    NARCIS (Netherlands)

    Oltra, Nuria Sancho; Browne, Wesley R.; Roelfes, Gerard

    2013-01-01

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

  8. Segmentation of Sloped Roofs from Airborne LiDAR Point Clouds Using Ridge-Based Hierarchical Decomposition

    Directory of Open Access Journals (Sweden)

    Hongchao Fan

    2014-04-01

    Full Text Available This paper presents a new approach for roof facet segmentation based on ridge detection and hierarchical decomposition along ridges. The proposed approach exploits the fact that every roof can be composed of a set of gabled roofs and single facets which are separated by the gabled roofs. In this work, firstly, building footprints stored in OpenStreetMap are used to extract 3D points on roofs. Then, roofs are segmented into roof facets. The algorithm starts with detecting roof ridges using RANSAC since they are parallel to the horizon and situated on the top of the roof. The roof ridges are utilized to indicate the location and direction of the gabled roof. Thus, points on the two roof facets along a roof ridge can be identified based on their connectivity and coplanarity. The results of the segmentation benefit the further process of roof reconstruction because many parameters, including the position, angle and size of the gabled roof can be calculated and used as priori knowledge for the model-driven approach, and topologies among the point segments are made known for the data-driven approach. The algorithm has been validated in the test sites of two towns next to Bavaria Forest national park. The experimental results show that building roofs can be segmented with both high correctness and completeness simultaneously.

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

    Science.gov (United States)

    Kim, J.; Kwon, H. H.

    2014-12-01

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

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

    Science.gov (United States)

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

    1994-01-01

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

  11. Electrophysiological correlates of strategic monitoring in event-based and time-based prospective memory.

    Directory of Open Access Journals (Sweden)

    Giorgia Cona

    Full Text Available Prospective memory (PM is the ability to remember to accomplish an action when a particular event occurs (i.e., event-based PM, or at a specific time (i.e., time-based PM while performing an ongoing activity. Strategic Monitoring is one of the basic cognitive functions supporting PM tasks, and involves two mechanisms: a retrieval mode, which consists of maintaining active the intention in memory; and target checking, engaged for verifying the presence of the PM cue in the environment. The present study is aimed at providing the first evidence of event-related potentials (ERPs associated with time-based PM, and at examining differences and commonalities in the ERPs related to Strategic Monitoring mechanisms between event- and time-based PM tasks.The addition of an event-based or a time-based PM task to an ongoing activity led to a similar sustained positive modulation of the ERPs in the ongoing trials, mainly expressed over prefrontal and frontal regions. This modulation might index the retrieval mode mechanism, similarly engaged in the two PM tasks. On the other hand, two further ERP modulations were shown specifically in an event-based PM task. An increased positivity was shown at 400-600 ms post-stimulus over occipital and parietal regions, and might be related to target checking. Moreover, an early modulation at 130-180 ms post-stimulus seems to reflect the recruitment of attentional resources for being ready to respond to the event-based PM cue. This latter modulation suggests the existence of a third mechanism specific for the event-based PM; that is, the "readiness mode".

  12. An event-based hydrologic simulation model for bioretention systems.

    Science.gov (United States)

    Roy-Poirier, A; Filion, Y; Champagne, P

    2015-01-01

    Bioretention systems are designed to treat stormwater and provide attenuated drainage between storms. Bioretention has shown great potential at reducing the volume and improving the quality of stormwater. This study introduces the bioretention hydrologic model (BHM), a one-dimensional model that simulates the hydrologic response of a bioretention system over the duration of a storm event. BHM is based on the RECARGA model, but has been adapted for improved accuracy and integration of pollutant transport models. BHM contains four completely-mixed layers and accounts for evapotranspiration, overflow, exfiltration to native soils and underdrain discharge. Model results were evaluated against field data collected over 10 storm events. Simulated flows were particularly sensitive to antecedent water content and drainage parameters of bioretention soils, which were calibrated through an optimisation algorithm. Temporal disparity was observed between simulated and measured flows, which was attributed to preferential flow paths formed within the soil matrix of the field system. Modelling results suggest that soil water storage is the most important short-term hydrologic process in bioretention, with exfiltration having the potential to be significant in native soils with sufficient permeability.

  13. VLSI-based Video Event Triggering for Image Data Compression

    Science.gov (United States)

    Williams, Glenn L.

    1994-01-01

    Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

  14. SEQUENTIAL CLUSTERING-BASED EVENT DETECTION FOR NONINTRUSIVE LOAD MONITORING

    Directory of Open Access Journals (Sweden)

    Karim Said Barsim

    2016-01-01

    Full Text Available The problem of change-point detection has been well studied and adopted in many signal processing applications. In such applications, the informative segments of the signal are the stationary ones before and after the change-point. However, for some novel signal processing and machine learning applications such as Non-Intrusive Load Monitoring (NILM, the information contained in the non-stationary transient intervals is of equal or even more importance to the recognition process. In this paper, we introduce a novel clustering-based sequential detection of abrupt changes in an aggregate electricity consumption profile with accurate decomposition of the input signal into stationary and non-stationary segments. We also introduce various event models in the context of clustering analysis. The proposed algorithm is applied to building-level energy profiles with promising results for the residential BLUED power dataset.

  15. Content-Based Hierarchical Analysis of News Video Using Audio and Visual Information

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A schema for content-based analysis of broadcast news video is presented. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at various levels of abstraction via effective integration of video, audio, and text data available from the news programs. Based on these news video structure and content analysis technologies, a TV news video Library is generated, from which users can retrieve definite news story according to their demands.

  16. Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

    Science.gov (United States)

    2016-06-07

    year. Our goal is to develop an ensemble ocean forecast methodology, using Bayesian Hierarchical Modelling (BHM) tools . The ocean ensemble forecast...from above); i.e. we assume Ut ~ Z Λt1/2. WORK COMPLETED The prototype MFS-Wind-BHM was designed and implemented based on stochastic...coding refinements we implemented on the prototype surface wind BHM. A DWF event in February 2005, in the Gulf of Lions, was identified for reforecast

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. An Improved Particle Swarm Optimization Based on Deluge Approach for Enhanced Hierarchical Cache Optimization in IPTV Networks

    Directory of Open Access Journals (Sweden)

    M. Somu

    2014-05-01

    Full Text Available In recent years, IP network has been considered as a new delivery network for TV services. A majority of the telecommunication industries have used IP network to offer on-demand services and linear TV services as it can offer a two-way and high-speed communication. In order to effectively and economically utilize the IP network, caching is the technique which is usually preferred. In IPTV system, a managed network is utilized to bring out TV services, the requests of Video on Demand (VOD objects are usually combined in a limited period intensively and user preferences are fluctuated dynamically. Furthermore, the VOD content updates often under the control of IPTV providers. In order to minimize this traffic and overall network cost, a segment of the video content is stored in caches closer to subscribers, for example, Digital Subscriber Line Access Multiplexer (DSLAM, a Central Office (CO and Intermediate Office (IO. The major problem focused in this approach is to determine the optimal cache memory that should be assigned in order to attain maximum cost effectiveness. This approach uses an effective Grate Deluge algorithm based Particle Swarm Optimization (GDPSO approach for attaining the optimal cache memory size which in turn minimizes the overall network cost. The analysis shows that hierarchical distributed caching can save significant network cost through the utilization of the GDPSO algorithm.

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

    Science.gov (United States)

    Lee, HyeongJin; Kim, GeunHyung

    2014-09-15

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

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

    Directory of Open Access Journals (Sweden)

    Xin Gao

    2016-01-01

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

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

    Science.gov (United States)

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

    2002-01-01

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

  5. Lateral suppressor and Goblet act in hierarchical order to regulate ectopic meristem formation at the base of tomato leaflets.

