OBSERVATIONS OF HIERARCHICAL SOLAR-TYPE MULTIPLE STAR SYSTEMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roberts, Lewis C. Jr.; Tokovinin, Andrei; Mason, Brian D.
2015-10-15
Twenty multiple stellar systems with solar-type primaries were observed at high angular resolution using the PALM-3000 adaptive optics system at the 5 m Hale telescope. The goal was to complement the knowledge of hierarchical multiplicity in the solar neighborhood by confirming recent discoveries by the visible Robo-AO system with new near-infrared observations with PALM-3000. The physical status of most, but not all, of the new pairs is confirmed by photometry in the Ks band and new positional measurements. In addition, we resolved for the first time five close sub-systems: the known astrometric binary in HIP 17129AB, companions to the primariesmore » of HIP 33555, and HIP 118213, and the companions to the secondaries in HIP 25300 and HIP 101430. We place the components on a color–magnitude diagram and discuss each multiple system individually.« less
Hierarchical screening for multiple mental disorders.
Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J
2013-10-01
There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.
Hierarchical group testing for multiple infections.
Hou, Peijie; Tebbs, Joshua M; Bilder, Christopher R; McMahan, Christopher S
2017-06-01
Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11% reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. © 2016, The International Biometric Society.
Hierarchical group testing for multiple infections
Hou, Peijie; Tebbs, Joshua M.; Bilder, Christopher R.; McMahan, Christopher S.
2016-01-01
Summary Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11 percent reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. PMID:27657666
NASA Astrophysics Data System (ADS)
Hamers, Adrian S.
2018-05-01
We extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the long-term secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy, provided that the system is composed of nested binary orbits. To model secular encounters, we expand the Hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system, to the separation of the widest orbit. Subsequently, we integrate over the perturber orbit numerically or analytically. We verify our method for secular encounters and illustrate it with an example. Furthermore, we describe a method to compute instantaneous orbital changes to multiple systems, such as asymmetric supernovae and impulsive encounters. The secular code, with implementation of the extensions described in this paper, is publicly available within AMUSE, and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters and asymmetric supernovae. The extensions presented in this paper are a next step towards efficiently modelling the evolution of complex multiple systems embedded in star clusters.
Lee, Yoon Ho; Lee, Tae Kyung; Kim, Hongki; Song, Inho; Lee, Jiwon; Kang, Saewon; Ko, Hyunhyub; Kwak, Sang Kyu; Oh, Joon Hak
2018-03-01
In insect eyes, ommatidia with hierarchical structured cornea play a critical role in amplifying and transferring visual signals to the brain through optic nerves, enabling the perception of various visual signals. Here, inspired by the structure and functions of insect ommatidia, a flexible photoimaging device is reported that can simultaneously detect and record incoming photonic signals by vertically stacking an organic photodiode and resistive memory device. A single-layered, hierarchical multiple-patterned back reflector that can exhibit various plasmonic effects is incorporated into the organic photodiode. The multiple-patterned flexible organic photodiodes exhibit greatly enhanced photoresponsivity due to the increased light absorption in comparison with the flat systems. Moreover, the flexible photoimaging device shows a well-resolved spatiotemporal mapping of optical signals with excellent operational and mechanical stabilities at low driving voltages below half of the flat systems. Theoretical calculation and scanning near-field optical microscopy analyses clearly reveal that multiple-patterned electrodes have much stronger surface plasmon coupling than flat and single-patterned systems. The developed methodology provides a versatile and effective route for realizing high-performance optoelectronic and photonic systems. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Clinical time series prediction: towards a hierarchical dynamical system framework
Liu, Zitao; Hauskrecht, Milos
2014-01-01
Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive
Clinical time series prediction: Toward a hierarchical dynamical system framework.
Liu, Zitao; Hauskrecht, Milos
2015-09-01
Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.
Hierarchical graphs for rule-based modeling of biochemical systems
2011-01-01
Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal) of an edge represents a class of association (dissociation) reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR) complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for specifying rule-based models
MX Hierarchical Networking System.
1982-02-01
criteria considered in this report are defined as follows: 1. Single Network Limitation. Will the scheme allow the maximum size network anticipated to be...AD-AI16 758 CONSTRUCTION ENGINEERING RESEARCH LAB (ARMY) CHAMPAIGN IL F/G 5/2 MX HIERARCHICAL NETWORKING SYSTEM.(U) FEB 82 M O-CONNOR, L M SOLISH, L...laboratory__ _ _ _ _ _ _ _ _ _ _ _ MX HIERARCHICAL NETWORKING SYSTEM by Michael O’Connor L. Michael Golish Lee Boyer IsI Approved for public
Hierarchical structure of biological systems
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
Analysis hierarchical model for discrete event systems
NASA Astrophysics Data System (ADS)
Ciortea, E. M.
2015-11-01
The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.
Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems
NASA Technical Reports Server (NTRS)
Koch, Patrick N.
1997-01-01
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for
Hilgetag, C C; O'Neill, M A; Young, M P
2000-01-29
subdivision of FST into two distinct areas, whose connectivity we predict, and the abolition of at least one of the less reliable rule constraints. Our analyses showed that the future collection of the same type of laminar constraints, or the inclusion of new hierarchical constraints from thalamocortical connections, will not resolve the problem of multiple optimal hierarchical representations for the primate visual system. Further data, however, may help to specify the relative ordering of some more areas. This indeterminacy of the visual hierarchy is in part due to the reported absence of some connections between cortical areas. These absences are consistent with limited cross-talk between differentiated processing streams in the system. Hence, hierarchical representation of the visual system is affected by, and must take into account, other organizational features, such as processing streams.
ERIC Educational Resources Information Center
Choi, Kilchan
2011-01-01
This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…
Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems
NASA Astrophysics Data System (ADS)
Koch, Patrick Nathan
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.
Modeling urban air pollution with optimized hierarchical fuzzy inference system.
Tashayo, Behnam; Alimohammadi, Abbas
2016-10-01
Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.
2012-01-01
Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html. PMID:22531049
DISTURBANCE PATTERNS IN A SOCIO-ECOLOGICAL SYSTEM AT MULTIPLE SCALES
Ecological systems with hierarchical organization and non-equilibrium dynamics require multiple-scale analyses to comprehend how a system is structured and to formulate hypotheses about regulatory mechanisms. Characteristic scales in real landscapes are determined by, or at least...
Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.
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.
Xiao, Fuyuan; Aritsugi, Masayoshi; Wang, Qing; Zhang, Rong
2016-09-01
For efficient and sophisticated analysis of complex event patterns that appear in streams of big data from health care information systems and support for decision-making, a triaxial hierarchical model is proposed in this paper. Our triaxial hierarchical model is developed by focusing on hierarchies among nested event pattern queries with an event concept hierarchy, thereby allowing us to identify the relationships among the expressions and sub-expressions of the queries extensively. We devise a cost-based heuristic by means of the triaxial hierarchical model to find an optimised query execution plan in terms of the costs of both the operators and the communications between them. According to the triaxial hierarchical model, we can also calculate how to reuse the results of the common sub-expressions in multiple queries. By integrating the optimised query execution plan with the reuse schemes, a multi-query optimisation strategy is developed to accomplish efficient processing of multiple nested event pattern queries. We present empirical studies in which the performance of multi-query optimisation strategy was examined under various stream input rates and workloads. Specifically, the workloads of pattern queries can be used for supporting monitoring patients' conditions. On the other hand, experiments with varying input rates of streams can correspond to changes of the numbers of patients that a system should manage, whereas burst input rates can correspond to changes of rushes of patients to be taken care of. The experimental results have shown that, in Workload 1, our proposal can improve about 4 and 2 times throughput comparing with the relative works, respectively; in Workload 2, our proposal can improve about 3 and 2 times throughput comparing with the relative works, respectively; in Workload 3, our proposal can improve about 6 times throughput comparing with the relative work. The experimental results demonstrated that our proposal was able to process
Gray, B.R.; Haro, R.J.; Rogala, J.T.; Sauer, J.S.
2005-01-01
1. Macroinvertebrate count data often exhibit nested or hierarchical structure. Examples include multiple measurements along each of a set of streams, and multiple synoptic measurements from each of a set of ponds. With data exhibiting hierarchical structure, outcomes at both sampling (e.g. Within stream) and aggregated (e.g. Stream) scales are often of interest. Unfortunately, methods for modelling hierarchical count data have received little attention in the ecological literature. 2. We demonstrate the use of hierarchical count models using fingernail clam (Family: Sphaeriidae) count data and habitat predictors derived from sampling and aggregated spatial scales. The sampling scale corresponded to that of a standard Ponar grab (0.052 m(2)) and the aggregated scale to impounded and backwater regions within 38-197 km reaches of the Upper Mississippi River. Impounded and backwater regions were resampled annually for 10 years. Consequently, measurements on clams were nested within years. Counts were treated as negative binomial random variates, and means from each resampling event as random departures from the impounded and backwater region grand means. 3. Clam models were improved by the addition of covariates that varied at both the sampling and regional scales. Substrate composition varied at the sampling scale and was associated with model improvements, and reductions (for a given mean) in variance at the sampling scale. Inorganic suspended solids (ISS) levels, measured in the summer preceding sampling, also yielded model improvements and were associated with reductions in variances at the regional rather than sampling scales. ISS levels were negatively associated with mean clam counts. 4. Hierarchical models allow hierarchically structured data to be modelled without ignoring information specific to levels of the hierarchy. In addition, information at each hierarchical level may be modelled as functions of covariates that themselves vary by and within levels. As
A hierarchical-multiobjective framework for risk management
NASA Technical Reports Server (NTRS)
Haimes, Yacov Y.; Li, Duan
1991-01-01
A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.
Disturbance patterns in a socio-ecological system at multiple scales
G. Zurlini; Kurt H. Riitters; N. Zaccarelli; I. Petrosillo; K.B. Jones; L. Rossi
2006-01-01
Ecological systems with hierarchical organization and non-equilibrium dynamics require multiple-scale analyses to comprehend how a system is structured and to formulate hypotheses about regulatory mechanisms. Characteristic scales in real landscapes are determined by, or at least reflect, the spatial patterns and scales of constraining human interactions with the...
Hierarchical structure of biological systems: a bioengineering approach.
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.
NASA Astrophysics Data System (ADS)
Chao, Woodrew; Ho, Bruce K. T.; Chao, John T.; Sadri, Reza M.; Huang, Lu J.; Taira, Ricky K.
1995-05-01
Our tele-medicine/PACS archive system is based on a three-tier distributed hierarchical architecture, including magnetic disk farms, optical jukebox, and tape jukebox sub-systems. The hierarchical storage management (HSM) architecture, built around a low cost high performance platform [personal computers (PC) and Microsoft Windows NT], presents a very scaleable and distributed solution ideal for meeting the needs of client/server environments such as tele-medicine, tele-radiology, and PACS. These image based systems typically require storage capacities mirroring those of film based technology (multi-terabyte with 10+ years storage) and patient data retrieval times at near on-line performance as demanded by radiologists. With the scaleable architecture, storage requirements can be easily configured to meet the needs of the small clinic (multi-gigabyte) to those of a major hospital (multi-terabyte). The patient data retrieval performance requirement was achieved by employing system intelligence to manage migration and caching of archived data. Relevant information from HIS/RIS triggers prefetching of data whenever possible based on simple rules. System intelligence embedded in the migration manger allows the clustering of patient data onto a single tape during data migration from optical to tape medium. Clustering of patient data on the same tape eliminates multiple tape loading and associated seek time during patient data retrieval. Optimal tape performance can then be achieved by utilizing the tape drives high performance data streaming capabilities thereby reducing typical data retrieval delays associated with streaming tape devices.
Zhou, Weizheng; Tong, Gangsheng; Wang, Dali; Zhu, Bangshang; Ren, Yu; Butler, Michael; Pelan, Eddie; Yan, Deyue; Zhu, Xinyuan; Stoyanov, Simeon D
2016-04-06
Hierarchical porous structures are ubiquitous in biological organisms and inorganic systems. Although such structures have been replicated, designed, and fabricated, they are often inferior to naturally occurring analogues. Apart from the complexity and multiple functionalities developed by the biological systems, the controllable and scalable production of hierarchically porous structures and building blocks remains a technological challenge. Herein, a facile and scalable approach is developed to fabricate hierarchical hollow spheres with integrated micro-, meso-, and macropores ranging from 1 nm to 100 μm (spanning five orders of magnitude). (Macro)molecules, micro-rods (which play a key role for the creation of robust capsules), and emulsion droplets have been successfully employed as multiple length scale templates, allowing the creation of hierarchical porous macrospheres. Thanks to their specific mechanical strength, these hierarchical porous spheres could be incorporated and assembled as higher level building blocks in various novel materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Sato, Naoyuki; Yamaguchi, Yoko
2009-06-01
The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.
Brough, David B; Wheeler, Daniel; Kalidindi, Surya R
2017-03-01
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.
Brough, David B; Wheeler, Daniel; Kalidindi, Surya R.
2017-01-01
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers. PMID:28690971
NASA Astrophysics Data System (ADS)
Liang, Dong; Song, Yimin; Sun, Tao; Jin, Xueying
2018-03-01
This paper addresses the problem of rigid-flexible coupling dynamic modeling and active control of a novel flexible parallel manipulator (PM) with multiple actuation modes. Firstly, based on the flexible multi-body dynamics theory, the rigid-flexible coupling dynamic model (RFDM) of system is developed by virtue of the augmented Lagrangian multipliers approach. For completeness, the mathematical models of permanent magnet synchronous motor (PMSM) and piezoelectric transducer (PZT) are further established and integrated with the RFDM of mechanical system to formulate the electromechanical coupling dynamic model (ECDM). To achieve the trajectory tracking and vibration suppression, a hierarchical compound control strategy is presented. Within this control strategy, the proportional-differential (PD) feedback controller is employed to realize the trajectory tracking of end-effector, while the strain and strain rate feedback (SSRF) controller is developed to restrain the vibration of the flexible links using PZT. Furthermore, the stability of the control algorithm is demonstrated based on the Lyapunov stability theory. Finally, two simulation case studies are performed to illustrate the effectiveness of the proposed approach. The results indicate that, under the redundant actuation mode, the hierarchical compound control strategy can guarantee the flexible PM achieves singularity-free motion and vibration attenuation within task workspace simultaneously. The systematic methodology proposed in this study can be conveniently extended for the dynamic modeling and efficient controller design of other flexible PMs, especially the emerging ones with multiple actuation modes.
A self-defining hierarchical data system
NASA Technical Reports Server (NTRS)
Bailey, J.
1992-01-01
The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.
Continued Kinematic and Photometric Investigations of Hierarchical Solar-type Multiple Star Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roberts, Lewis C. Jr.; Marinan, Anne D.; Tokovinin, Andrei
2017-03-01
We observed 15 of the solar-type binaries within 67 pc of the Sun previously observed by the Robo-AO system in the visible, with the PHARO near-infrared camera and the PALM-3000 adaptive optics system on the 5 m Hale telescope. The physical status of the binaries is confirmed through common proper motion and detection of orbital motion. In the process, we detected a new candidate companion to HIP 95309. We also resolved the primary of HIP 110626 into a close binary, making that system a triple. These detections increase the completeness of the multiplicity survey of the solar-type stars within 67more » pc of the Sun. Combining our observations of HIP 103455 with archival astrometric measurements and RV measurements, we are able to compute the first orbit of HIP 103455, showing that the binary has a 68 year period. We place the components on a color–magnitude diagram and discuss each multiple system individually.« less
Hierarchical storage management system evaluation
NASA Technical Reports Server (NTRS)
Woodrow, Thomas S.
1993-01-01
The Numerical Aerodynamic Simulation (NAS) Program at NASA Ames Research Center has been developing a hierarchical storage management system, NAStore, for some 6 years. This evaluation compares functionality, performance, reliability, and other factors of NAStore and three commercial alternatives. FileServ is found to be slightly better overall than NAStore and DMF. UniTree is found to be severely lacking in comparison.
NASA Astrophysics Data System (ADS)
Marcy, G. W.; Fischer, D. A.; Butler, R. P.; Vogt, S. S.
To date, 10 stars are known which harbor two or three planets. These systems reveal secular and mean motion resonances in some systems and consist of widely separated, eccentric orbits in others. Both of the triple planet systems, namely Upsilon And and 55 Cancri, exhibit evidence of resonances. The two planets orbiting GJ 876 exhibit both mean-motion and secular resonances and they perturb each other so strongly that the evolution of the orbits is revealed in the Doppler measurements. The common occurrence of resonances suggests that delicate dynamical processes often shape the architecture of planetary systems. Likely processes include planet migration in a viscous disk, eccentricity pumping by the planet-disk interaction, and resonance capture of two planets. We find a class of "hierarchical" double-planet systems characterized by two planets in widely separated orbits, defined to have orbital period ratios greater than 5 to 1. In such systems, resonant interactions are weak, leaving high-order interactions and Kozai resonances plausibly important. We compare the planets that are single with those in multiple systems. We find that neither the two mass distributions nor the two eccentricity distributions are significantly different. This similarity in single and multiple systems suggests that similar dynamical processes may operate in both. The origin of eccentricities may stem from a multi-planet past or from interactions between planets and disk. Multiple planets in resonances can pump their eccentricities pumping resulting in one planet being ejected from the system or sent into the star, leaving a (more massive) single planet in an eccentric orbit. The distribution of semimajor axes of all known extrasolar planets shows a rise toward larger orbits, portending a population of gas-giant planets that reside beyond 3 AU, arguably in less perturbed, more circular orbits.
ERIC Educational Resources Information Center
Richter, Tobias
2006-01-01
Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…
Hierarchical drivers of reef-fish metacommunity structure.
MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P
2009-01-01
Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at
Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems
NASA Technical Reports Server (NTRS)
Yasar, Murat; Tolani, Devendra; Ray, Asok; Shah, Neerav; Litt, Jonathan S.
2004-01-01
This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.
Combining information from multiple flood projections in a hierarchical Bayesian framework
NASA Astrophysics Data System (ADS)
Le Vine, Nataliya
2016-04-01
This study demonstrates, in the context of flood frequency analysis, the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach explicitly accommodates shared multimodel discrepancy as well as the probabilistic nature of the flood estimates, and treats the available models as a sample from a hypothetical complete (but unobserved) set of models. The methodology is applied to flood estimates from multiple hydrological projections (the Future Flows Hydrology data set) for 135 catchments in the UK. The advantages of the approach are shown to be: (1) to ensure adequate "baseline" with which to compare future changes; (2) to reduce flood estimate uncertainty; (3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; (4) to diminish the importance of model consistency when model biases are large; and (5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.
Evaluating Hierarchical Structure in Music Annotations
McFee, Brian; Nieto, Oriol; Farbood, Morwaread M.; Bello, Juan Pablo
2017-01-01
Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement. PMID:28824514
Hierarchical algorithms for modeling the ocean on hierarchical architectures
NASA Astrophysics Data System (ADS)
Hill, C. N.
2012-12-01
This presentation will describe an approach to using accelerator/co-processor technology that maps hierarchical, multi-scale modeling techniques to an underlying hierarchical hardware architecture. The focus of this work is on making effective use of both CPU and accelerator/co-processor parts of a system, for large scale ocean modeling. In the work, a lower resolution basin scale ocean model is locally coupled to multiple, "embedded", limited area higher resolution sub-models. The higher resolution models execute on co-processor/accelerator hardware and do not interact directly with other sub-models. The lower resolution basin scale model executes on the system CPU(s). The result is a multi-scale algorithm that aligns with hardware designs in the co-processor/accelerator space. We demonstrate this approach being used to substitute explicit process models for standard parameterizations. Code for our sub-models is implemented through a generic abstraction layer, so that we can target multiple accelerator architectures with different programming environments. We will present two application and implementation examples. One uses the CUDA programming environment and targets GPU hardware. This example employs a simple non-hydrostatic two dimensional sub-model to represent vertical motion more accurately. The second example uses a highly threaded three-dimensional model at high resolution. This targets a MIC/Xeon Phi like environment and uses sub-models as a way to explicitly compute sub-mesoscale terms. In both cases the accelerator/co-processor capability provides extra compute cycles that allow improved model fidelity for little or no extra wall-clock time cost.
A Hierarchical Learning Control Framework for an Aerial Manipulation System
NASA Astrophysics Data System (ADS)
Ma, Le; Chi, yanxun; Li, Jiapeng; Li, Zhongsheng; Ding, Yalei; Liu, Lixing
2017-07-01
A hierarchical learning control framework for an aerial manipulation system is proposed. Firstly, the mechanical design of aerial manipulation system is introduced and analyzed, and the kinematics and the dynamics based on Newton-Euler equation are modeled. Secondly, the framework of hierarchical learning for this system is presented, in which flight platform and manipulator are controlled by different controller respectively. The RBF (Radial Basis Function) neural networks are employed to estimate parameters and control. The Simulation and experiment demonstrate that the methods proposed effective and advanced.
NASA Technical Reports Server (NTRS)
Wheatley, Thomas E.; Michaloski, John L.; Lumia, Ronald
1989-01-01
Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored.
Moisture effect on interfacial integrity of epoxy-bonded system: a hierarchical approach
NASA Astrophysics Data System (ADS)
Tam, Lik-ho; Lun Chow, Cheuk; Lau, Denvid
2018-01-01
The epoxy-bonded system has been widely used in various applications across different scale lengths. Prior investigations have indicated that the moisture-affected interfacial debonding is the major failure mode of such a system, but the fundamental mechanism remains unknown, such as the basis for the invasion of water molecules in the cross-linked epoxy and the epoxy-bonded interface. This prevents us from predicting the long-term performance of the epoxy-related applications under the effect of the moisture. Here, we use full atomistic models to investigate the response of the epoxy-bonded system towards the adhesion test, and provide a detailed analysis of the interfacial integrity under the moisture effect and the associated debonding mechanism. Molecular dynamics simulations show that water molecules affect the hierarchical structure of the epoxy-bonded system at the nanoscale by disrupting the film-substrate interaction and the molecular interaction within the epoxy, which leads to the detachment of the epoxy thin film, and the final interfacial debonding. The simulation results show good agreement with the experimental results of the epoxy-bonded system. Through identifying the relationship between the epoxy structure and the debonding mechanism at multiple scales, it is shown that the hierarchical structure of the epoxy-bonded system is crucial for the interfacial integrity. In particular, the available space of the epoxy-bonded system, which consists of various sizes ranging from the atomistic scale to the macroscale and is close to the interface facilitates the moisture accumulation, leading to a distinct interfacial debonding when compared to the dry scenario.
Maximum entropy approach to H -theory: Statistical mechanics of hierarchical systems
NASA Astrophysics Data System (ADS)
Vasconcelos, Giovani L.; Salazar, Domingos S. P.; Macêdo, A. M. S.
2018-02-01
A formalism, called H-theory, is applied to the problem of statistical equilibrium of a hierarchical complex system with multiple time and length scales. In this approach, the system is formally treated as being composed of a small subsystem—representing the region where the measurements are made—in contact with a set of "nested heat reservoirs" corresponding to the hierarchical structure of the system, where the temperatures of the reservoirs are allowed to fluctuate owing to the complex interactions between degrees of freedom at different scales. The probability distribution function (pdf) of the temperature of the reservoir at a given scale, conditioned on the temperature of the reservoir at the next largest scale in the hierarchy, is determined from a maximum entropy principle subject to appropriate constraints that describe the thermal equilibrium properties of the system. The marginal temperature distribution of the innermost reservoir is obtained by integrating over the conditional distributions of all larger scales, and the resulting pdf is written in analytical form in terms of certain special transcendental functions, known as the Fox H functions. The distribution of states of the small subsystem is then computed by averaging the quasiequilibrium Boltzmann distribution over the temperature of the innermost reservoir. This distribution can also be written in terms of H functions. The general family of distributions reported here recovers, as particular cases, the stationary distributions recently obtained by Macêdo et al. [Phys. Rev. E 95, 032315 (2017), 10.1103/PhysRevE.95.032315] from a stochastic dynamical approach to the problem.
Maximum entropy approach to H-theory: Statistical mechanics of hierarchical systems.
Vasconcelos, Giovani L; Salazar, Domingos S P; Macêdo, A M S
2018-02-01
A formalism, called H-theory, is applied to the problem of statistical equilibrium of a hierarchical complex system with multiple time and length scales. In this approach, the system is formally treated as being composed of a small subsystem-representing the region where the measurements are made-in contact with a set of "nested heat reservoirs" corresponding to the hierarchical structure of the system, where the temperatures of the reservoirs are allowed to fluctuate owing to the complex interactions between degrees of freedom at different scales. The probability distribution function (pdf) of the temperature of the reservoir at a given scale, conditioned on the temperature of the reservoir at the next largest scale in the hierarchy, is determined from a maximum entropy principle subject to appropriate constraints that describe the thermal equilibrium properties of the system. The marginal temperature distribution of the innermost reservoir is obtained by integrating over the conditional distributions of all larger scales, and the resulting pdf is written in analytical form in terms of certain special transcendental functions, known as the Fox H functions. The distribution of states of the small subsystem is then computed by averaging the quasiequilibrium Boltzmann distribution over the temperature of the innermost reservoir. This distribution can also be written in terms of H functions. The general family of distributions reported here recovers, as particular cases, the stationary distributions recently obtained by Macêdo et al. [Phys. Rev. E 95, 032315 (2017)10.1103/PhysRevE.95.032315] from a stochastic dynamical approach to the problem.