    Science.gov (United States)

    Rossmann, Susanne; Kohlen, Wouter; Hasson, Alice; Theres, Klaus

    2015-03-01

    In seed plants, new axes of growth are established by the formation of meristems, groups of pluripotent cells that maintain themselves and initiate the formation of lateral organs. After embryonic development, secondary shoot meristems form in the boundary zones between the shoot apical meristem and leaf primordia, the leaf axils. In addition, many plant species develop ectopic meristems at different positions of the plant body. In the compound tomato leaf, ectopic meristems can initiate at the base of leaflets, which are delimited by two distinct boundary zones, referred to as the proximal (PLB) and distal (DLB) leaflet boundaries. We demonstrate that the two leaflet boundaries differ from each other and that ectopic meristem formation is strictly limited to the DLB. Our data suggest that the DLB harbours a group of pluripotent cells that seems to be the launching pad for meristem formation. Initiation of these meristems is dependent on the activities of the transcriptional regulators Goblet (Gob) and Lateral suppressor (Ls), specifically expressed in the DLB. Gob and Ls act in hierarchical order, because Ls transcript accumulation is dependent on Gob activity, but not vice versa. Ectopic meristem formation at the DLB is also observed in other seed plants, like Cardamine pratensis, indicating that it is part of a widespread developmental program. Ectopic meristem formation leads to an increase in the number of buds, enhances the capacity for survival and opens the route to vegetative propagation. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

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

    Science.gov (United States)

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

    2016-06-22

    Inspired by the preparation of the hierarchically-porous carbon (HPC) derived from metal organic frameworks (MOFs) for energy storage, in this work, a simple iron-based metal- organic complex (MOC), which was simpler and cheaper compared with the MOF, was selected to achieve versatile energy storage. The intertwined 1 D nanospindles and enriched-oxygen doping of the HPC was obtained after one-step carbonization of the MOC. When employed in lithium-ion batteries, the HPC exhibited reversible capacity of 778 mA h g(-1) after 60 cycles at 50 mA g(-1) . Moreover, the HPC maintained a capacity of 188 mA h g(-1) after 400 cycles at 100 mA g(-1) as the anode material in a sodium-ion battery. In addition, the HPC served as the cathode matrix for evaluation of a lithium-sulfur battery. The general preparation process of the HPC is commercial, which is responsible for the large-scale production for its practical application. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. HDS: Hierarchical Data System

    Science.gov (United States)

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

    2015-02-01

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

  8. 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

    2013-01-01

    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 als

  9. Hierarchical part-type segmentation using voxel-based curve skeletons

    NARCIS (Netherlands)

    Reniers, Dennie; Telea, Alexandru

    2008-01-01

    We present an effective framework for segmenting 3D shapes into meaningful components using the curve skeleton. Our algorithm identifies a number of critical points on the efficiently computed curve skeleton, either fully automatically as the junctions of the curve skeleton, or based on user input.

  10. 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…

  11. Edge Crossing Minimization Algorithm for Hierarchical Graphs Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    We present an edge crossing minimization algorithm forhierarchical gr aphs based on genetic algorithms, and comparing it with some heuristic algorithm s. The proposed algorithm is more efficient and has the following advantages: th e frame of the algorithms is unified, the method is simple, and its implementati on and revision are easy.

  12. A Meta Analysis and Hierarchical Classification of HU-Based Atherosclerotic Plaque Characterization Criteria

    NARCIS (Netherlands)

    Kristanto, Wisnumurti; van Ooijen, Peter M. A.; Jansen-van der Weide, Marijke C.; Vliegenthart, Rozemarijn; Oudkerk, Matthijs

    2013-01-01

    Background: Many computed tomography (CT) studies have reported that lipid-rich, presumably rupture-prone atherosclerotic plaques can be characterized according to their Hounsfield Unit (HU) value. However, the published HU-based characterization criteria vary considerably. The present study aims to

  13. 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

    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 ...

  14. A CAD System for Identification and Classification of Breast Cancer Tumors in DCE-MR Images Based on Hierarchical Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Rastiboroujeni

    2015-06-01

    Full Text Available In this paper, we propose a computer aided diagnosis (CAD system based on hierarchical convolutional neural networks (HCNNs to discriminate between malignant and benign tumors in breast DCE-MRIs. A HCNN is a hierarchical neural network that operates on two-dimensional images. A HCNN integrates feature extraction and classification processes into one single and fully adaptive structure. It can extract two-dimensional key features automatically, and it is relatively tolerant to geometric and local distortions in input images. We evaluate CNN implementation learning and testing processes based on gradient descent (GD and resilient back-propagation (RPROP approaches. We show that, proposed HCNN with RPROP learning approach provide an effective and robust neural structure to design a CAD base system for breast MRI, and has potential as a mechanism for the evaluation of different types of abnormalities in medical images.

  15. HIERARCHICAL DOCUMENT ORGANIZATION AND RETRIEVAL BASED ON THEMES FOR NEWS TRACKS

    Directory of Open Access Journals (Sweden)

    S. M. Arnica Sowmi

    2013-12-01

    Full Text Available Organizing text documents is an important task and there are also numbers of strategies available in it. A good document clustering approach can assist computers in organizing the document corpus automatically into a meaningful cluster hierarchy for efficient browsing and navigation, which is very valuable for overcoming the deficiencies of traditional information retrieval methods. By clustering the text documents, the documents sharing the same topic are grouped together. Unlike document classification, no labelled documents are provided in clustering. Hence clustering is also known as unsupervised learning. In case of term based data retrieval, time consumption problem prevails. This is because as for each term, the data set’s has to be retrieved. Hence we are going for taxonomy based data retrieval. This paper presents the taxonomical approach of clustering data set in a dynamic environment. It is a difficult task to cluster data in a dynamic environment. But this can be made easily by using RSS feeds.

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

    OpenAIRE

    David O. Yawson; Armah, Frederick A.; Alex N. M. Pappoe

    2009-01-01

    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 ...

  17. Large-Scale Automatic Labeling of Video Events with Verbs Based on Event-Participant Interaction

    CERN Document Server

    Barbu, Andrei; Coroian, Dan; Dickinson, Sven; Mussman, Sam; Narayanaswamy, Siddharth; Salvi, Dhaval; Schmidt, Lara; Shangguan, Jiangnan; Siskind, Jeffrey Mark; Waggoner, Jarrell; Wang, Song; Wei, Jinlian; Yin, Yifan; Zhang, Zhiqi

    2012-01-01

    We present an approach to labeling short video clips with English verbs as event descriptions. A key distinguishing aspect of this work is that it labels videos with verbs that describe the spatiotemporal interaction between event participants, humans and objects interacting with each other, abstracting away all object-class information and fine-grained image characteristics, and relying solely on the coarse-grained motion of the event participants. We apply our approach to a large set of 22 distinct verb classes and a corpus of 2,584 videos, yielding two surprising outcomes. First, a classification accuracy of greater than 70% on a 1-out-of-22 labeling task and greater than 85% on a variety of 1-out-of-10 subsets of this labeling task is independent of the choice of which of two different time-series classifiers we employ. Second, we achieve this level of accuracy using a highly impoverished intermediate representation consisting solely of the bounding boxes of one or two event participants as a function of ...

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

    Energy Technology Data Exchange (ETDEWEB)

    Lipnikov, Konstantin [Los Alamos National Laboratory; Agouzal, Abdellatif [UNIV DE LYON; Vassilevski, Yuri [Los Alamos National Laboratory

    2009-01-01

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

  19. Hierarchical Downlink Resource Management Framework for OFDMA based WiMAX Systems

    DEFF Research Database (Denmark)

    Wang, Hua; Iversen, Villy Bæk

    2008-01-01

    resource management framework for OFDMA based WiMAX systems. Our framework consists of a dynamic resource allocation (DRA) module and a connection admission control (CAC) module. DRA emphasizes on how to share the limited radio resources in term of subchannels and time slots among WiMAX subscribers...... belonging to different service classes with the objective of increasing the spectral efficiency while satisfying the diverse QoS requirements in each service class. CAC highlights how to limit the number of ongoing connections preventing the system capacity from being overused. Through system...

  20. 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.

  1. Study of a Comprehensive Assessment Method for Coal Mine Safety Based on a Hierarchical Grey Analysis

    Institute of Scientific and Technical Information of China (English)

    LIU Ya-jing; MAO Shan-jun; LI Mei; YAO Ji-ming

    2007-01-01

    Coal mine safety is a complex system, which is controlled by a number of interrelated factors and is difficult to estimate. This paper proposes an index system of safety assessment based on correlated factors involved in coal mining and a comprehensive evaluation model that combines the advantages of the AHP and a grey clustering method to guarantee the accuracy and objectivity of weight coefficients. First, we confirmed the weight of every index using the AHP, then did a general safety assessment by means of a grey clustering method. This model analyses the status of mining safety both qualitatively and quantitatively. It keeps management and technical groups informed of the situation of the coal production line in real time, which aids in making correct decisions based on practical safety issues. A case study in the application of the model is presented. The results show that the method is applicable and realistic with regard to the core of a coal mine's safety management. Consequently, the safe production of a mine and the awareness of advanced safe production management is accelerated.

  2. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    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.

  3. Model-Based Event Detection in Wireless Sensor Networks

    CERN Document Server

    Gupchup, Jayant; Burns, Randal; Szalay, Alex

    2009-01-01

    In this paper we present an application of techniques from statistical signal processing to the problem of event detection in wireless sensor networks used for environmental monitoring. The proposed approach uses the well-established Principal Component Analysis (PCA) technique to build a compact model of the observed phenomena that is able to capture daily and seasonal trends in the collected measurements. We then use the divergence between actual measurements and model predictions to detect the existence of discrete events within the collected data streams. Our preliminary results show that this event detection mechanism is sensitive enough to detect the onset of rain events using the temperature modality of a wireless sensor network.