P2MP MPLS-Based Hierarchical Service Management System
NASA Astrophysics Data System (ADS)
Kumaki, Kenji; Nakagawa, Ikuo; Nagami, Kenichi; Ogishi, Tomohiko; Ano, Shigehiro
This paper proposes a point-to-multipoint (P2MP) Multi-Protocol Label Switching (MPLS) based hierarchical service management system. Traditionally, general management systems deployed in some service providers control MPLS Label Switched Paths (LSPs) (e.g., RSVP-TE and LDP) and services (e.g., L2VPN, L3VPN and IP) separately. In order for dedicated management systems for MPLS LSPs and services to cooperate with each other automatically, a hierarchical service management system has been proposed with the main focus on point-to-point (P2P) TE LSPs in MPLS path management. In the case where P2MP TE LSPs and services are deployed in MPLS networks, the dedicated management systems for P2MP TE LSPs and services must work together automatically. Therefore, this paper proposes a new algorithm that uses a correlation between P2MP TE LSPs and multicast VPN services based on a P2MP MPLS-based hierarchical service management architecture. Also, the capacity and performance of the proposed algorithm are evaluated by simulations, which are actually based on certain real MPLS production networks, and are compared to that of the algorithm for P2P TE LSPs. Results show this system is very scalable within real MPLS production networks. This system, with the automatic correlation, appears to be deployable in real MPLS production networks.
Hierarchical Modelling Of Mobile, Seeing Robots
NASA Astrophysics Data System (ADS)
Luh, Cheng-Jye; Zeigler, Bernard P.
1990-03-01
This paper describes the implementation of a hierarchical robot simulation which supports the design of robots with vision and mobility. A seeing robot applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.
Hierarchical modelling of mobile, seeing robots
NASA Technical Reports Server (NTRS)
Luh, Cheng-Jye; Zeigler, Bernard P.
1990-01-01
This paper describes the implementation of a hierarchical robot simulation which supports the design of robots with vision and mobility. A seeing robot applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.
We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of polic...
Swartz, Michael D; Cai, Yi; Chan, Wenyaw; Symanski, Elaine; Mitchell, Laura E; Danysh, Heather E; Langlois, Peter H; Lupo, Philip J
2015-02-09
While there is evidence that maternal exposure to benzene is associated with spina bifida in offspring, to our knowledge there have been no assessments to evaluate the role of multiple hazardous air pollutants (HAPs) simultaneously on the risk of this relatively common birth defect. In the current study, we evaluated the association between maternal exposure to HAPs identified by the United States Environmental Protection Agency (U.S. EPA) and spina bifida in offspring using hierarchical Bayesian modeling that includes Stochastic Search Variable Selection (SSVS). The Texas Birth Defects Registry provided data on spina bifida cases delivered between 1999 and 2004. The control group was a random sample of unaffected live births, frequency matched to cases on year of birth. Census tract-level estimates of annual HAP levels were obtained from the U.S. EPA's 1999 Assessment System for Population Exposure Nationwide. Using the distribution among controls, exposure was categorized as high exposure (>95(th) percentile), medium exposure (5(th)-95(th) percentile), and low exposure (<5(th) percentile, reference). We used hierarchical Bayesian logistic regression models with SSVS to evaluate the association between HAPs and spina bifida by computing an odds ratio (OR) for each HAP using the posterior mean, and a 95% credible interval (CI) using the 2.5(th) and 97.5(th) quantiles of the posterior samples. Based on previous assessments, any pollutant with a Bayes factor greater than 1 was selected for inclusion in a final model. Twenty-five HAPs were selected in the final analysis to represent "bins" of highly correlated HAPs (ρ > 0.80). We identified two out of 25 HAPs with a Bayes factor greater than 1: quinoline (ORhigh = 2.06, 95% CI: 1.11-3.87, Bayes factor = 1.01) and trichloroethylene (ORmedium = 2.00, 95% CI: 1.14-3.61, Bayes factor = 3.79). Overall there is evidence that quinoline and trichloroethylene may be significant contributors to the risk of spina bifida
Mansouri, Mohammad; Teshnehlab, Mohammad; Aliyari Shoorehdeli, Mahdi
2015-05-01
In this paper, a novel adaptive hierarchical fuzzy control system based on the variable structure control is developed for a class of SISO canonical nonlinear systems in the presence of bounded disturbances. It is assumed that nonlinear functions of the systems be completely unknown. Switching surfaces are incorporated into the hierarchical fuzzy control scheme to ensure the system stability. A fuzzy soft switching system decides the operation area of the hierarchical fuzzy control and variable structure control systems. All the nonlinearly appeared parameters of conclusion parts of fuzzy blocks located in different layers of the hierarchical fuzzy control system are adjusted through adaptation laws deduced from the defined Lyapunov function. The proposed hierarchical fuzzy control system reduces the number of rules and consequently the number of tunable parameters with respect to the ordinary fuzzy control system. Global boundedness of the overall adaptive system and the desired precision are achieved using the proposed adaptive control system. In this study, an adaptive hierarchical fuzzy system is used for two objectives; it can be as a function approximator or a control system based on an intelligent-classic approach. Three theorems are proven to investigate the stability of the nonlinear dynamic systems. The important point about the proposed theorems is that they can be applied not only to hierarchical fuzzy controllers with different structures of hierarchical fuzzy controller, but also to ordinary fuzzy controllers. Therefore, the proposed algorithm is more general. To show the effectiveness of the proposed method four systems (two mechanical, one mathematical and one chaotic) are considered in simulations. Simulation results demonstrate the validity, efficiency and feasibility of the proposed approach to control of nonlinear dynamic systems. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Hierarchical Address Event Routing for Reconfigurable Large-Scale Neuromorphic Systems.
Park, Jongkil; Yu, Theodore; Joshi, Siddharth; Maier, Christoph; Cauwenberghs, Gert
2017-10-01
We present a hierarchical address-event routing (HiAER) architecture for scalable communication of neural and synaptic spike events between neuromorphic processors, implemented with five Xilinx Spartan-6 field-programmable gate arrays and four custom analog neuromophic integrated circuits serving 262k neurons and 262M synapses. The architecture extends the single-bus address-event representation protocol to a hierarchy of multiple nested buses, routing events across increasing scales of spatial distance. The HiAER protocol provides individually programmable axonal delay in addition to strength for each synapse, lending itself toward biologically plausible neural network architectures, and scales across a range of hierarchies suitable for multichip and multiboard systems in reconfigurable large-scale neuromorphic systems. We show approximately linear scaling of net global synaptic event throughput with number of routing nodes in the network, at 3.6×10 7 synaptic events per second per 16k-neuron node in the hierarchy.
A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis
NASA Technical Reports Server (NTRS)
Gossman, W. E.
1986-01-01
A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.
Risk transfer modeling among hierarchically associated stakeholders in development of space systems
NASA Astrophysics Data System (ADS)
Henkle, Thomas Grove, III
reasonably exceed multiple tens of $millions per space project. Additional results indicate that current US government statutory arrangements on risk sharing with underwriting entities appears reasonable with respect to stated objectives. This research combines aspects of multiple disciplines to include risk management, decision theory, utility theory, and systems architecting. It also demonstrates development of a more general theory on prescribing risk transfer criteria between distinct, but hierarchically associated entities involved in complex system development with applicability to a variety of technical domains.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hummel, K.E.
1987-12-01
Expert systems are artificial intelligence programs that solve problems requiring large amounts of heuristic knowledge, based on years of experience and tradition. Production systems are domain-independent tools that support the development of rule-based expert systems. This document describes a general purpose production system known as HERB. This system was developed to support the programming of expert systems using hierarchically structured rule bases. HERB encourages the partitioning of rules into multiple rule bases and supports the use of multiple conflict resolution strategies. Multiple rule bases can also be placed on a system stack and simultaneously searched during each interpreter cycle. Bothmore » backward and forward chaining rules are supported by HERB. The condition portion of each rule can contain both patterns, which are matched with facts in a data base, and LISP expressions, which are explicitly evaluated in the LISP environment. Properties of objects can also be stored in the HERB data base and referenced within the scope of each rule. This document serves both as an introduction to the principles of LISP-based production systems and as a user's manual for the HERB system. 6 refs., 17 figs.« less
A hierarchically distributed architecture for fault isolation expert systems on the space station
NASA Technical Reports Server (NTRS)
Miksell, Steve; Coffer, Sue
1987-01-01
The Space Station Axiomatic Fault Isolating Expert Systems (SAFTIES) system deals with the hierarchical distribution of control and knowledge among independent expert systems doing fault isolation and scheduling of Space Station subsystems. On its lower level, fault isolation is performed on individual subsystems. These fault isolation expert systems contain knowledge about the performance requirements of their particular subsystem and corrective procedures which may be involved in repsonse to certain performance errors. They can control the functions of equipment in their system and coordinate system task schedules. On a higher level, the Executive contains knowledge of all resources, task schedules for all systems, and the relative priority of all resources and tasks. The executive can override any subsystem task schedule in order to resolve use conflicts or resolve errors that require resources from multiple subsystems. Interprocessor communication is implemented using the SAFTIES Communications Interface (SCI). The SCI is an application layer protocol which supports the SAFTIES distributed multi-level architecture.
NASA Astrophysics Data System (ADS)
Montillo, Albert; Song, Qi; Das, Bipul; Yin, Zhye
2015-03-01
Parsing volumetric computed tomography (CT) into 10 or more salient organs simultaneously is a challenging task with many applications such as personalized scan planning and dose reporting. In the clinic, pre-scan data can come in the form of very low dose volumes acquired just prior to the primary scan or from an existing primary scan. To localize organs in such diverse data, we propose a new learning based framework that we call hierarchical pictorial structures (HPS) which builds multiple levels of models in a tree-like hierarchy that mirrors the natural decomposition of human anatomy from gross structures to finer structures. Each node of our hierarchical model learns (1) the local appearance and shape of structures, and (2) a generative global model that learns probabilistic, structural arrangement. Our main contribution is twofold. First we embed the pictorial structures approach in a hierarchical framework which reduces test time image interpretation and allows for the incorporation of additional geometric constraints that robustly guide model fitting in the presence of noise. Second we guide our HPS framework with the probabilistic cost maps extracted using random decision forests using volumetric 3D HOG features which makes our model fast to train and fast to apply to novel test data and posses a high degree of invariance to shape distortion and imaging artifacts. All steps require approximate 3 mins to compute and all organs are located with suitably high accuracy for our clinical applications such as personalized scan planning for radiation dose reduction. We assess our method using a database of volumetric CT scans from 81 subjects with widely varying age and pathology and with simulated ultra-low dose cadaver pre-scan data.
Organization of excitable dynamics in hierarchical biological networks.
Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten
2008-09-26
This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.
Scale of association: hierarchical linear models and the measurement of ecological systems
Sean M. McMahon; Jeffrey M. Diez
2007-01-01
A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...
Shishir, Sharmin; Tsuyuzaki, Shiro
2018-05-11
Detecting fine-scale spatiotemporal land use changes is a prerequisite for understanding and predicting the effects of urbanization and its related human impacts on the ecosystem. Land use changes are frequently examined using vegetation indices (VIs), although the validation of these indices has not been conducted at a high resolution. Therefore, a hierarchical classification was constructed to obtain accurate land use types at a fine scale. The characteristics of four popular VIs were investigated prior to examining the hierarchical classification by using Purbachal New Town, Bangladesh, which exhibits ongoing urbanization. These four VIs are the normalized difference VI (NDVI), green-red VI (GRVI), enhanced VI (EVI), and two-band EVI (EVI2). The reflectance data were obtained by the IKONOS (0.8-m resolution) and WorldView-2 sensor (0.5-m resolution) in 2001 and 2015, respectively. The hierarchical classification of land use types was constructed using a decision tree (DT) utilizing all four of the examined VIs. The accuracy of the classification was evaluated using ground truth data with multiple comparisons and kappa (κ) coefficients. The DT showed overall accuracies of 96.1 and 97.8% in 2001 and 2015, respectively, while the accuracies of the VIs were less than 91.2%. These results indicate that each VI exhibits unique advantages. In addition, the DT was the best classifier of land use types, particularly for native ecosystems represented by Shorea forests and homestead vegetation, at the fine scale. Since the conservation of these native ecosystems is of prime importance, DTs based on hierarchical classifications should be used more widely.
Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems
2004-11-01
Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University, University Park, Pennsylvania Neerav Shah Glenn Research Center...Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University...Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University University Park, Pennsylvania 16802 Neerav Shah National
Brely, Lucas; Bosia, Federico; Pugno, Nicola M
2018-06-20
Contact unit size reduction is a widely studied mechanism as a means to improve adhesion in natural fibrillar systems, such as those observed in beetles or geckos. However, these animals also display complex structural features in the way the contact is subdivided in a hierarchical manner. Here, we study the influence of hierarchical fibrillar architectures on the load distribution over the contact elements of the adhesive system, and the corresponding delamination behaviour. We present an analytical model to derive the load distribution in a fibrillar system loaded in shear, including hierarchical splitting of contacts, i.e. a "hierarchical shear-lag" model that generalizes the well-known shear-lag model used in mechanics. The influence on the detachment process is investigated introducing a numerical procedure that allows the derivation of the maximum delamination force as a function of the considered geometry, including statistical variability of local adhesive energy. Our study suggests that contact splitting generates improved adhesion only in the ideal case of extremely compliant contacts. In real cases, to produce efficient adhesive performance, contact splitting needs to be coupled with hierarchical architectures to counterbalance high load concentrations resulting from contact unit size reduction, generating multiple delamination fronts and helping to avoid detrimental non-uniform load distributions. We show that these results can be summarized in a generalized adhesion scaling scheme for hierarchical structures, proving the beneficial effect of multiple hierarchical levels. The model can thus be used to predict the adhesive performance of hierarchical adhesive structures, as well as the mechanical behaviour of composite materials with hierarchical reinforcements.
Turkson, Anthony Joe; Otchey, James Eric
2015-01-14
Various psychosocial studies on health related lifestyles lay emphasis on the fact that the perception one has of himself as being at risk of HIV/AIDS infection was a necessary condition for preventive behaviors to be adopted. Hierarchical Multiple Regression models was used to examine the relationship between eight independent variables and one dependent variable to isolate predictors which have significant influence on behavior and sexual practices. A Cross-sectional design was used for the study. Structured close-ended interviewer-administered questionnaire was used to collect primary data. Multistage stratified technique was used to sample views from 380 students from Takoradi Polytechnic, Ghana. A Hierarchical multiple regression model was used to ascertain the significance of certain predictors of sexual behavior and practices. The variables that were extracted from the multiple regression were; for the constant; Beta=14.202, t=2.279, p=0.023, variable is significant; for the marital status; Beta=0.092, t=1.996, p<0.05, variable is significant; for the knowledge on AIDs; Beta=0.090, t=1.996, p<0.05, variable is significant; for the attitude towards HIV/AIDs; =0.486, t=10.575, p<0.001, variable is highly significant. Thus, the best fitting model for predicting behavior and sexual practices was a linear combination of the constant, one's marital status, knowledge on HIV/AIDs and Attitude towards HIV/AIDs., Y(Behavior and sexual practies)= Beta0+Beta1(Marital status)+Beta2(Knowledge on HIV/AIDs issues)+Beta3(Attitude towards HIV/AIDs issues) Beta0, Beta1, Beta2 and Beta3 are respectively 14.201, 2.038, 0.148 and 0.486; the higher the better. Attitude and behavior change education on HIV/AIDs should be intensified in the institution so that students could adopt better lifestyles.
Hierarchical Ensemble Methods for Protein Function Prediction
2014-01-01
Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954
Shih, Arthur Chun-Chieh; Lee, DT; Peng, Chin-Lin; Wu, Yu-Wei
2007-01-01
Background When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences. Results A multiple-logo alignment visualization tool, called Phylo-mLogo, is presented in this paper. Phylo-mLogo calculates the variabilities and homogeneities of alignment sequences by base frequencies or entropies. Different from the traditional representations of sequence logos, Phylo-mLogo not only displays the global logo patterns of the whole alignment of multiple sequences, but also demonstrates their local homologous logos for each clade hierarchically. In addition, Phylo-mLogo also allows the user to focus only on the analysis of some important, structurally or functionally constrained sites in the alignment selected by the user or by built-in automatic calculation. Conclusion With Phylo-mLogo, the user can symbolically and hierarchically visualize hundreds of aligned sequences simultaneously and easily check the changes of their amino acid sites when analyzing many homologous/orthologous or influenza virus sequences. More information of Phylo-mLogo can be found at URL . PMID:17319966
NASA Technical Reports Server (NTRS)
Caines, P. E.
1999-01-01
The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.
Control of discrete event systems modeled as hierarchical state machines
NASA Technical Reports Server (NTRS)
Brave, Y.; Heymann, M.
1991-01-01
The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.
Statistical Significance for Hierarchical Clustering
Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.
2017-01-01
Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990
Chen, Xuemei; Patel, Ravi S.; Weibel, Justin A.; Garimella, Suresh V.
2016-01-01
Coalescence-induced jumping of condensate droplets from a superhydrophobic surface with hierarchical micro/nanoscale roughness is quantitatively characterized. Experimental observations show that the condensate droplet jumping is induced by coalescence of multiple droplets of different sizes, and that the coalesced droplet trajectories typically deviate from the surface normal. A depth-from-defocus image processing technique is developed to track the out-of-plane displacement of the jumping droplets, so as to accurately measure the droplet size and velocity. The results demonstrate that the highest jumping velocity is achieved when two droplets coalesce. The jumping velocity decreases gradually with an increase in the number of coalescing droplets, despite the greater potential surface energy released upon coalescence. A general theoretical model that accounts for viscous dissipation, surface adhesion, line tension, the initial droplet wetting states, and the number and sizes of the coalescing droplets is developed to explain the trends of droplet jumping velocity observed in the experiments. PMID:26725512
Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.
2011-01-01
Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.
HAL: a hierarchical format for storing and analyzing multiple genome alignments.
Hickey, Glenn; Paten, Benedict; Earl, Dent; Zerbino, Daniel; Haussler, David
2013-05-15
Large multiple genome alignments and inferred ancestral genomes are ideal resources for comparative studies of molecular evolution, and advances in sequencing and computing technology are making them increasingly obtainable. These structures can provide a rich understanding of the genetic relationships between all subsets of species they contain. Current formats for storing genomic alignments, such as XMFA and MAF, are all indexed or ordered using a single reference genome, however, which limits the information that can be queried with respect to other species and clades. This loss of information grows with the number of species under comparison, as well as their phylogenetic distance. We present HAL, a compressed, graph-based hierarchical alignment format for storing multiple genome alignments and ancestral reconstructions. HAL graphs are indexed on all genomes they contain. Furthermore, they are organized phylogenetically, which allows for modular and parallel access to arbitrary subclades without fragmentation because of rearrangements that have occurred in other lineages. HAL graphs can be created or read with a comprehensive C++ API. A set of tools is also provided to perform basic operations, such as importing and exporting data, identifying mutations and coordinate mapping (liftover). All documentation and source code for the HAL API and tools are freely available at http://github.com/glennhickey/hal. hickey@soe.ucsc.edu or haussler@soe.ucsc.edu Supplementary data are available at Bioinformatics online.
2017-01-01
China is setting up a hierarchical medical system to solve the problems of biased resource allocation and high patient flows to large hospitals. The development of big data and mobile Internet technology provides a new perspective for the establishment of hierarchical medical system. This viewpoint discusses the challenges with the hierarchical medical system in China and how big data and mobile Internet can be used to mitigate these challenges. PMID:28790024
An hierarchical approach to performance evaluation of expert systems
NASA Technical Reports Server (NTRS)
Dominick, Wayne D. (Editor); Kavi, Srinu
1985-01-01
The number and size of expert systems is growing rapidly. Formal evaluation of these systems - which is not performed for many systems - increases the acceptability by the user community and hence their success. Hierarchical evaluation that had been conducted for computer systems is applied for expert system performance evaluation. Expert systems are also evaluated by treating them as software systems (or programs). This paper reports many of the basic concepts and ideas in the Performance Evaluation of Expert Systems Study being conducted at the University of Southwestern Louisiana.
Hierarchically Nanostructured Materials for Sustainable Environmental Applications
NASA Astrophysics Data System (ADS)
Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian
2013-11-01
This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.
Defining and Enabling Resiliency of Electric Distribution Systems With Multiple Microgrids
Chanda, Sayonsom; Srivastava, Anurag K.
2016-05-02
This paper presents a method for quantifying and enabling the resiliency of a power distribution system (PDS) using analytical hierarchical process and percolation theory. Using this metric, quantitative analysis can be done to analyze the impact of possible control decisions to pro-actively enable the resilient operation of distribution system with multiple microgrids and other resources. Developed resiliency metric can also be used in short term distribution system planning. The benefits of being able to quantify resiliency can help distribution system planning engineers and operators to justify control actions, compare different reconfiguration algorithms, develop proactive control actions to avert power systemmore » outage due to impending catastrophic weather situations or other adverse events. Validation of the proposed method is done using modified CERTS microgrids and a modified industrial distribution system. Furthermore, simulation results show topological and composite metric considering power system characteristics to quantify the resiliency of a distribution system with the proposed methodology, and improvements in resiliency using two-stage reconfiguration algorithm and multiple microgrids.« less
Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures
NASA Astrophysics Data System (ADS)
Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.
2017-05-01
In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.
Image Information Mining Utilizing Hierarchical Segmentation
NASA Technical Reports Server (NTRS)
Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai
2002-01-01
The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.
Hierarchical Management Information Systems: A Decentralized Approach for University Administration
ERIC Educational Resources Information Center
Wager, J. James
1977-01-01
A Hierarchical Management Information System (HMIS) provides decision-making as well as operational information to all groups of the institution in a timely and predictable manner. Its operational aspects and benefits are discussed. (Author/LBH)
Non-Archimedean reaction-ultradiffusion equations and complex hierarchic systems
NASA Astrophysics Data System (ADS)
Zúñiga-Galindo, W. A.
2018-06-01
We initiate the study of non-Archimedean reaction-ultradiffusion equations and their connections with models of complex hierarchic systems. From a mathematical perspective, the equations studied here are the p-adic counterpart of the integro-differential models for phase separation introduced by Bates and Chmaj. Our equations are also generalizations of the ultradiffusion equations on trees studied in the 1980s by Ogielski, Stein, Bachas, Huberman, among others, and also generalizations of the master equations of the Avetisov et al models, which describe certain complex hierarchic systems. From a physical perspective, our equations are gradient flows of non-Archimedean free energy functionals and their solutions describe the macroscopic density profile of a bistable material whose space of states has an ultrametric structure. Some of our results are p-adic analogs of some well-known results in the Archimedean setting, however, the mechanism of diffusion is completely different due to the fact that it occurs in an ultrametric space.
Hierarchical prisoner’s dilemma in hierarchical game for resource competition
NASA Astrophysics Data System (ADS)
Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko
2017-07-01
Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.
Hierarchically nanostructured materials for sustainable environmental applications
Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian
2013-01-01
This review presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions, and multiple functionalities toward water remediation, biosensing, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing, and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology. PMID:24790946
Hierarchical fuzzy control of low-energy building systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, Zhen; Dexter, Arthur
2010-04-15
A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profilemore » can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)« less
A Petri net controller for distributed hierarchical systems. Thesis
NASA Technical Reports Server (NTRS)
Peck, Joseph E.
1991-01-01
The solutions to a wide variety of problems are often best organized as a distributed hierarchical system. These systems can be graphically and mathematically modeled through the use of Petri nets, which can easily represent synchronous, asynchronous, and concurrent operations. This thesis presents a controller implementation based on Petri nets and a design methodology for the interconnection of distributed Petri nets. Two case studies are presented in which the controller operates a physical system, the Center for Intelligent Robotic Systems for Space Exploration Dual Arm Robotic Testbed.
EMIR: a configurable hierarchical system for event monitoring and incident response
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Knuth, K. H.
2001-05-01
We consider the application of Bayesian inference to the study of self-organized structures in complex adaptive systems. In particular, we examine the distribution of elements, agents, or processes in systems dominated by hierarchical structure. We demonstrate that results obtained by Caianiello [1] on Hierarchical Modular Systems (HMS) can be found by applying Jaynes' Principle of Group Invariance [2] to a few key assumptions about our knowledge of hierarchical organization. Subsequent application of the Principle of Maximum Entropy allows inferences to be made about specific systems. The utility of the Bayesian method is considered by examining both successes and failures of the hierarchical model. We discuss how Caianiello's original statements suffer from the Mind Projection Fallacy [3] and we restate his assumptions thus widening the applicability of the HMS model. The relationship between inference and statistical physics, described by Jaynes [4], is reiterated with the expectation that this realization will aid the field of complex systems research by moving away from often inappropriate direct application of statistical mechanics to a more encompassing inferential methodology.
Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo
2018-05-10
Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.
Oak Ridge Computerized Hierarchical Information System (ORCHIS) status report, July 1973
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brooks, A.A.
1974-01-01
This report summarizes the concepts, software, and contents of the Oak Ridge Computerized Hierarchical Information System. This data analysis and text processing system was developed as an integrated, comprehensive information processing capability to meet the needs of an on-going multidisciplinary research and development organization. (auth)
Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.
Li, Shancang; Tryfonas, Theo; Russell, Gordon; Andriotis, Panagiotis
2016-08-01
Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess the security risks posed by each mobile applications (apps), thus gaining a stronger understanding of any vulnerabilities present. This paper aims at developing a three-layer framework that assesses the potential risks which apps introduce within the Android mobile systems. A Bayesian risk graphical model is proposed to evaluate risk propagation in a layered risk architecture. By integrating static analysis, dynamic analysis, and behavior analysis in a hierarchical framework, the risks and their propagation through each layer are well modeled by the Bayesian risk graph, which can quantitatively analyze risks faced to both apps and mobile systems. The proposed hierarchical Bayesian risk graph model offers a novel way to investigate the security risks in mobile environment and enables users and administrators to evaluate the potential risks. This strategy allows to strengthen both app security as well as the security of the entire system.
Hierarchical process memory: memory as an integral component of information processing
Hasson, Uri; Chen, Janice; Honey, Christopher J.
2015-01-01
Models of working memory commonly focus on how information is encoded into and retrieved from storage at specific moments. However, in the majority of real-life processes, past information is used continuously to process incoming information across multiple timescales. Considering single unit, electrocorticography, and functional imaging data, we argue that (i) virtually all cortical circuits can accumulate information over time, and (ii) the timescales of accumulation vary hierarchically, from early sensory areas with short processing timescales (tens to hundreds of milliseconds) to higher-order areas with long processing timescales (many seconds to minutes). In this hierarchical systems perspective, memory is not restricted to a few localized stores, but is intrinsic to information processing that unfolds throughout the brain on multiple timescales. “The present contains nothing more than the past, and what is found in the effect was already in the cause.”Henri L Bergson PMID:25980649
Extreme close approaches in hierarchical triple systems with comparable masses
NASA Astrophysics Data System (ADS)
Haim, Niv; Katz, Boaz
2018-06-01
We study close approaches in hierarchical triple systems with comparable masses using full N-body simulations, motivated by a recent model for type Ia supernovae involving direct collisions of white dwarfs (WDs). For stable hierarchical systems where the inner binary components have equal masses, we show that the ability of the inner binary to achieve very close approaches, where the separation between the components of the inner binary reaches values which are orders of magnitude smaller than the semi-major axis, can be analytically predicted from initial conditions. The rate of close approaches is found to be roughly linear with the mass of the tertiary. The rate increases in systems with unequal inner binaries by a marginal factor of ≲ 2 for mass ratios 0.5 ≤ m1/m2 ≤ 1 relevant for the inner white-dwarf binaries. For an average tertiary mass of ˜0.3M⊙ which is representative of typical M-dwarfs, the chance for clean collisions is ˜1% setting challenging constraints on the collisional model for type Ia's.
Compiler-Directed File Layout Optimization for Hierarchical Storage Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ding, Wei; Zhang, Yuanrui; Kandemir, Mahmut
File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performancemore » against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.« less
Compiler-Directed File Layout Optimization for Hierarchical Storage Systems
Ding, Wei; Zhang, Yuanrui; Kandemir, Mahmut; ...
2013-01-01
File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performancemore » against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.« less
Random walk on p-adics and hierarchical systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lukierska-Walasek, K.; Topolski, K.; Institute of Mathematics, Wroclaw University, pl. Grunwaldzki 2/4, 50-384 Wroclaw
2006-02-01
We show that p-adic analysis provides a quite natural basis for the description of relaxation in hierarchical systems. For our purposes, we specify the Markov stochastic process considered by Albeverio and Karwowski. As a result we have obtained a random walk on the p-adic integer numbers, which provides the generalization of Cayley tree proposed by Ogielski and Stein. The temperature-dependent power-law decay and the Kohlrausch law are derived.
A hierarchical, retinotopic proto-organization of the primate visual system at birth
Arcaro, Michael J; Livingstone, Margaret S
2017-01-01
The adult primate visual system comprises a series of hierarchically organized areas. Each cortical area contains a topographic map of visual space, with different areas extracting different kinds of information from the retinal input. Here we asked to what extent the newborn visual system resembles the adult organization. We find that hierarchical, topographic organization is present at birth and therefore constitutes a proto-organization for the entire primate visual system. Even within inferior temporal cortex, this proto-organization was already present, prior to the emergence of category selectivity (e.g., faces or scenes). We propose that this topographic organization provides the scaffolding for the subsequent development of visual cortex that commences at the onset of visual experience DOI: http://dx.doi.org/10.7554/eLife.26196.001 PMID:28671063
Formal Multilevel Hierarchical Verification of Synchronous MOS VLSI Circuits.
1987-06-01
166 12.4 Capacitance Coupling............................. 166 12.5 Multiple Abstraction Fuctions ....................... 168...depend on whether it is performing flat verification or hierarchical verification. The primary operations of Silica Pithecus when performing flat...signals never arise. The primary operation of Silica Pithecus when performing hierarchical verification is processing constraints to show they hold
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gorentla Venkata, Manjunath; Shamis, Pavel; Graham, Richard L
2013-01-01
Many scientific simulations, using the Message Passing Interface (MPI) programming model, are sensitive to the performance and scalability of reduction collective operations such as MPI Allreduce and MPI Reduce. These operations are the most widely used abstractions to perform mathematical operations over all processes that are part of the simulation. In this work, we propose a hierarchical design to implement the reduction operations on multicore systems. This design aims to improve the efficiency of reductions by 1) tailoring the algorithms and customizing the implementations for various communication mechanisms in the system 2) providing the ability to configure the depth ofmore » hierarchy to match the system architecture, and 3) providing the ability to independently progress each of this hierarchy. Using this design, we implement MPI Allreduce and MPI Reduce operations (and its nonblocking variants MPI Iallreduce and MPI Ireduce) for all message sizes, and evaluate on multiple architectures including InfiniBand and Cray XT5. We leverage and enhance our existing infrastructure, Cheetah, which is a framework for implementing hierarchical collective operations to implement these reductions. The experimental results show that the Cheetah reduction operations outperform the production-grade MPI implementations such as Open MPI default, Cray MPI, and MVAPICH2, demonstrating its efficiency, flexibility and portability. On Infini- Band systems, with a microbenchmark, a 512-process Cheetah nonblocking Allreduce and Reduce achieves a speedup of 23x and 10x, respectively, compared to the default Open MPI reductions. The blocking variants of the reduction operations also show similar performance benefits. A 512-process nonblocking Cheetah Allreduce achieves a speedup of 3x, compared to the default MVAPICH2 Allreduce implementation. On a Cray XT5 system, a 6144-process Cheetah Allreduce outperforms the Cray MPI by 145%. The evaluation with an application kernel
A Hierarchical Security Architecture for Cyber-Physical Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quanyan Zhu; Tamer Basar
2011-08-01
Security of control systems is becoming a pivotal concern in critical national infrastructures such as the power grid and nuclear plants. In this paper, we adopt a hierarchical viewpoint to these security issues, addressing security concerns at each level and emphasizing a holistic cross-layer philosophy for developing security solutions. We propose a bottom-up framework that establishes a model from the physical and control levels to the supervisory level, incorporating concerns from network and communication levels. We show that the game-theoretical approach can yield cross-layer security strategy solutions to the cyber-physical systems.
NASA Astrophysics Data System (ADS)
Minakuchi, Shu; Tsukamoto, Haruka; Takeda, Nobuo
2009-03-01
This study proposes novel hierarchical sensing concept for detecting damages in composite structures. In the hierarchical system, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with the optical fiber network through transducing mechanisms. The distributed "sensory nerve cell" devices detect the damage, and the fiber optic "spinal cord" network gathers damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of the hierarchical sensing system thorough comparison with existing fiber optic based systems and nerve systems in the animal kingdom. Then, in order to validate the proposed sensing concept, impact damage detection system for the composite structure was proposed. The sensor devices were developed based on Comparative Vacuum Monitoring (CVM) system and the Brillouin based distributed strain sensing was utilized to gather the damage signals from the distributed devices. Finally a verification test was conducted using prototype devices. Occurrence of barely visible impact damage was successfully detected and it was clearly indicated that the hierarchical system has better repairability, higher robustness, and wider monitorable area compared to existing systems utilizing embedded optical fiber sensors.
Dynamic Non-Hierarchical File Systems for Exascale Storage
DOE Office of Scientific and Technical Information (OSTI.GOV)
Long, Darrell E.; Miller, Ethan L
This constitutes the final report for “Dynamic Non-Hierarchical File Systems for Exascale Storage”. The ultimate goal of this project was to improve data management in scientific computing and high-end computing (HEC) applications, and to achieve this goal we proposed: to develop the first, HEC-targeted, file system featuring rich metadata and provenance collection, extreme scalability, and future storage hardware integration as core design goals, and to evaluate and develop a flexible non-hierarchical file system interface suitable for providing more powerful and intuitive data management interfaces to HEC and scientific computing users. Data management is swiftly becoming a serious problem in themore » scientific community – while copious amounts of data are good for obtaining results, finding the right data is often daunting and sometimes impossible. Scientists participating in a Department of Energy workshop noted that most of their time was spent “...finding, processing, organizing, and moving data and it’s going to get much worse”. Scientists should not be forced to become data mining experts in order to retrieve the data they want, nor should they be expected to remember the naming convention they used several years ago for a set of experiments they now wish to revisit. Ideally, locating the data you need would be as easy as browsing the web. Unfortunately, existing data management approaches are usually based on hierarchical naming, a 40 year-old technology designed to manage thousands of files, not exabytes of data. Today’s systems do not take advantage of the rich array of metadata that current high-end computing (HEC) file systems can gather, including content-based metadata and provenance1 information. As a result, current metadata search approaches are typically ad hoc and often work by providing a parallel management system to the “main” file system, as is done in Linux (the locate utility), personal computers, and enterprise
Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems
NASA Technical Reports Server (NTRS)
Menasce, Daniel A.; Pentakalos, Odysseas I.
1995-01-01
Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.
Robust Real-Time Music Transcription with a Compositional Hierarchical Model.
Pesek, Matevž; Leonardis, Aleš; Marolt, Matija
2017-01-01
The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.
Hierarchical cortical transcriptome disorganization in autism.
Lombardo, Michael V; Courchesne, Eric; Lewis, Nathan E; Pramparo, Tiziano
2017-01-01
Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple
Hierarchical graphs for better annotations of rule-based models of biochemical systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Bin; Hlavacek, William
2009-01-01
In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of amore » 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.« less
Griscti, Odette; Aston, Megan; Warner, Grace; Martin-Misener, Ruth; McLeod, Deborah
2017-01-01
To explore experiences of chronically ill patients and registered nurses when they negotiate patient care in hospital settings. Specifically, we explored how social and institutional discourses shape power relations during the negotiation process. The hospital system is embedded in a hierarchical structure where the voice of the healthcare provider as expert is often given more importance than the patient. This system has been criticised as being oppressive to patients who are perceived to be lower in the hierarchy. In this study, we illustrate how the hospital's hierarchical system is not always oppressing but can also create moments of empowerment for patients. A feminist poststructuralist approach informed by the teaching of Foucault was used to explore power relations between nurses and patients when negotiating patient care in hospital settings. Eight individuals who suffered from chronic illness shared their stories about how they negotiated their care with nurses in hospital settings. The interviews were tape-recorded. Discourse analysis was used to analyse the data. Patients recounted various experiences when their voices were not heard because the current hospital system privileged the healthcare provider experts' advice over the patients' voice. The hierarchical structure of hospital supported these dynamics by privileging nurses as gatekeepers of service, by excluding the patients' input in the nursing notes and through a process of self-regulation. However, patients in this study were not passive recipients of care and used their agency creatively to resist these discourses. Nurses need to be mindful of how the hospital's hierarchical system tends to place nurses in a position of power, and how their authoritative position may positively or adversely affect the negotiation of patient care. © 2016 John Wiley & Sons Ltd.
On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems
NASA Technical Reports Server (NTRS)
Tunstel, Edward; Jamshidi, Mo
1997-01-01
Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.
Resilient 3D hierarchical architected metamaterials
Meza, Lucas R.; Zelhofer, Alex J.; Clarke, Nigel; Mateos, Arturo J.; Kochmann, Dennis M.; Greer, Julia R.
2015-01-01
Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic–polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property. PMID:26330605
Resilient 3D hierarchical architected metamaterials.
Meza, Lucas R; Zelhofer, Alex J; Clarke, Nigel; Mateos, Arturo J; Kochmann, Dennis M; Greer, Julia R
2015-09-15
Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic-polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥ 50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property.
M.D. Bryant; B.E. Wright; B.J. Davies
1992-01-01
A hierarchical classification system separating stream habitat into habitat units defined by stream morphology and hydrology was used in a pre-enhancement stream survey. The system separates habitat units into macrounits, mesounits, and micro- units and includes a separate evaluation of instream cover that also uses the hierarchical scheme. This paper presents an...