  4. Multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory-based environmental risk evaluation for tailings reservoirs

    Institute of Scientific and Technical Information of China (English)

    田森; 陈建宏

    2015-01-01

    Environmental risk assessment of tailings reservoir assessment system is complex and has many index factors. In order to accurately judge surrounding environmental risks of tailings reservoirs and determinate the corresponding prevention and control work, multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory are implemented to evaluate them and find out the rules of this evaluation system with 14 representative cases. The methods of multi-hierarchical fuzzy evaluation can overall consider each influence factor of risk assessment system and their mutual impact, and the index weight based on the analytic hierarchy process is relatively reasonable. Rough set theory based on dominance relation reduces each index attribute from the top down, largely simplifies the complexity of the original evaluation system, and considers the preferential information in each index. Furthermore, grey correlation theory is applied to analysis of importance of each reducted condition attribute. The results demonstrate the feasibility of the proposed safety evaluation system and the application potential.

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

    Science.gov (United States)

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

    2012-01-01

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

  7. 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.

  8. 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.

  9. Prediction problem for target events based on the inter-event waiting time

    Science.gov (United States)

    Shapoval, A.

    2010-11-01

    In this paper we address the problem of forecasting the target events of a time series given the distribution ξ of time gaps between target events. Strong earthquakes and stock market crashes are the two types of such events that we are focusing on. In the series of earthquakes, as McCann et al. show [W.R. Mc Cann, S.P. Nishenko, L.R. Sykes, J. Krause, Seismic gaps and plate tectonics: seismic potential for major boundaries, Pure and Applied Geophysics 117 (1979) 1082-1147], there are well-defined gaps (called seismic gaps) between strong earthquakes. On the other hand, usually there are no regular gaps in the series of stock market crashes [M. Raberto, E. Scalas, F. Mainardi, Waiting-times and returns in high-frequency financial data: an empirical study, Physica A 314 (2002) 749-755]. For the case of seismic gaps, we analytically derive an upper bound of prediction efficiency given the coefficient of variation of the distribution ξ. For the case of stock market crashes, we develop an algorithm that predicts the next crash within a certain time interval after the previous one. We show that this algorithm outperforms random prediction. The efficiency of our algorithm sets up a lower bound of efficiency for effective prediction of stock market crashes.

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

    Science.gov (United States)

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

    2016-06-08

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

  11. Deterministic event-based simulation of quantum phenomena

    NARCIS (Netherlands)

    De Raedt, K; De Raedt, H; Michielsen, K

    2005-01-01

    We propose and analyse simple deterministic algorithms that can be used to construct machines that have primitive learning capabilities. We demonstrate that locally connected networks of these machines can be used to perform blind classification on an event-by-event basis, without storing the inform

  12. Relevant sampling applied to event-based state-estimation

    NARCIS (Netherlands)

    Marck, J.W.; Sijs, J.

    2010-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are de

  13. A process-oriented event-based programming language

    DEFF Research Database (Denmark)

    Hildebrandt, Thomas; Zanitti, Francesco

    2012-01-01

    Vi præsenterer den første version af PEPL, et deklarativt Proces-orienteret, Event-baseret Programmeringssprog baseret på den fornyligt introducerede Dynamic Condition Response (DCR) Graphs model. DCR Graphs tillader specifikation, distribuerede udførsel og verifikation af pervasive event-basered...... defineret og udført i en almindelig web-browser....

  14. Logical Discrete Event Systems in a trace theory based setting

    NARCIS (Netherlands)

    Smedinga, R.

    1993-01-01

    Discrete event systems can be modelled using a triple consisting of some alphabet (representing the events that might occur), and two trace sets (sets of possible strings) denoting the possible behaviour and the completed tasks of the system. Using this definition we are able to formulate and solve

  15. A process-oriented event-based programming language

    DEFF Research Database (Denmark)

    Hildebrandt, Thomas; Zanitti, Francesco

    2012-01-01

    Vi præsenterer den første version af PEPL, et deklarativt Proces-orienteret, Event-baseret Programmeringssprog baseret på den fornyligt introducerede Dynamic Condition Response (DCR) Graphs model. DCR Graphs tillader specifikation, distribuerede udførsel og verifikation af pervasive event-basered...

  16. Relevant sampling applied to event-based state-estimation

    NARCIS (Netherlands)

    Marck, J.W.; Sijs, J.

    2010-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are de

  17. Effects of Instructional Events in Computer-Based Instruction

    Science.gov (United States)

    Martin, Florence; Klein, James; Sullivan, Howard

    2004-01-01

    Forty years ago, Robert Gagne published the first edition of his book The Conditions of Learning (1965) in which he proposed nine events of instruction that provide a sequence for organizing a lesson. These events remain the foundation of current instructional design practice (Reiser, 2002; Richey, 2000). They represent desirable conditions in an…

  18. 基于规则的分层负载平衡调度模型%A Hierarchical Load Balancing Scheduling Model Based on Rules

    Institute of Scientific and Technical Information of China (English)

    李冬梅; 施海虎; 顾毓清

    2003-01-01

    On a massively parallel and distributed system and a network of workstations system, it is a critical problem to increase the utilization efficiency of resources and the answer speed of tasks by using effective load balancing scheduling strategy. This paper analyzes the scheduling strategy of dynamic load balancing and static load balancing,and then proposes a hierarchical load balancing scheduling model based on rules. Finally,making somecomparisons with Other scheduling models.

  19. Event based classification of Web 2.0 text streams

    CERN Document Server

    Bauer, Andreas

    2012-01-01

    Web 2.0 applications like Twitter or Facebook create a continuous stream of information. This demands new ways of analysis in order to offer insight into this stream right at the moment of the creation of the information, because lots of this data is only relevant within a short period of time. To address this problem real time search engines have recently received increased attention. They take into account the continuous flow of information differently than traditional web search by incorporating temporal and social features, that describe the context of the information during its creation. Standard approaches where data first get stored and then is processed from a peristent storage suffer from latency. We want to address the fluent and rapid nature of text stream by providing an event based approach that analyses directly the stream of information. In a first step we want to define the difference between real time search and traditional search to clarify the demands in modern text filtering. In a second s...

  20. Diet Activity Characteristic of Large-scale Sports Events Based on HACCP Management Model

    Directory of Open Access Journals (Sweden)

    Xiao-Feng Su

    2015-01-01

    Full Text Available The study proposed major sports events dietary management based on "HACCP" management model. According to the characteristic of major sports events catering activities. Major sports events are not just showcase level of competitive sports activities which have become comprehensive special events including social, political, economic, cultural and other factors, complex. Sporting events conferred reach more diverse goals and objectives of economic, political, cultural, technological and other influence and impact.

  1. 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.

  2. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

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

  3. RELATIONSHIP BETWEEN CULTURAL/ARTISTIC EVENTS VISITATION AND OTHER ACTIVITY-BASED TOURISM SEGMENTS

    National Research Council Canada - National Science Library

    Ana Tezak; Darko Saftic; Zdravko Sergo

    2011-01-01

    .... One of these specific forms of tourism is event tourism. The aim of this research is to determine the relationship between cultural/artistic events visitation and other activity-based tourism segments...

  4. Using Event-Based Parsing to Support Dynamic Protocol Evolution

    Science.gov (United States)

    2003-03-01

    System Generator HTTP 1.0 Parser Composer EBP System Generator HTTP 1.0 Parser Composer Client... Generator HTTP 1.0 Parser Composer EBP System Generator HTTP 1.0 Parser Composer Client HTTP 1.1 Proxy Event Handler 1-7 8 8 Fig. 8: Modified...configuration and scenario events 9 though 19. Server HTTP 1.0 EBP System Generator HTTP 1.0 Parser Composer Client HTTP 1.1 Proxy

  5. Event-based text mining for biology and functional genomics.

    Science.gov (United States)

    Ananiadou, Sophia; Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B

    2015-05-01

    The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of 'events', i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research.

  6. 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

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

    Science.gov (United States)

    Gendreau, Audrey

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

  8. Agreement between event-based and trend-based glaucoma progression analyses.

    Science.gov (United States)

    Rao, H L; Kumbar, T; Kumar, A U; Babu, J G; Senthil, S; Garudadri, C S

    2013-07-01

    To evaluate the agreement between event- and trend-based analyses to determine visual field (VF) progression in glaucoma. VFs of 175 glaucoma eyes with ≥5 VFs were analyzed by proprietary software of VF analyzer to determine progression. Agreement (κ) between trend-based analysis of VF index (VFI) and event-based analysis (glaucoma progression analysis, GPA) was evaluated. For eyes progressing by event- and trend-based methods, time to progression by two methods was calculated. Median number of VFs per eye was 7 and follow-up 7.5 years. GPA classified 101 eyes (57.7%) as stable, 30 eyes (17.1%) as possible and 44 eyes (25.2%) as likely progression. Trend-based analysis classified 122 eyes (69.7%) as stable (slope >-1% per year or any slope magnitude with P>0.05), 53 eyes (30.3%) as progressing with slope trend-based analysis was 0.48, and between specific criteria of GPA (possible clubbed with no progression) and trend-based analysis was 0.50. In eyes progressing by sensitive criteria of both methods (42 eyes), median time to progression by GPA (4.9 years) was similar (P=0.30) to trend-based method (5.0 years). This was also similar in eyes progressing by specific criteria of both methods (25 eyes; 5.6 years versus 5.9 years, P=0.23). Agreement between event- and trend-based progression analysis was moderate. GPA seemed to detect progression earlier than trend-based analysis, but this wasn't statistically significant.

  9. Event-based text mining for biology and functional genomics

    Science.gov (United States)

    Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

    2015-01-01

    The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

  10. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  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...... 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....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  12. Event-based stormwater management pond runoff temperature model

    Science.gov (United States)

    Sabouri, F.; Gharabaghi, B.; Sattar, A. M. A.; Thompson, A. M.

    2016-09-01

    Stormwater management wet ponds are generally very shallow and hence can significantly increase (about 5.4 °C on average in this study) runoff temperatures in summer months, which adversely affects receiving urban stream ecosystems. This study uses gene expression programming (GEP) and artificial neural networks (ANN) modeling techniques to advance our knowledge of the key factors governing thermal enrichment effects of stormwater ponds. The models developed in this study build upon and compliment the ANN model developed by Sabouri et al. (2013) that predicts the catchment event mean runoff temperature entering the pond as a function of event climatic and catchment characteristic parameters. The key factors that control pond outlet runoff temperature, include: (1) Upland Catchment Parameters (catchment drainage area and event mean runoff temperature inflow to the pond); (2) Climatic Parameters (rainfall depth, event mean air temperature, and pond initial water temperature); and (3) Pond Design Parameters (pond length-to-width ratio, pond surface area, pond average depth, and pond outlet depth). We used monitoring data for three summers from 2009 to 2011 in four stormwater management ponds, located in the cities of Guelph and Kitchener, Ontario, Canada to develop the models. The prediction uncertainties of the developed ANN and GEP models for the case study sites are around 0.4% and 1.7% of the median value. Sensitivity analysis of the trained models indicates that the thermal enrichment of the pond outlet runoff is inversely proportional to pond length-to-width ratio, pond outlet depth, and directly proportional to event runoff volume, event mean pond inflow runoff temperature, and pond initial water temperature.

  13. Naive Probability: Model-Based Estimates of Unique Events.

    Science.gov (United States)

    Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N

    2015-08-01

    We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning.

  14. A simulation based approach to quantify the difference between event-based and routine water quality monitoring schemes

    Directory of Open Access Journals (Sweden)

    J.S. Lessels

    2015-09-01

    New hydrological insights for the region: The inclusion of event-based sampling improved annual load estimates of all sites with a maximum RMSE difference of 16.11 tonnes between event-based and routine sampling. Based on the accuracy of annual loads, event-based sampling was found to be more important in catchments with a large relief and high annual rainfall in this region. Using this approach, different sampling schemes can be compared based on limited historical data.

  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-param...

  16. Linguistic scope-based and biological event-based speculation and negation annotations in the BioScope and Genia Event corpora

    Directory of Open Access Journals (Sweden)

    Vincze Veronika

    2011-10-01

    Full Text Available Abstract Background The treatment of negation and hedging in natural language processing has received much interest recently, especially in the biomedical domain. However, open access corpora annotated for negation and/or speculation are hardly available for training and testing applications, and even if they are, they sometimes follow different design principles. In this paper, the annotation principles of the two largest corpora containing annotation for negation and speculation – BioScope and Genia Event – are compared. BioScope marks linguistic cues and their scopes for negation and hedging while in Genia biological events are marked for uncertainty and/or negation. Results Differences among the annotations of the two corpora are thematically categorized and the frequency of each category is estimated. We found that the largest amount of differences is due to the issue that scopes – which cover text spans – deal with the key events and each argument (including events within events of these events is under the scope as well. In contrast, Genia deals with the modality of events within events independently. Conclusions The analysis of multiple layers of annotation (linguistic scopes and biological events showed that the detection of negation/hedge keywords and their scopes can contribute to determining the modality of key events (denoted by the main predicate. On the other hand, for the detection of the negation and speculation status of events within events, additional syntax-based rules investigating the dependency path between the modality cue and the event cue have to be employed.

  17. The COMPASS event store

    CERN Document Server

    Duic, V; Fuchs, U; Gobbo, B; Lamanna, M; Martin, A; Nowak, M

    2004-01-01

    COMPASS, the fixed-target experiment at CERN studying the structure of the nucleon and spectroscopy, has collected over 500 TB during 2002 and 2003 runs. At the beginning of the experiment these data together with the reconstructed events information were put in a database infrastructure based on Objectivity/DB and on the hierarchical storage manager CASTOR. Starting from 2003 Oracle has been adopted as the database technology. The experience in the usage of the databases is reviewed, and the evolution of the system outlined.

  18. Event based state estimation with time synchronous updates

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.

    2012-01-01

    To reduce the amount of data transfer in networked systems, measurements are usually taken only when an event occurs rather than at each synchronous sample instant. However, this complicates estimation problems considerably, especially in the situation when no measurement is received anymore. The go

  19. Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing

    OpenAIRE

    Fan, Deliang; Sharad, Mrigank; Sengupta, Abhronil; Roy, Kaushik

    2014-01-01

    Hierarchical temporal memory (HTM) tries to mimic the computing in cerebral-neocortex. It identifies spatial and temporal patterns in the input for making inferences. This may require large number of computationally expensive tasks like, dot-product evaluations. Nano-devices that can provide direct mapping for such primitives are of great interest. In this work we show that the computing blocks for HTM can be mapped using low-voltage, fast-switching, magneto-metallic spin-neurons combined wit...

  20. The New Model of Chemical Evolution of r-process Elements Based on The Hierarchical Galaxy Formation I: Ba and Eu

    CERN Document Server

    Komiya, Yutaka; Suda, Takuma; Fujimoto, Masayuki Y

    2014-01-01

    We investigate the chemical enrichment of r-process elements in the early evolutionary stages of the Milky Way halo within the framework of hierarchical galaxy formation using a semi-analytic merger tree. In this paper, we focus on heavy r-process elements, Ba and Eu, of extremely metal-poor (EMP) stars and give constraints on their astronomical sites. Our models take into account changes of the surface abundances of EMP stars by the accretion of interstellar matter (ISM). We also consider metal-enrichment of intergalactic medium (IGM) by galactic winds and the resultant pre-enrichment of proto-galaxies. The trend and scatter of the observed r-process abundances are well reproduced by our hierarchical model with $\\sim 10\\%$ of core-collapse supernovae in low-mass end ($\\sim 10M_{\\odot}$) as a dominant r-process source and the star formation efficiency of $\\sim 10^{-10} \\hbox{yr}^{-1}$. For neutron star mergers as an r-process source, their coalescence timescale has to be $ \\sim 10^7$yrs, and the event rates $...

  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. Event Management for Teacher-Coaches: Risk and Supervision Considerations for School-Based Sports

    Science.gov (United States)

    Paiement, Craig A.; Payment, Matthew P.

    2011-01-01

    A professional sports event requires considerable planning in which years are devoted to the success of that single activity. School-based sports events do not have that luxury, because high schools across the country host athletic events nearly every day. It is not uncommon during the fall sports season for a combination of boys' and girls'…

  3. Event Management for Teacher-Coaches: Risk and Supervision Considerations for School-Based Sports

    Science.gov (United States)

    Paiement, Craig A.; Payment, Matthew P.

    2011-01-01

    A professional sports event requires considerable planning in which years are devoted to the success of that single activity. School-based sports events do not have that luxury, because high schools across the country host athletic events nearly every day. It is not uncommon during the fall sports season for a combination of boys' and girls'…

  4. Nanosheet-based hierarchical Ni(2)(CO(3))(OH)(2) microspheres with weak crystallinity for high-performance supercapacitor.