Metastability on the hierarchical lattice
NASA Astrophysics Data System (ADS)
den Hollander, Frank; Jovanovski, Oliver
2017-07-01
We study metastability for Glauber spin-flip dynamics on the N-dimensional hierarchical lattice with n hierarchical levels. Each vertex carries an Ising spin that can take the values -1 or +1 . Spins interact with an external magnetic field h>0 . Pairs of spins interact with each other according to a ferromagnetic pair potential J=\\{J_i\\}i=1n , where J_i>0 is the strength of the interaction between spins at hierarchical distance i. Spins flip according to a Metropolis dynamics at inverse temperature β. In the limit as β\\to∞ , we analyse the crossover time from the metastable state \\boxminus (all spins -1 ) to the stable state \\boxplus (all spins +1 ). Under the assumption that J is non-increasing, we identify the mean transition time up to a multiplicative factor 1+o_β(1) . On the scale of its mean, the transition time is exponentially distributed. We also identify the set of configurations representing the gate for the transition. For the special case where Ji = \\tilde{J}/Ni , 1 ≤slant i ≤slant n , with \\tilde{J}>0 the relevant formulas simplify considerably. Also the hierarchical mean-field limit N\\to∞ can be analysed in detail.
In-plane crashworthiness of bio-inspired hierarchical honeycombs
Yin, Hanfeng; Huang, Xiaofei; Scarpa, Fabrizio; ...
2018-03-13
Biological tissues like bone, wood, and sponge possess hierarchical cellular topologies, which are lightweight and feature an excellent energy absorption capability. Here we present a system of bio-inspired hierarchical honeycomb structures based on hexagonal, Kagome, and triangular tessellations. The hierarchical designs and a reference regular honeycomb configuration are subjected to simulated in-plane impact using the nonlinear finite element code LS-DYNA. The numerical simulation results show that the triangular hierarchical honeycomb provides the best performance compared to the other two hierarchical honeycombs, and features more than twice the energy absorbed by the regular honeycomb under similar loading conditions. We also proposemore » a parametric study correlating the microstructure parameters (hierarchical length ratio r and the number of sub cells N) to the energy absorption capacity of these hierarchical honeycombs. The triangular hierarchical honeycomb with N = 2 and r = 1/8 shows the highest energy absorption capacity among all the investigated cases, and this configuration could be employed as a benchmark for the design of future safety protective systems.« less
In-plane crashworthiness of bio-inspired hierarchical honeycombs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yin, Hanfeng; Huang, Xiaofei; Scarpa, Fabrizio
Biological tissues like bone, wood, and sponge possess hierarchical cellular topologies, which are lightweight and feature an excellent energy absorption capability. Here we present a system of bio-inspired hierarchical honeycomb structures based on hexagonal, Kagome, and triangular tessellations. The hierarchical designs and a reference regular honeycomb configuration are subjected to simulated in-plane impact using the nonlinear finite element code LS-DYNA. The numerical simulation results show that the triangular hierarchical honeycomb provides the best performance compared to the other two hierarchical honeycombs, and features more than twice the energy absorbed by the regular honeycomb under similar loading conditions. We also proposemore » a parametric study correlating the microstructure parameters (hierarchical length ratio r and the number of sub cells N) to the energy absorption capacity of these hierarchical honeycombs. The triangular hierarchical honeycomb with N = 2 and r = 1/8 shows the highest energy absorption capacity among all the investigated cases, and this configuration could be employed as a benchmark for the design of future safety protective systems.« less
The Stability of Tidal Equilibrium for Hierarchical Star-Planet-Moon Systems
NASA Astrophysics Data System (ADS)
Adams, Fred C.
2018-04-01
Motivated by the current search for exomoons, this talk considers the stability of tidal equilibrium for hierarchical three-body systems containing a star, a planet, and a moon. In this treatment, the energy and angular momentum budgets include contributions from the planetary orbit, lunar orbit, stellar spin, planetary spin, and lunar spin. The goal is to determine the optimized energy state of the system subject to the constraint of constant angular momentum. Due to the lack of a closed form solution for the full three-body problem, however, we must use use an approximate description of the orbits. We first consider the Keplerian limit and find that the critical energy states are saddle points, rather than minima, so that these hierarchical systems have no stable tidal equilibrium states. We then generalize the calculation so that the lunar orbit is described by a time-averaged version of the circular restricted three-body problem. In this latter case, the critical energy state is a shallow minimum, so that a tidal equilibrium state exists. In both cases, however, the lunar orbit for the critical point lies outside the boundary (roughly half the Hill radius) where (previous) numerical simulations indicate dynamical instability.
HiCoDG: a hierarchical data-gathering scheme using cooperative multiple mobile elements.
Van Le, Duc; Oh, Hoon; Yoon, Seokhoon
2014-12-17
In this paper, we study mobile element (ME)-based data-gathering schemes in wireless sensor networks. Due to the physical speed limits of mobile elements, the existing data-gathering schemes that use mobile elements can suffer from high data-gathering latency. In order to address this problem, this paper proposes a new hierarchical and cooperative data-gathering (HiCoDG) scheme that enables multiple mobile elements to cooperate with each other to collect and relay data. In HiCoDG, two types of mobile elements are used: the mobile collector (MC) and the mobile relay (MR). MCs collect data from sensors and forward them to the MR, which will deliver them to the sink. In this work, we also formulated an integer linear programming (ILP) optimization problem to find the optimal trajectories for MCs and the MR, such that the traveling distance of MEs is minimized. Two variants of HiCoDG, intermediate station (IS)-based and cooperative movement scheduling (CMS)-based, are proposed to facilitate cooperative data forwarding from MCs to the MR. An analytical model for estimating the average data-gathering latency in HiCoDG was also designed. Simulations were performed to compare the performance of the IS and CMS variants, as well as a multiple traveling salesman problem (mTSP)-based approach. The simulation results show that HiCoDG outperforms mTSP in terms of latency. The results also show that CMS can achieve the lowest latency with low energy consumption.
Compiling software for a hierarchical distributed processing system
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2013-12-31
Compiling software for a hierarchical distributed processing system including providing to one or more compiling nodes software to be compiled, wherein at least a portion of the software to be compiled is to be executed by one or more nodes; compiling, by the compiling node, the software; maintaining, by the compiling node, any compiled software to be executed on the compiling node; selecting, by the compiling node, one or more nodes in a next tier of the hierarchy of the distributed processing system in dependence upon whether any compiled software is for the selected node or the selected node's descendents; sending to the selected node only the compiled software to be executed by the selected node or selected node's descendent.
Under-sampling in a Multiple-Channel Laser Vibrometry System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Corey, Jordan
2007-03-01
Laser vibrometry is a technique used to detect vibrations on objects using the interference of coherent light with itself. Most vibrometry systems process only one target location at a time, but processing multiple locations simultaneously provides improved detection capabilities. Traditional laser vibrometry systems employ oversampling to sample the incoming modulated-light signal, however as the number of channels increases in these systems, certain issues arise such a higher computational cost, excessive heat, increased power requirements, and increased component cost. This thesis describes a novel approach to laser vibrometry that utilizes undersampling to control the undesirable issues associated with over-sampled systems. Undersamplingmore » allows for significantly less samples to represent the modulated-light signals, which offers several advantages in the overall system design. These advantages include an improvement in thermal efficiency, lower processing requirements, and a higher immunity to the relative intensity noise inherent in laser vibrometry applications. A unique feature of this implementation is the use of a parallel architecture to increase the overall system throughput. This parallelism is realized using a hierarchical multi-channel architecture based on off-the-shelf programmable logic devices (PLDs).« less
Badre, David
2012-01-01
Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490
Towards a hierarchical optimization modeling framework for ...
Background:Bilevel optimization has been recognized as a 2-player Stackelberg game where players are represented as leaders and followers and each pursue their own set of objectives. Hierarchical optimization problems, which are a generalization of bilevel, are especially difficult because the optimization is nested, meaning that the objectives of one level depend on solutions to the other levels. We introduce a hierarchical optimization framework for spatially targeting multiobjective green infrastructure (GI) incentive policies under uncertainties related to policy budget, compliance, and GI effectiveness. We demonstrate the utility of the framework using a hypothetical urban watershed, where the levels are characterized by multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities), and objectives include minimization of policy cost, implementation cost, and risk; reduction of combined sewer overflow (CSO) events; and improvement in environmental benefits such as reduced nutrient run-off and water availability. Conclusions: While computationally expensive, this hierarchical optimization framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urba
Statistical label fusion with hierarchical performance models
Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.
2014-01-01
Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809
Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro
2016-02-01
Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Hierarchical Multiple Regression in Counseling Research: Common Problems and Possible Remedies.
ERIC Educational Resources Information Center
Petrocelli, John V.
2003-01-01
A brief content analysis was conducted on the use of hierarchical regression in counseling research published in the "Journal of Counseling Psychology" and the "Journal of Counseling & Development" during the years 1997-2001. Common problems are cited and possible remedies are described. (Contains 43 references and 3 tables.) (Author)
Hierarchical Strategy for Rapid Analysis Environment
NASA Technical Reports Server (NTRS)
Whitcomb, John
2003-01-01
A new philosophy is developed wherein the hierarchical definition of data is made use of in creating a better environment to conduct analyses of practical problems. This system can be adapted to conduct virtually any type of analysis, since this philosophy is not bound to any specific kind of analysis. It provides a framework to manage different models and its results and more importantly, the interaction between the different models. Thus, it is ideal for many types of finite element analyses like globalAoca1 analysis and those that involve multiple scales and fields. The system developed during the course of this work is just a demonstrator of the basic concepts. A complete implementation of this strategy could potentially make a major impact on the way analyses are conducted. It could considerably reduce the time frame required to conduct the analysis of real-life problems by efficient management of the data involved and reducing the human effort involved. It also helps in better decision making because of more ways to interpret the results. The strategy has been currently implemented for structural analysis, but with more work it could be extended to other fields of science when the finite element method is used to solve the differential equations numerically. This report details the work that has been done during the course of this project and its achievements and results. The following section discusses the meaning of the word hierarchical and the different references to the term in the literature. It talks about the development of the finite element method, its different versions and how hierarchy has been used to improve the methodology. The next section describes the hierarchical philosophy in detail and explains the different concepts and terms associated with it. It goes on to describe the implementation and the features of the demonstrator. A couple of problems are analyzed using the demonstrator program to show the working of the system. The two
Design, fabrication and testing of hierarchical micro-optical structures and systems
NASA Astrophysics Data System (ADS)
Cannistra, Aaron Thomas
Micro-optical systems are becoming essential components in imaging, sensing, communications, computing, and other applications. Optically based designs are replacing electronic, chemical and mechanical systems for a variety of reasons, including low power consumption, reduced maintenance, and faster operation. However, as the number and variety of applications increases, micro-optical system designs are becoming smaller, more integrated, and more complicated. Micro and nano-optical systems found in nature, such as the imaging systems found in many insects and crustaceans, can have highly integrated optical structures that vary in size by orders of magnitude. These systems incorporate components such as compound lenses, anti-reflective lens surface structuring, spectral filters, and polarization selective elements. For animals, these hybrid optical systems capable of many optical functions in a compact package have been repeatedly selected during the evolutionary process. Understanding the advantages of these designs gives motivation for synthetic optical systems with comparable functionality. However, alternative fabrication methods that deviate from conventional processes are needed to create such systems. Further complicating the issue, the resulting device geometry may not be readily compatible with existing measurement techniques. This dissertation explores several nontraditional fabrication techniques for optical components with hierarchical geometries and measurement techniques to evaluate performance of such components. A micro-transfer molding process is found to produce high-fidelity micro-optical structures and is used to fabricate a spectral filter on a curved surface. By using a custom measurement setup we demonstrate that the spectral filter retains functionality despite the nontraditional geometry. A compound lens is fabricated using similar fabrication techniques and the imaging performance is analyzed. A spray coating technique for photoresist
1983-12-16
management system (DBMS) is to record and maintain information used by an organization in the organization’s decision-making process. Some advantages of a...independence. Database Management Systems are classified into three major models; relational, network, and hierarchical. Each model uses a software...feeling impedes the overall effectiveness of the 4-" Acquisition Management Information System (AMIS), which currently uses S2k. The size of the AMIS
A hierarchical distributed control model for coordinating intelligent systems
NASA Technical Reports Server (NTRS)
Adler, Richard M.
1991-01-01
A hierarchical distributed control (HDC) model for coordinating cooperative problem-solving among intelligent systems is described. The model was implemented using SOCIAL, an innovative object-oriented tool for integrating heterogeneous, distributed software systems. SOCIAL embeds applications in 'wrapper' objects called Agents, which supply predefined capabilities for distributed communication, control, data specification, and translation. The HDC model is realized in SOCIAL as a 'Manager'Agent that coordinates interactions among application Agents. The HDC Manager: indexes the capabilities of application Agents; routes request messages to suitable server Agents; and stores results in a commonly accessible 'Bulletin-Board'. This centralized control model is illustrated in a fault diagnosis application for launch operations support of the Space Shuttle fleet at NASA, Kennedy Space Center.
Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks
USDA-ARS?s Scientific Manuscript database
Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...
Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle.
Peng, Jiankun; He, Hongwen; Liu, Wei; Guo, Hongqiang
2015-01-01
This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.
Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle
Peng, Jiankun; He, Hongwen; Guo, Hongqiang
2015-01-01
This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved. PMID:26236772
Microprocessor Based Real-Time Monitoring of Multiple ECG Signals
Nasipuri, M.; Basu, D.K.; Dattagupta, R.; Kundu, M.; Banerjee, S.
1987-01-01
A microprocessor based system capable of realtime monitoring of multiple ECG signals has been described. The system consists of a number of microprocessors connected in a hierarchical fashion and capable of working concurrently on ECG data collected from different channels. The system can monitor different arrhythmic abnormalities for at least 36 patients even for a heart rate of 500 beats/min.
Application of a hierarchical structure stochastic learning automation
NASA Technical Reports Server (NTRS)
Neville, R. G.; Chrystall, M. S.; Mars, P.
1979-01-01
A hierarchical structure automaton was developed using a two state stochastic learning automato (SLA) in a time shared model. Application of the hierarchical SLA to systems with multidimensional, multimodal performance criteria is described. Results of experiments performed with the hierarchical SLA using a performance index with a superimposed noise component of ? or - delta distributed uniformly over the surface are discussed.
NASA Astrophysics Data System (ADS)
Bekki, Kenji
2017-05-01
Most old globular clusters (GCs) in the Galaxy are observed to have internal chemical abundance spreads in light elements. We discuss a new GC formation scenario based on hierarchical star formation within fractal molecular clouds. In the new scenario, a cluster of bound and unbound star clusters ('star cluster complex', SCC) that have a power-law cluster mass function with a slope (β) of 2 is first formed from a massive gas clump developed in a dwarf galaxy. Such cluster complexes and β = 2 are observed and expected from hierarchical star formation. The most massive star cluster ('main cluster'), which is the progenitor of a GC, can accrete gas ejected from asymptotic giant branch (AGB) stars initially in the cluster and other low-mass clusters before the clusters are tidally stripped or destroyed to become field stars in the dwarf. The SCC is initially embedded in a giant gas hole created by numerous supernovae of the SCC so that cold gas outside the hole can be accreted on to the main cluster later. New stars formed from the accreted gas have chemical abundances that are different from those of the original SCC. Using hydrodynamical simulations of GC formation based on this scenario, we show that the main cluster with the initial mass as large as [2-5] × 105 M⊙ can accrete more than 105 M⊙ gas from AGB stars of the SCC. We suggest that merging of hierarchical SSCs can play key roles in stellar halo formation around GCs and self-enrichment processes in the early phase of GC formation.
ERIC Educational Resources Information Center
Anderson, Daniel
2012-01-01
This manuscript provides an overview of hierarchical linear modeling (HLM), as part of a series of papers covering topics relevant to consumers of educational research. HLM is tremendously flexible, allowing researchers to specify relations across multiple "levels" of the educational system (e.g., students, classrooms, schools, etc.).…
NASA thesaurus. Volume 1: Hierarchical Listing
NASA Technical Reports Server (NTRS)
1988-01-01
There are over 17,000 postable terms and nearly 4,000 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary and Volume 3 - Definitions.
NASA thesaurus. Volume 1: Hierarchical listing
NASA Technical Reports Server (NTRS)
1985-01-01
There are 16,835 postable terms and 3,765 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary.
NASA Thesaurus. Volume 1: Hierarchical listing
NASA Technical Reports Server (NTRS)
1982-01-01
There are 16,713 postable terms and 3,716 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary.
ERIC Educational Resources Information Center
Wholeben, Brent Edward
A number of key issues facing elementary, secondary, and postsecondary educational administrators during retrenchment require a hierarchical decision-modeling approach. This paper identifies and discusses the use of a hierarchical multiple-alternatives modeling formulation (computer-based) that compares and evaluates a group of solution…
HiCoDG: A Hierarchical Data-Gathering Scheme Using Cooperative Multiple Mobile Elements †
Van Le, Duc; Oh, Hoon; Yoon, Seokhoon
2014-01-01
In this paper, we study mobile element (ME)-based data-gathering schemes in wireless sensor networks. Due to the physical speed limits of mobile elements, the existing data-gathering schemes that use mobile elements can suffer from high data-gathering latency. In order to address this problem, this paper proposes a new hierarchical and cooperative data-gathering (HiCoDG) scheme that enables multiple mobile elements to cooperate with each other to collect and relay data. In HiCoDG, two types of mobile elements are used: the mobile collector (MC) and the mobile relay (MR). MCs collect data from sensors and forward them to the MR, which will deliver them to the sink. In this work, we also formulated an integer linear programming (ILP) optimization problem to find the optimal trajectories for MCs and the MR, such that the traveling distance of MEs is minimized. Two variants of HiCoDG, intermediate station (IS)-based and cooperative movement scheduling (CMS)-based, are proposed to facilitate cooperative data forwarding from MCs to the MR. An analytical model for estimating the average data-gathering latency in HiCoDG was also designed. Simulations were performed to compare the performance of the IS and CMS variants, as well as a multiple traveling salesman problem (mTSP)-based approach. The simulation results show that HiCoDG outperforms mTSP in terms of latency. The results also show that CMS can achieve the lowest latency with low energy consumption. PMID:25526356
Hierarchical analytical and simulation modelling of human-machine systems with interference
NASA Astrophysics Data System (ADS)
Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.
2017-01-01
The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.
Use Hierarchical Storage and Analysis to Exploit Intrinsic Parallelism
NASA Astrophysics Data System (ADS)
Zender, C. S.; Wang, W.; Vicente, P.
2013-12-01
Big Data is an ugly name for the scientific opportunities and challenges created by the growing wealth of geoscience data. How to weave large, disparate datasets together to best reveal their underlying properties, to exploit their strengths and minimize their weaknesses, to continually aggregate more information than the world knew yesterday and less than we will learn tomorrow? Data analytics techniques (statistics, data mining, machine learning, etc.) can accelerate pattern recognition and discovery. However, often researchers must, prior to analysis, organize multiple related datasets into a coherent framework. Hierarchical organization permits entire dataset to be stored in nested groups that reflect their intrinsic relationships and similarities. Hierarchical data can be simpler and faster to analyze by coding operators to automatically parallelize processes over isomorphic storage units, i.e., groups. The newest generation of netCDF Operators (NCO) embody this hierarchical approach, while still supporting traditional analysis approaches. We will use NCO to demonstrate the trade-offs involved in processing a prototypical Big Data application (analysis of CMIP5 datasets) using hierarchical and traditional analysis approaches.
Patterns of Hierarchical Structure in the Medical Lexicon
Michael, Patricia A.; Cole, William G.; Stewart, James; Blois, Marsden S.
1987-01-01
Concepts in basic and clinical medical science cover a wide range of levels of description, from the subatomic level to the level of the patient as a whole. Medical language may have usage regularities consistent with this hierarchical nature of medical knowledge. Preliminary studies of word occurrence in abstracts drawn from three medical journals representing three broadly defined levels of description (chemical system, physiologic system, and patient as a whole) demonstrated a nonuniform word usage, with many words unique to one or another journal. In this present study, word occurrence was examined in an expanded pool of medical text consisting of sixteen textbooks representing ten different levels of description: atom/ion, micromolecule, macromolecule, organelle, cell, tissue, organ, physiologic system, major body part (or multiple physiologic systems) and patient as a whole. Word usage was found to be nonuniform, with many words unique to specific levels. The presence of such usage regularities may provide a basis for facilitating the automatic classification and retrieval of medical text.
NASA Astrophysics Data System (ADS)
Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan
2018-04-01
To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.
The self-calibration method for multiple systems at the CHARA Array
NASA Astrophysics Data System (ADS)
O'Brien, David
The self-calibration method, a new interferometric technique at the CHARA Array, has been used to derive orbits for several spectroscopic binaries. This method uses the wide component of a hierarchical triple system to calibrate visibility measurements of the triple's close binary system. At certain baselines and separations, the calibrator in one of these systems can be observed quasi-simultaneously with the target. Depending on the orientation of the CHARA observation baseline relative to the orientation of the wide orbit of the triple system, separated fringe packets may be observed. A sophisticated observing scheme must be put in place to ensure the existence of separated fringe packets on nights of observation. Prior to the onset of this project, the reduction of separated fringe packet data had never included the goal of deriving visibilities for both fringe packets, so new data reduction software has been written. Visibilities obtained with separated fringe packet data for the target close binary are run through both Monte Carlo simulations and grid search programs in order to determine the best-fit orbital elements of the close binary. Several targets have been observed in this fashion, and orbits have been derived for seven targets, including three new orbits. Derivation of the orbit of the close pair in a triple system allows for the calculation of the mutual inclination, which is the angle between the planes of the wide and close orbit. Knowledge of this quantity may give insight into the formation processes that create multiple star systems. INDEX WORDS: Long-baseline interferometry, Self calibration, Separated fringe packets, Triple systems, Close binaries, Multiple systems, Orbital parameters, Near-infrared interferometry
Self-assembly of hierarchically ordered structures in DNA nanotube systems
NASA Astrophysics Data System (ADS)
Glaser, Martin; Schnauß, Jörg; Tschirner, Teresa; Schmidt, B. U. Sebastian; Moebius-Winkler, Maximilian; Käs, Josef A.; Smith, David M.
2016-05-01
The self-assembly of molecular and macromolecular building blocks into organized patterns is a complex process found in diverse systems over a wide range of size and time scales. The formation of star- or aster-like configurations, for example, is a common characteristic in solutions of polymers or other molecules containing multi-scaled, hierarchical assembly processes. This is a recurring phenomenon in numerous pattern-forming systems ranging from cellular constructs to solutions of ferromagnetic colloids or synthetic plastics. To date, however, it has not been possible to systematically parameterize structural properties of the constituent components in order to study their influence on assembled states. Here, we circumvent this limitation by using DNA nanotubes with programmable mechanical properties as our basic building blocks. A small set of DNA oligonucleotides can be chosen to hybridize into micron-length DNA nanotubes with a well-defined circumference and stiffness. The self-assembly of these nanotubes to hierarchically ordered structures is driven by depletion forces caused by the presence of polyethylene glycol. This trait allowed us to investigate self-assembly effects while maintaining a complete decoupling of density, self-association or bundling strength, and stiffness of the nanotubes. Our findings show diverse ranges of emerging structures including heterogeneous networks, aster-like structures, and densely bundled needle-like structures, which compare to configurations found in many other systems. These show a strong dependence not only on concentration and bundling strength, but also on the underlying mechanical properties of the nanotubes. Similar network architectures to those caused by depletion forces in the low-density regime are obtained when an alternative hybridization-based bundling mechanism is employed to induce self-assembly in an isotropic network of pre-formed DNA nanotubes. This emphasizes the universal effect inevitable
ORBITS OF FOUR YOUNG TRIPLE-LINED MULTIPLE SYSTEMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tokovinin, Andrei, E-mail: atokovinin@ctio.noao.edu
2016-07-01
Each of the nearby triple systems HIP 7601, 13498, 23824, and 113597 (HD 10800, 18198, 35877, 217379) consist of solar-type dwarfs with comparable masses, where all three components are resolved spectrally, while the outer pairs are resolved both visually and spectrally. These stars are relatively young (between 100 and 600 Myr) and chromospherically active (X-ray sources), although they rotate slowly. I determine the spectroscopic orbits of the inner subsystems (periods 19.4, 14.1, 5.6, 20.3 days) and the orbits of the outer systems (periods 1.75, 51, 27, 500 years, respectively). For HIP 7601 and 13498, the combined spectro-interferometric outer orbits producemore » direct measurement of the masses of all of the components, allowing for a comparison with stellar models. The 6708 Å lithium line is present and its strength is measured in each component individually by subtracting the contributions of the other components. The inner and outer orbits of HIP 7601 are nearly circular, likely co-planar, and have a modest period ratio of 1:33. This study contributes to the characterization of hierarchical multiplicity in the solar neighborhood and provides data for testing stellar evolutionary models and chronology.« less
Hierarchical and Parallelizable Direct Volume Rendering for Irregular and Multiple Grids
NASA Technical Reports Server (NTRS)
Wilhelms, Jane; VanGelder, Allen; Tarantino, Paul; Gibbs, Jonathan
1996-01-01
A general volume rendering technique is described that efficiently produces images of excellent quality from data defined over irregular grids having a wide variety of formats. Rendering is done in software, eliminating the need for special graphics hardware, as well as any artifacts associated with graphics hardware. Images of volumes with about one million cells can be produced in one to several minutes on a workstation with a 150 MHz processor. A significant advantage of this method for applications such as computational fluid dynamics is that it can process multiple intersecting grids. Such grids present problems for most current volume rendering techniques. Also, the wide range of cell sizes (by a factor of 10,000 or more), which is typical of such applications, does not present difficulties, as it does for many techniques. A spatial hierarchical organization makes it possible to access data from a restricted region efficiently. The tree has greater depth in regions of greater detail, determined by the number of cells in the region. It also makes it possible to render useful 'preview' images very quickly (about one second for one-million-cell grids) by displaying each region associated with a tree node as one cell. Previews show enough detail to navigate effectively in very large data sets. The algorithmic techniques include use of a kappa-d tree, with prefix-order partitioning of triangles, to reduce the number of primitives that must be processed for one rendering, coarse-grain parallelism for a shared-memory MIMD architecture, a new perspective transformation that achieves greater numerical accuracy, and a scanline algorithm with depth sorting and a new clipping technique.