    Science.gov (United States)

    Zhu, Guoxing; Xi, Chunyan; Shen, Mengqi; Bao, Chunlin; Zhu, Jun

    2014-10-08

    Three-dimensionally hierarchical oxide/hydroxide materials have recently attracted increasing interest by virtue of their exciting potential in electrochemical energy conversion and storage. Herein, hierarchical Ni2(CO3)(OH)2 microspheres assembled from ultrathin nanosheets were successfully synthesized by a one-pot/one-step hydrothermal route. In this method, common nickel salts and urea were selected as raw materials. The influence of urea concentration on the final product was studied. The hierarchical Ni2(CO3)(OH)2 microspheres show weak crystallinity and contain crystalline water. It was found that they exhibit excellent rate capacity when used as supercapacitor electrode. Under current density of 0.5 and 10 A/g, the optimized Ni2(CO3)(OH)2 electrode with loading density of 5.3 mg/cm(2) exhibited specific capacitances of 1178 and 613 F/g with excellent cycling stability. The excellent electrochemical property is possibly attributed to the intrinsic nature of Ni2(CO3)(OH)2, the ultrathin thickness of nanosheet units, and the sufficient space available to interact with the electrolyte. This facile synthesis strategy and the good electrochemical properties indicate that hydroxycarbonates are promising materials for supercapacitor application. This study suggests a large library of materials for potential application in energy storage systems.

  5. Discrete Topology Based Hierarchical Segmentation for Efficient Object-Based Image Analyis: Application to Object Detection in High Resolution Satellite Images

    Science.gov (United States)

    Syed, A. H.; Saber, E.; Messinger, D.

    2013-05-01

    With rapid developments in satellite and sensor technologies, there has been a dramatic increase in the availability of high resolution (HR) remotely sensed images. Hence, the ability to collect images remotely is expected to far exceed our capacity to analyse these images manually. Consequently, techniques that can handle large volumes of data are urgently needed. In many of today's multiscale techniques the underlying representation of objects is still pixel-based, i.e. object entities are still described/accessed via pixelbased descriptors, thereby creating a bottleneck when processing large volumes of data. Also, these techniques do not yet leverage the topological and contextual information present in the image. We propose a framework for Discrete Topology based hierarchical segmentation, addressing both the algorithms and data structures that will be required. The framework consists of three components: 1) Conversion to dart-based representation, 2) Size-Constrained-Region Merging to generate multiple segmentations, and 3) Update of two sparse arrays SIGMA and LAMBDA which together encode the topology of each region in the hierarchy. The results of our representation are demonstrated both on a synthetic and a real high resolution images. Application of this representation to objectdetection is also discussed.

  6. Automatic event detection based on artificial neural networks

    Science.gov (United States)

    Doubravová, Jana; Wiszniowski, Jan; Horálek, Josef

    2015-04-01

    The proposed algorithm was developed to be used for Webnet, a local seismic network in West Bohemia. The Webnet network was built to monitor West Bohemia/Vogtland swarm area. During the earthquake swarms there is a large number of events which must be evaluated automatically to get a quick estimate of the current earthquake activity. Our focus is to get good automatic results prior to precise manual processing. With automatic data processing we may also reach a lower completeness magnitude. The first step of automatic seismic data processing is the detection of events. To get a good detection performance we require low number of false detections as well as high number of correctly detected events. We used a single layer recurrent neural network (SLRNN) trained by manual detections from swarms in West Bohemia in the past years. As inputs of the SLRNN we use STA/LTA of half-octave filter bank fed by vertical and horizontal components of seismograms. All stations were trained together to obtain the same network with the same neuron weights. We tried several architectures - different number of neurons - and different starting points for training. Networks giving the best results for training set must not be the optimal ones for unknown waveforms. Therefore we test each network on test set from different swarm (but still with similar characteristics, i.e. location, focal mechanisms, magnitude range). We also apply a coincidence verification for each event. It means that we can lower the number of false detections by rejecting events on one station only and force to declare an event on all stations in the network by coincidence on two or more stations. In further work we would like to retrain the network for each station individually so each station will have its own coefficients (neural weights) set. We would also like to apply this method to data from Reykjanet network located in Reykjanes peninsula, Iceland. As soon as we have a reliable detection, we can proceed to

  7. Qualitative Event-based Diagnosis with Possible Conflicts Applied to Spacecraft Power Distribution Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based diagnosis enables efficient and safe operation of engineered systems. In this paper, we describe two algorithms based on a qualitative event-based fault...

  8. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

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

  9. A fuzzy-decision based approach for Composite event detection in wireless sensor networks.

    Science.gov (United States)

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming; Jia, Juncheng

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic.

  10. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Shukui Zhang

    2014-01-01

    Full Text Available The event detection is one of the fundamental researches in wireless sensor networks (WSNs. Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic.

  11. XML Schema-Based Minification for Communication of Security Information and Event Management (SIEM Systems in Cloud Environments

    Directory of Open Access Journals (Sweden)

    Bishoy Moussa

    2014-09-01

    Full Text Available XML-based communication governs most of today’s systems communication, due to its capability of representing complex structural and hierarchical data. However, XML document structure is considered a huge and bulky data that can be reduced to minimize bandwidth usage, transmission time, and maximize performance. This contributes to a more efficient and utilized resource usage. In cloud environments, this affects the amount of money the consumer pays. Several techniques are used to achieve this goal. This paper discusses these techniques and proposes a new XML Schema-based Minification technique. The proposed technique works on XML Structure reduction using minification. The proposed technique provides a separation between the meaningful names and the underlying minified names, which enhances software/code readability. This technique is applied to Intrusion Detection Message Exchange Format (IDMEF messages, as part of Security Information and Event Management (SIEM system communication hosted on Microsoft Azure Cloud. Test results show message size reduction ranging from 8.15% to 50.34% in the raw message, without using time-consuming compression techniques. Adding GZip compression to the proposed technique produces 66.1% shorter message size compared to original XML messages.

  12. Computation of Edge-Edge-Edge Events Based on Conicoid Theory for 3-D Object Recognition

    Institute of Scientific and Technical Information of China (English)

    WU Chenye; MA Huimin

    2009-01-01

    The availability of a good viewpoint space partition is crucial in three dimensional (3-D) object rec-ognition on the approach of aspect graph. There are two important events depicted by the aspect graph ap-proach, edge-edge-edge (EEE) events and edge-vertex (EV) events. This paper presents an algorithm to compute EEE events by characteristic analysis based on conicoid theory, in contrast to current algorithms that focus too much on EV events and often overlook the importance of EEE events. Also, the paper provides a standard flowchart for the viewpoint space partitioning based on aspect graph theory that makes it suitable for perspective models. The partitioning result best demonstrates the algorithm's efficiency with more valu-able viewpoints found with the help of EEE events, which can definitely help to achieve high recognition rate for 3-D object recognition.

  13. Model based monitoring of wellbore hydraulics for abnormal event detection

    Energy Technology Data Exchange (ETDEWEB)

    Todorov, Dimitar; Fruhwirth, Rudolf K. [Thonhauser Data Engineering GmbH, Leoben (Austria); Thonhauser, Gerhard [Montanuniversitaet Leoben (Austria)

    2013-03-15

    With the increasing demand for energy in the last decades, the petroleum industry was forced to push the limits to levels that have never been reached before. Exploring very deep waters, drilling under varying conditions of extreme pressure and temperature and dealing with issues, which involve a new level of understanding, are challenges, which need to be overcome in order to safely and successfully accomplish the planned goals. Operating under such circumstances obligates the driller to be extremely precise in his actions. Even with the driller's extensive experience and training, the possible reaction time is in some cases extremely short. This article discusses the reasons for automatic trouble event recognition systems in the drilling process and how these affect the drilling operations and optimization processes. In this respect a concept of a real time hydraulic monitor will be developed helping the driller to visualize calculations in a plot, showing the pump limitations, the limitations due to the formation fracture gradient and the hole cleaning requirements. Additionally, taking into account the complete wellbore hydraulics and introducing various well behavior models and different algorithms, the system is capable of operating as a real-time indicator for undesired downhole events. (orig.)

  14. 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

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

    Science.gov (United States)

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

    2016-02-01

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

  16. Assessing the continuum of event-based biosurveillance through an operational lens.

    Science.gov (United States)

    Corley, Courtney D; Lancaster, Mary J; Brigantic, Robert T; Chung, James S; Walters, Ronald A; Arthur, Ray R; Bruckner-Lea, Cynthia J; Calapristi, Augustin; Dowling, Glenn; Hartley, David M; Kennedy, Shaun; Kircher, Amy; Klucking, Sara; Lee, Eva K; McKenzie, Taylor; Nelson, Noele P; Olsen, Jennifer; Pancerella, Carmen; Quitugua, Teresa N; Reed, Jeremy Todd; Thomas, Carla S

    2012-03-01

    This research follows the Updated Guidelines for Evaluating Public Health Surveillance Systems, Recommendations from the Guidelines Working Group, published by the Centers for Disease Control and Prevention nearly a decade ago. Since then, models have been developed and complex systems have evolved with a breadth of disparate data to detect or forecast chemical, biological, and radiological events that have a significant impact on the One Health landscape. How the attributes identified in 2001 relate to the new range of event-based biosurveillance technologies is unclear. This article frames the continuum of event-based biosurveillance systems (that fuse media reports from the internet), models (ie, computational that forecast disease occurrence), and constructs (ie, descriptive analytical reports) through an operational lens (ie, aspects and attributes associated with operational considerations in the development, testing, and validation of the event-based biosurveillance methods and models and their use in an operational environment). A workshop was held in 2010 to scientifically identify, develop, and vet a set of attributes for event-based biosurveillance. Subject matter experts were invited from 7 federal government agencies and 6 different academic institutions pursuing research in biosurveillance event detection. We describe 8 attribute families for the characterization of event-based biosurveillance: event, readiness, operational aspects, geographic coverage, population coverage, input data, output, and cost. Ultimately, the analyses provide a framework from which the broad scope, complexity, and relevant issues germane to event-based biosurveillance useful in an operational environment can be characterized.

  17. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  18. Oil Spill! An Event-Based Science Module. Student Edition. Oceanography Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  19. Oil Spill!: An Event-Based Science Module. Teacher's Guide. Oceanography Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school earth science or general science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event- based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork,…

  20. Blight! An Event-Based Science Module. Student Edition. Plants and Plant Diseases Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  1. Asteroid! An Event-Based Science Module. Student Edition. Astronomy Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  2. Asteroid! An Event-Based Science Module. Teacher's Guide. Astronomy Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school earth science or general science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event- based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork,…

  3. Asteroid! An Event-Based Science Module. Teacher's Guide. Astronomy Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school earth science or general science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event- based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork,…

  4. Asteroid! An Event-Based Science Module. Student Edition. Astronomy Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  5. Gold Rush!: An Event-Based Science Module. Student Edition. Rocks and Minerals Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  6. Gold Rush!: An Event-Based Science Module. Teacher's Guide. Geology Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school earth science or general science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event- based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork,…

  7. Blight! An Event-Based Science Module. Teacher's Guide. Plants and Plant Diseases Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school life science or physical science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event- based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork,…

  8. Volcano!: An Event-Based Science Module. Teacher's Guide. Geology Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school earth science teachers to help their students learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research,…

  9. Volcano!: An Event-Based Science Module. Student Edition. Geology Module.

    Science.gov (United States)

    Wright, Russell G.

    This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…

  10. Associative Hierarchical Random Fields.

    Science.gov (United States)

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

    2014-06-01

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

  11. Event-based simulation of neutron interferometry experiments

    CERN Document Server

    De Raedt, Hans; Michielsen, Kristel

    2012-01-01

    A discrete-event approach, which has already been shown to give a cause-and-effect explanation of many quantum optics experiments, is applied to single-neutron interferometry experiments. The simulation algorithm yields a logically consistent description in terms of individual neutrons and does not require the knowledge of the solution of a wave equation. It is shown that the simulation method reproduces the results of several single-neutron interferometry experiments, including experiments which, in quantum theoretical language, involve entanglement. Our results demonstrate that classical (non-Hamiltonian) systems can exhibit correlations which in quantum theory are associated with interference and entanglement, also when all particles emitted by the source are accounted for.

  12. An event-based architecture for solving constraint satisfaction problems

    Science.gov (United States)

    Mostafa, Hesham; Müller, Lorenz K.; Indiveri, Giacomo

    2015-12-01

    Constraint satisfaction problems are ubiquitous in many domains. They are typically solved using conventional digital computing architectures that do not reflect the distributed nature of many of these problems, and are thus ill-suited for solving them. Here we present a parallel analogue/digital hardware architecture specifically designed to solve such problems. We cast constraint satisfaction problems as networks of stereotyped nodes that communicate using digital pulses, or events. Each node contains an oscillator implemented using analogue circuits. The non-repeating phase relations among the oscillators drive the exploration of the solution space. We show that this hardware architecture can yield state-of-the-art performance on random SAT problems under reasonable assumptions on the implementation. We present measurements from a prototype electronic chip to demonstrate that a physical implementation of the proposed architecture is robust to practical non-idealities and to validate the theory proposed.

  13. 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

    2016-09-01

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

  14. 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.

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

    Science.gov (United States)

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

    2016-05-01

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

  16. Event-building and PC farm based level-3 trigger at the CDF experiment

    CERN Document Server

    Anikeev, K; Furic, I K; Holmgren, D; Korn, A J; Kravchenko, I V; Mulhearn, M; Ngan, P; Paus, C; Rakitine, A; Rechenmacher, R; Shah, T; Sphicas, Paris; Sumorok, K; Tether, S; Tseng, J

    2000-01-01

    In the technical design report the event building process at Fermilab's CDF experiment is required to function at an event rate of 300 events/sec. The events are expected to have an average size of 150 kBytes (kB) and are assembled from fragments of 16 readout locations. The fragment size from the different locations varies between 12 kB and 16 kB. Once the events are assembled they are fed into the Level-3 trigger which is based on processors running programs to filter events using the full event information. Computing power on the order of a second on a Pentium II processor is required per event. The architecture design is driven by the cost and is therefore based on commodity components: VME processor modules running VxWorks for the readout, an ATM switch for the event building, and Pentium PCs running Linux as an operation system for the Level-3 event processing. Pentium PCs are also used to receive events from the ATM switch and further distribute them to the processing nodes over multiple 100 Mbps Ether...

  17. A Model for Slicing JAVA Programs Hierarchically

    Institute of Scientific and Technical Information of China (English)

    Bi-Xin Li; Xiao-Cong Fan; Jun Pang; Jian-Jun Zhao

    2004-01-01

    Program slicing can be effectively used to debug, test, analyze, understand and maintain objectoriented software. In this paper, a new slicing model is proposed to slice Java programs based on their inherent hierarchical feature. The main idea of hierarchical slicing is to slice programs in a stepwise way, from package level, to class level, method level, and finally up to statement level. The stepwise slicing algorithm and the related graph reachability algorithms are presented, the architecture of the Java program Analyzing Tool (JATO) based on hierarchical slicing model is provided, the applications and a small case study are also discussed.

  18. An Event-Based Methodology to Generate Class Diagrams and its Empirical Evaluation

    Directory of Open Access Journals (Sweden)

    Sandeep K. Singh

    2010-01-01

    Full Text Available Problem statement: Event-based systems have importance in many application domains ranging from real time monitoring systems in production, logistics, medical devices and networking to complex event processing in finance and security. The increasing popularity of Event-based systems has opened new challenging issues for them. One such issue is to carry out requirements analysis of event-based systems and build conceptual models. Currently, Object Oriented Analysis (OOA using Unified Modeling Language (UML is the most popular requirement analysis approach for which several OOA tools and techniques have been proposed. But none of the techniques and tools to the best of our knowledge, have focused on event-based requirements analysis, rather all are behavior-based approaches. Approach: This study described a requirement analysis approach specifically for event based systems. The proposed approach started from events occurring in the system and derives an importable class diagram specification in XML Metadata Interchange (XMI format for Argo UML tool. Requirements of the problem domain are captured as events in restricted natural language using the proposed Event Templates in order to reduce the ambiguity. Results: Rules were designed to extract a domain model specification (analysis-level class diagram from Event Templates. A prototype tool 'EV-ClassGEN' is also developed to provide automation support to extract events from requirements, document the extracted events in Event Templates and implement rules to derive specification for an analysis-level class diagram. The proposed approach is also validated through a controlled experiment by applying it on many cases from different application domains like real time systems, business applications, gaming. Conclusion: Results of the controlled experiment had shown that after studying and applying Event-based approach, student's perception about ease of use and usefulness of OOA technique has

  19. 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.

  20. 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.

  1. 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.

  2. 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

    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...... 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...... and L stand for spherical, spherical in liquid-like state, spherical in body-centered-cubic arrangement, cylindrical and lamellar, respectively. Synchrotron small angle X-ray scattering (SAXS) and crossed polarizers, together with SAXS modelling analysis, were used for a detailed structural study...

  3. Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing.

    Science.gov (United States)

    Fan, Deliang; Sharad, Mrigank; Sengupta, Abhronil; Roy, Kaushik

    2016-09-01

    Hierarchical temporal memory (HTM) tries to mimic the computing in cerebral neocortex. It identifies spatial and temporal patterns in the input for making inferences. This may require a large number of computationally expensive tasks, such as dot product evaluations. Nanodevices that can provide direct mapping for such primitives are of great interest. In this paper, we propose that the computing blocks for HTM can be mapped using low-voltage, magnetometallic spin-neurons combined with an emerging resistive crossbar network, which involves a comprehensive design at algorithm, architecture, circuit, and device levels. Simulation results show the possibility of more than 200× lower energy as compared with a 45-nm CMOS ASIC design.

  4. Galactic Cosmic Ray Event-Based Risk Model (GERM) Code

    Science.gov (United States)

    Cucinotta, Francis A.; Plante, Ianik; Ponomarev, Artem L.; Kim, Myung-Hee Y.

    2013-01-01

    This software describes the transport and energy deposition of the passage of galactic cosmic rays in astronaut tissues during space travel, or heavy ion beams in patients in cancer therapy. Space radiation risk is a probability distribution, and time-dependent biological events must be accounted for physical description of space radiation transport in tissues and cells. A stochastic model can calculate the probability density directly without unverified assumptions about shape of probability density function. The prior art of transport codes calculates the average flux and dose of particles behind spacecraft and tissue shielding. Because of the signaling times for activation and relaxation in the cell and tissue, transport code must describe temporal and microspatial density of functions to correlate DNA and oxidative damage with non-targeted effects of signals, bystander, etc. These are absolutely ignored or impossible in the prior art. The GERM code provides scientists data interpretation of experiments; modeling of beam line, shielding of target samples, and sample holders; and estimation of basic physical and biological outputs of their experiments. For mono-energetic ion beams, basic physical and biological properties are calculated for a selected ion type, such as kinetic energy, mass, charge number, absorbed dose, or fluence. Evaluated quantities are linear energy transfer (LET), range (R), absorption and fragmentation cross-sections, and the probability of nuclear interactions after 1 or 5 cm of water equivalent material. In addition, a set of biophysical properties is evaluated, such as the Poisson distribution for a specified cellular area, cell survival curves, and DNA damage yields per cell. Also, the GERM code calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle in a selected material. The GERM code makes the numerical estimates of basic

  5. 基于PBIL算法的分层教学自动组班研究%Automatic Grouping of Hierarchical Teaching Based on PBIL Algorithm

    Institute of Scientific and Technical Information of China (English)

    刘日仙; 袁利永

    2011-01-01

    The adoption of hierarchial teaching mode brings a new challege to course scheduling and course elective. In this paper, an algorithm for automatic grouping of hierarchical teaching based on PBIL is proposed. The design of gene structure and the relationships between the optimal function and automatic grouping class constraint is emphasized. Experimental tests on real data show that the proposed algorithm of automatic grouping class can successfully solve the course scheduling problem in the hierarchical teaching mode. The practical application of it has good results.%分层教学模式的采用对选课排课工作带来了新的挑战.提出了一种基于PBIL的分层教学自动组班算法,重点论述了基因结构的设计,以及目标优化函数与自动组班约束条件之间的关系.基于实际数据的实验测试表明,本文提出的自动组班算法能够较好地解决分层教学模式下产生的排课选课问题,实际应用效果良好.

  6. 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

    2014-12-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  8. Influence of intra-event-based flood regime on sediment flow behavior from a typical agro-catchment of the Chinese Loess Plateau

    Science.gov (United States)

    Zhang, Le-Tao; Li, Zhan-Bin; Wang, He; Xiao, Jun-Bo

    2016-07-01

    The pluvial erosion process is significantly affected by tempo-spatial patterns of flood flows. However, despite their importance, only a few studies have investigated the sediment flow behavior that is driven by different flood regimes. The study aims to investigate the effect of intra-event-based flood regimes on the dynamics of sediment exports at Tuanshangou catchment, a typical agricultural catchment (unmanaged) in the hilly loess region on the Chinese Loess Plateau. Measurements of 193 flood events and 158 sediment-producing events were collected from Tuanshangou station between 1961 and 1969. The combined methods of hierarchical clustering approach, discriminant analysis and One-Way ANOVA were used to classify the flood events in terms of their event-based flood characteristics, including flood duration, peak discharge, and event flood runoff depth. The 193 flood events were classified into five regimes, and the mean statistical features of each regime significantly differed. Regime A includes flood events with the shortest duration (76 min), minimum flood crest (0.045 m s-1), least runoff depth (0.2 mm), and highest frequency. Regime B includes flood events with a medium duration (274 min), medium flood crest (0.206 m s-1), and minor runoff depth (0.7 mm). Regime C includes flood events with the longest duration (822 min), medium flood crest (0.236 m s-1), and medium runoff depth (1.7 mm). Regime D includes flood events with a medium duration (239 min), large flood crest (4.21 m s-1), and large runoff depth (10 mm). Regime E includes flood events with a medium duration (304 min), maximum flood crest (8.62 m s-1), and largest runoff depth (25.9 mm). The sediment yield by different flood regimes is ranked as follows: Regime E > Regime D > Regime B > Regime C > Regime A. In terms of event-based average and maximum suspended sediment concentration, these regimes are ordered as follows: Regime E > Regime D > Regime C > Regime B > Regime A. Regimes D and E

  9. Knowledge-Driven Event Extraction in Russian: Corpus-Based Linguistic Resources.

    Science.gov (United States)

    Solovyev, Valery; Ivanov, Vladimir

    2016-01-01

    Automatic event extraction form text is an important step in knowledge acquisition and knowledge base population. Manual work in development of extraction system is indispensable either in corpus annotation or in vocabularies and pattern creation for a knowledge-based system. Recent works have been focused on adaptation of existing system (for extraction from English texts) to new domains. Event extraction in other languages was not studied due to the lack of resources and algorithms necessary for natural language processing. In this paper we define a set of linguistic resources that are necessary in development of a knowledge-based event extraction system in Russian: a vocabulary of subordination models, a vocabulary of event triggers, and a vocabulary of Frame Elements that are basic building blocks for semantic patterns. We propose a set of methods for creation of such vocabularies in Russian and other languages using Google Books NGram Corpus. The methods are evaluated in development of event extraction system for Russian.

  10. Tag and Neighbor based Recommender systems for Medical events

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Dolog, Peter

    2010-01-01

    This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag...... in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach....

  11. Tag and Neighbor based Recommender systems for Medical events

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Dolog, Peter

    This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag...... in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach....

  12. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  13. Efficient hierarchical ID-based encryption scheme%一个高效的基于身份的分层加密方案

    Institute of Scientific and Technical Information of China (English)

    张席; 杨玲

    2012-01-01

    基于Gentry方案,利用双线性配对,提出了一个高效的基于身份的分层加密方案,在随机预言机模型下证明满足IND-ID-CCA2安全,通过分析,该方案较Gentry方案缩短了密文长度,解密仅需要进行一次双线性配对,大大提高了加密和解密的效率.%This paper proposes an efficient hierarchical id-based encryption scheme with bilinear pairing, which is based on Gentry scheme. This scheme meets IND-ID-CCA2 security in the random oracle model. This scheme reduces the ciphertext length, and only computes bilinear pairing once in the decryption, which increases the efficiency of encryption and decryption, compared with Gentry scheme.

  14. A Butterfly-Based Direct Integral-Equation Solver Using Hierarchical LU Factorization for Analyzing Scattering From Electrically Large Conducting Objects

    Science.gov (United States)

    Guo, Han; Liu, Yang; Hu, Jun; Michielssen, Eric

    2017-09-01

    A butterfly-based direct combined-field integral equation (CFIE) solver for analyzing scattering from electrically large, perfect electrically conducting objects is presented. The proposed solver leverages the butterfly scheme to compress blocks of the hierarchical LU-factorized discretized CFIE operator and uses randomized butterfly reconstruction schemes to expedite the factorization. The memory requirements and computational cost of the direct butterfly-CFIE solver scale as $O(N\\mathrm{log}^2N)$ and $O(N^{1.5}\\mathrm{log}N)$, respectively. These scaling estimates permit significant memory and CPU savings when compared to those realized by low-rank (LR) decomposition-based solvers. The efficacy and accuracy of the proposed solver are demonstrated through its application to the analysis of scattering from canonical and realistic objects involving up to 14 million unknowns.

  15. Hierarchical structure of biological systems

    Science.gov (United States)

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

    2014-01-01

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

  16. Generating weighted community networks based on local events

    Institute of Scientific and Technical Information of China (English)

    Xu Qi-Xin; Xu Xin-Jian

    2009-01-01

    realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes' strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

  17. A unifying Lyapunov-based framework for the event-triggered control of nonlinear systems

    CERN Document Server

    Postoyan, Romain; Nesic, Dragan; Tabuada, Paulo

    2011-01-01

    We present a prescriptive framework for the event-triggered control of nonlinear systems. Rather than closing the loop periodically, as traditionally done in digital control, in event-triggered implementations the loop is closed according to a state-dependent criterion. Event-triggered control is especially well suited for embedded systems and networked control systems since it reduces the amount of resources needed for control such as communication bandwidth. By modeling the event-triggered implementations as hybrid systems, we provide Lyapunov-based conditions to guarantee the stability of the resulting closed-loop system and explain how they can be utilized to synthesize event-triggering rules. We illustrate the generality of the approach by showing how it encompasses several existing event-triggering policies and by developing new strategies which further reduce the resources needed for control.

  18. Extraction of spatio-temporal information of earthquake event based on semantic technology

    Science.gov (United States)

    Fan, Hong; Guo, Dan; Li, Huaiyuan

    2015-12-01

    In this paper a web information extraction method is presented which identifies a variety of thematic events utilizing the event knowledge framework derived from text training, and then further uses the syntactic analysis to extract the event key information. The method which combines the text semantic information and domain knowledge of the event makes the extraction of information people interested more accurate. In this paper, web based earthquake news extraction is taken as an example. The paper firstly briefs the overall approaches, and then details the key algorithm and experiments of seismic events extraction. Finally, this paper conducts accuracy analysis and evaluation experiments which demonstrate that the proposed method is a promising way of hot events mining.

  19. A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

    Science.gov (United States)

    Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

    2017-01-01

    Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

  20. Dynamic hierarchical reinforcement learning based on probability model%基于概率模型的动态分层强化学习

    Institute of Scientific and Technical Information of China (English)

    戴朝晖; 袁姣红; 吴敏; 陈鑫

    2011-01-01

    为解决大规模强化学习中的"维度灾难"问题,克服以往学习算法的性能高度依赖于先验知识的局限性,本文提出一种基于概率模型的动态分层强化学习方法.首先基于贝叶斯学习对状态转移概率进行建模,建立基于概率参数的关键状态识别方法,进而通过聚类动态生成若干状态子空间和学习分层结构下的最优策略.仿真结果表明该算法能显著提高复杂环境下智能体的学习效率,适用于未知环境中的大规模学习.%To deal with the overwhelming dimensionality in the large-scale reinforcement-learning and the strong depen-dence on prior knowledge in existing learning algorithms,we propose the method of dynamic hierarchical reinforcement learning based on the probability model(DHRL--model).This method identifies some key states automatically based on probability parameters of the state-transition probability model established based on Bayesian learning,then generates some state-subspaces dynamically by clustering,and learns the optimal policy based on hierarchical structure.Simulation results show that DHRL--model algorithm improves the learning efficiency of the agent remarkably in the complex environment,and can be applied to learning in the unknown large-scale world.

  1. An observation-based approach to identify local natural dust events from routine aerosol ground monitoring

    Directory of Open Access Journals (Sweden)

    D. Q. Tong

    2012-02-01

    Full Text Available Dust is a major component of atmospheric aerosols in many parts of the world. Although there exist many routine aerosol monitoring networks, it is often difficult to obtain dust records from these networks, because these monitors are either deployed far away from dust active regions (most likely collocated with dense population or contaminated by anthropogenic sources and other natural sources, such as wildfires and vegetation detritus. Here we propose a new approach to identify local dust events relying solely on aerosol mass and composition from general-purpose aerosol measurements. Through analyzing the chemical and physical characteristics of aerosol observations during satellite-detected dust episodes, we select five indicators to be used to identify local dust records: (1 high PM10 concentrations; (2 low PM2.5/PM10 ratio; (3 higher concentrations and percentage of crustal elements; (4 lower percentage of anthropogenic pollutants; and (5 low enrichment factors of anthropogenic elements. After establishing these identification criteria, we conduct hierarchical cluster analysis for all validated aerosol measurement data over 68 IMPROVE sites in the Western United States. A total of 182 local dust events were identified over 30 of the 68 locations from 2000 to 2007. These locations are either close to the four US Deserts, namely the Great Basin Desert, the Mojave Desert, the Sonoran Desert, and the Chihuahuan Desert, or in the high wind power region (Colorado. During the eight-year study period, the total number of dust events displays an interesting four-year activity cycle (one in 2000–2003 and the other in 2004–2007. The years of 2003, 2002 and 2007 are the three most active dust periods, with 46, 31 and 24 recorded dust events, respectively, while the years of 2000, 2004 and 2005 are the calmest periods, all with single digit dust records. Among these deserts, the Chihuahua Desert (59 cases and the

  2. Are Time- and Event-based Prospective Memory Comparably Affected in HIV Infection?†

    Science.gov (United States)

    Zogg, Jennifer B.; Woods, Steven Paul; Weber, Erica; Doyle, Katie; Grant, Igor; Atkinson, J. Hampton; Ellis, Ronald J.; McCutchan, J. Allen; Marcotte, Thomas D.; Hale, Braden R.; Ellis, Ronald J.; McCutchan, J. Allen; Letendre, Scott; Capparelli, Edmund; Schrier, Rachel; Heaton, Robert K.; Cherner, Mariana; Moore, David J.; Jernigan, Terry; Fennema-Notestine, Christine; Archibald, Sarah L.; Hesselink, John; Annese, Jacopo; Taylor, Michael J.; Masliah, Eliezer; Everall, Ian; Langford, T. Dianne; Richman, Douglas; Smith, David M.; McCutchan, J. Allen; Everall, Ian; Lipton, Stuart; McCutchan, J. Allen; Atkinson, J. Hampton; Ellis, Ronald J.; Letendre, Scott; Atkinson, J. Hampton; von Jaeger, Rodney; Gamst, Anthony C.; Cushman, Clint; Masys, Daniel R.; Abramson, Ian; Ake, Christopher; Vaida, Florin

    2011-01-01

    According to the multi-process theory of prospective memory (ProM), time-based tasks rely more heavily on strategic processes dependent on prefrontal systems than do event-based tasks. Given the prominent frontostriatal pathophysiology of HIV infection, one would expect HIV-infected individuals to demonstrate greater deficits in time-based versus event-based ProM. However, the two prior studies examining this question have produced variable results. We evaluated this hypothesis in 143 individuals with HIV infection and 43 demographically similar seronegative adults (HIV−) who completed the research version of the Memory for Intentions Screening Test, which yields parallel subscales of time- and event-based ProM. Results showed main effects of HIV serostatus and cue type, but no interaction between serostatus and cue. Planned pair-wise comparisons showed a significant effect of HIV on time-based ProM and a trend-level effect on event-based ProM that was driven primarily by the subset of participants with HIV-associated neurocognitive disorders. Nevertheless, time-based ProM was more strongly correlated with measures of executive functions, attention/working memory, and verbal fluency in HIV-infected persons. Although HIV-associated deficits in time- and event-based ProM appear to be of comparable severity, the cognitive architecture of time-based ProM may be more strongly influenced by strategic monitoring and retrieval processes. PMID:21459901

  3. 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...

  4. 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.

  5. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  6. 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....

  7. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

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

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  8. Gene-Set Local Hierarchical Clustering (GSLHC--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.

    Directory of Open Access Journals (Sweden)

    Feng-Hsiang Chung

    Full Text Available Gene-set-based analysis (GSA, which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA, which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap, an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap, in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.

  9. Efficiency of Event-Based Sampling According to Error Energy Criterion

    OpenAIRE

    Marek Miskowicz

    2010-01-01

    The paper belongs to the studies that deal with the effectiveness of the particular event-based sampling scheme compared to the conventional periodic sampling as a reference. In the present study, the event-based sampling according to a constant energy of sampling error is analyzed. This criterion is suitable for applications where the energy of sampling error should be bounded (i.e., in building automation, or in greenhouse climate monitoring and control). Compared to the integral sampling c...

  10. Automatic Distribution Network Reconfiguration: An Event-Driven Approach

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Fei; Jiang, Huaiguang; Tan, Jin

    2016-11-14

    This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observable and detectable.

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

    Science.gov (United States)

    Aksoy, Ozan; Weesie, Jeroen

    2014-05-01

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

  12. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-12-14

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

  15. THE EFFECT OF DEVOTEE-BASED BRAND EQUITY ON RELIGIOUS EVENTS

    Directory of Open Access Journals (Sweden)

    MUHAMMAD JAWAD IQBAL

    2016-04-01

    Full Text Available The objective of this research is to apply DBBE model to discover the constructs to measure the religious event as a business brand on the bases of devotees’ perception. SEM technique was applied to measure the hypothesized model of which CFA put to analyze the model and a theoretical model was made to measure the model fit. Sample size was of 500. The base of brand loyalty was affected directly by image and quality. This information might be beneficial to event management and sponsors in making brand and operating visitors’ destinations. More importantly, the brand of these religious events in Pakistan can be built as a strong tourism product.

  16. A semi-supervised learning framework for biomedical event extraction based on hidden topics.

    Science.gov (United States)

    Zhou, Deyu; Zhong, Dayou

    2015-05-01

    Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely

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

    Science.gov (United States)

    Bucur, Amelia

    2015-09-01

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

  18. 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.

  19. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  20. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.