Standardization of a Hierarchical Transactive Control System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hammerstrom, Donald J.; Oliver, Terry V.; Melton, Ronald B.
2010-12-03
The authors describe work they have conducted toward the generalization and standardization of the transactive control approach that was first demonstrated in the Olympic Peninsula Project for the management of a transmission constraint. The newly generalized approach addresses several potential shortfalls of the prior approach: First, the authors have formalized a hierarchical node structure which defines the nodes and the functional signal pathways between these nodes. Second, by fully generalizing the inputs, outputs, and functional responsibilities of each node, the authors make the approach available to a much wider set of responsive assets and operational objectives. Third, the new, generalizedmore » approach defines transactive signals that include the predicted day-ahead future. This predictive feature allows the market-like bids and offers to become resolved iteratively over time, thus allowing the behaviors of responsive assets to be called upon both for the present and as future dispatch decisions are being made. The hierarchical transactive control approach is a key feature of a proposed Pacific Northwest smart grid demonstration.« less
An exactly solvable model of hierarchical self-assembly
NASA Astrophysics Data System (ADS)
Dudowicz, Jacek; Douglas, Jack F.; Freed, Karl F.
2009-06-01
Many living and nonliving structures in the natural world form by hierarchical organization, but physical theories that describe this type of organization are scarce. To address this problem, a model of equilibrium self-assembly is formulated in which dynamically associating species organize into hierarchical structures that preserve their shape at each stage of assembly. In particular, we consider symmetric m-gons that associate at their vertices into Sierpinski gasket structures involving the hierarchical association of triangles, squares, hexagons, etc., at their corner vertices, thereby leading to fractal structures after many generations of assembly. This rather idealized model of hierarchical assembly yields an infinite sequence of self-assembly transitions as the morphology progressively organizes to higher levels of the hierarchy, and these structures coexists at dynamic equilibrium, as found in real hierarchically self-assembling systems such as amyloid fiber forming proteins. Moreover, the transition sharpness progressively grows with increasing m, corresponding to larger and larger loops in the assembled structures. Calculations are provided for several basic thermodynamic properties (including the order parameters for assembly for each stage of the hierarchy, average mass of clusters, specific heat, transition sharpness, etc.) that are required for characterizing the interaction parameters governing this type of self-assembly and for elucidating other basic qualitative aspects of these systems. Our idealized model of hierarchical assembly gives many insights into this ubiquitous type of self-organization process.
Hierarchical, Three-Dimensional Measurement System for Crime Scene Scanning.
Marcin, Adamczyk; Maciej, Sieniło; Robert, Sitnik; Adam, Woźniak
2017-07-01
We present a new generation of three-dimensional (3D) measuring systems, developed for the process of crime scene documentation. This measuring system facilitates the preparation of more insightful, complete, and objective documentation for crime scenes. Our system reflects the actual requirements for hierarchical documentation, and it consists of three independent 3D scanners: a laser scanner for overall measurements, a situational structured light scanner for more minute measurements, and a detailed structured light scanner for the most detailed parts of tscene. Each scanner has its own spatial resolution, of 2.0, 0.3, and 0.05 mm, respectively. The results of interviews we have conducted with technicians indicate that our developed 3D measuring system has significant potential to become a useful tool for forensic technicians. To ensure the maximum compatibility of our measuring system with the standards that regulate the documentation process, we have also performed a metrological validation and designated the maximum permissible length measurement error E MPE for each structured light scanner. In this study, we present additional results regarding documentation processes conducted during crime scene inspections and a training session. © 2017 American Academy of Forensic Sciences.
NASA Astrophysics Data System (ADS)
Lei, Tianhu; Udupa, Jayaram K.; Moonis, Gul; Schwartz, Eric; Balcer, Laura
2005-04-01
Based on Fuzzy Connectedness (FC) object delineation principles and algorithms, a hierarchical brain tissue segmentation technique has been developed for MR images. After MR image background intensity inhomogeneity correction and intensity standardization, three FC objects for cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) are generated via FC object delineation, and an intracranial (IC) mask is created via morphological operations. Then, the IC mask is decomposed into parenchymal (BP) and CSF masks, while the BP mask is separated into WM and GM masks. WM mask is further divided into pure and dirty white matter masks (PWM and DWM). In Multiple Sclerosis studies, a severe white matter lesion (LS) mask is defined from DWM mask. Based on the segmented brain tissue images, a histogram-based method has been developed to find disease-specific, image-based quantitative markers for characterizing the macromolecular manifestation of the two diseases. These same procedures have been applied to 65 MS (46 patients and 19 normal subjects) and 25 AD (15 patients and 10 normal subjects) data sets, each of which consists of FSE PD- and T2-weighted MR images. Histograms representing standardized PD and T2 intensity distributions and their numerical parameters provide an effective means for characterizing the two diseases. The procedures are systematic, nearly automated, robust, and the results are reproducible.
Hierarchical Production Planning: A Two Stage System.
1980-05-01
production planning issues (see [101,[121,[ 131 ). However, some elements of the hierarchical framework can also be construct- ively used to enhance an...inventories are nonzero, but the product families’ initial inventories are well balanced, i.e., if IJo = d , for 11,2,... ,I and JEJ(i)E) I ° Z j JCi ) JEJ(i
Retrieval Capabilities of Hierarchical Networks: From Dyson to Hopfield
NASA Astrophysics Data System (ADS)
Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia
2015-01-01
We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.
COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.
Cui, Licong
Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance
NASA Astrophysics Data System (ADS)
Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido
2015-12-01
The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.
NASA Technical Reports Server (NTRS)
Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Abdallah, Muhammad E. (Inventor)
2013-01-01
A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.
Automated control of hierarchical systems using value-driven methods
NASA Technical Reports Server (NTRS)
Pugh, George E.; Burke, Thomas E.
1990-01-01
An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.
NASA Astrophysics Data System (ADS)
Barkin, Yu. V.
2003-04-01
BELT-HIERARCHIC STRUCTURE OF THE RING, SATELLITE AND PLANET SYSTEMS: PREDICTION S/2001 U1 AND OTHERS OBJECTS IN SOLAR SYSTEM Yu.V.Barkin Sternberg Astronomical Institute, Moscow, Russia, barkin@sai.msu.ru Structure regularities of the planet and satellite systems have been studied. Statistic analysis of the distribution of the major semi-axes of the orbits of the planets, comets and centaurs of the Solar system, satellite and ring systems of Jupiter, Saturn, Neptune and Uran, exoplanet systems of the pulsars PSR 1257+12, PSR 1828-11 and of the main consequence star Ups And was fulfilled. The following empirical regularities were described [1]: 1) the bodies of systems are combined into hierarchic groups and main from them combine 5 companions; 2) differences of the major semi-axes of the neighboring orbits for bodies of every group are constant; 4) for main neighboring hierarchic group these distances are distinguished in 6 times increasing to external grope; 5) the filling of the gropes and some present changes in their structure are caused by the past catastrophes in corresponding systems. The special method of reconstruction of the catastrophes which had place in the life of the Solar system (SS) was developed. Suggested method has let us to explain uniformly observed values of the major semi-axes and average values of eccentricities of the planets. In particular the Pancul’s hypothesis about Jupiter formation from two giant protoplanets (Jupiter I and Jupiter II) was confirmed. The new empirical law of the filling of the orbits of the regular groups of the planets or satellites (or rings structures) of the hierarchic ordered systems of celestial bodies was established. It was shown that sum number of bodies is proportional to the value of catastrophic value of the eccentricities which are same for first, second ,.... and fifth orbits of all gropes. The theoretical numbers of bodies for pointed orbits practically coincide with their observed numbers in main
Schwieger, Wilhelm; Machoke, Albert Gonche; Weissenberger, Tobias; Inayat, Amer; Selvam, Thangaraj; Klumpp, Michael; Inayat, Alexandra
2016-06-13
'Hierarchy' is a property which can be attributed to a manifold of different immaterial systems, such as ideas, items and organisations or material ones like biological systems within living organisms or artificial, man-made constructions. The property 'hierarchy' is mainly characterised by a certain ordering of individual elements relative to each other, often in combination with a certain degree of branching. Especially mass-flow related systems in the natural environment feature special hierarchically branched patterns. This review is a survey into the world of hierarchical systems with special focus on hierarchically porous zeolite materials. A classification of hierarchical porosity is proposed based on the flow distribution pattern within the respective pore systems. In addition, this review might serve as a toolbox providing several synthetic and post-synthetic strategies to prepare zeolitic or zeolite containing material with tailored hierarchical porosity. Very often, such strategies with their underlying principles were developed for improving the performance of the final materials in different technical applications like adsorptive or catalytic processes. In the present review, besides on the hierarchically porous all-zeolite material, special focus is laid on the preparation of zeolitic composite materials with hierarchical porosity capable to face the demands of industrial application.
Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering
NASA Technical Reports Server (NTRS)
Tilton, James C.
2002-01-01
This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.
Activity recognition using dynamic multiple sensor fusion in body sensor networks.
Gao, Lei; Bourke, Alan K; Nelson, John
2012-01-01
Multiple sensor fusion is a main research direction for activity recognition. However, there are two challenges in those systems: the energy consumption due to the wireless transmission and the classifier design because of the dynamic feature vector. This paper proposes a multi-sensor fusion framework, which consists of the sensor selection module and the hierarchical classifier. The sensor selection module adopts the convex optimization to select the sensor subset in real time. The hierarchical classifier combines the Decision Tree classifier with the Naïve Bayes classifier. The dataset collected from 8 subjects, who performed 8 scenario activities, was used to evaluate the proposed system. The results show that the proposed system can obviously reduce the energy consumption while guaranteeing the recognition accuracy.
Hierarchical specification of the SIFT fault tolerant flight control system
NASA Technical Reports Server (NTRS)
Melliar-Smith, P. M.; Schwartz, R. L.
1981-01-01
The specification and mechanical verification of the Software Implemented Fault Tolerance (SIFT) flight control system is described. The methodology employed in the verification effort is discussed, and a description of the hierarchical models of the SIFT system is given. To meet the objective of NASA for the reliability of safety critical flight control systems, the SIFT computer must achieve a reliability well beyond the levels at which reliability can be actually measured. The methodology employed to demonstrate rigorously that the SIFT computer meets as reliability requirements is described. The hierarchy of design specifications from very abstract descriptions of system function down to the actual implementation is explained. The most abstract design specifications can be used to verify that the system functions correctly and with the desired reliability since almost all details of the realization were abstracted out. A succession of lower level models refine these specifications to the level of the actual implementation, and can be used to demonstrate that the implementation has the properties claimed of the abstract design specifications.
NASA Technical Reports Server (NTRS)
Leake, Stephen; Green, Tom; Cofer, Sue; Sauerwein, Tim
1989-01-01
HARPS is a telerobot control system that can perform some simple but useful tasks. This capability is demonstrated by performing the ORU exchange demonstration. HARPS is based on NASREM (NASA Standard Reference Model). All software is developed in Ada, and the project incorporates a number of different CASE (computer-aided software engineering) tools. NASREM was found to be a valid and useful model for building a telerobot control system. Its hierarchical and distributed structure creates a natural and logical flow for implementing large complex robust control systems. The ability of Ada to create and enforce abstraction enhanced the implementation of such control systems.
Chuang, Hui-Ping; Hsu, Mao-Hsuan; Chen, Wei-Yu
2013-01-01
In this study, we established a rapid multiplex method to detect the relative abundances of amplified 16S rRNA genes from known cultivatable methanogens at hierarchical specificities in anaerobic digestion systems treating industrial wastewater and sewage sludge. The method was based on the hierarchical oligonucleotide primer extension (HOPE) technique and combined with a set of 27 primers designed to target the total archaeal populations and methanogens from 22 genera within 4 taxonomic orders. After optimization for their specificities and detection sensitivity under the conditions of multiple single-nucleotide primer extension reactions, the HOPE approach was applied to analyze the methanogens in 19 consortium samples from 7 anaerobic treatment systems (i.e., 513 reactions). Among the samples, the methanogen populations detected with order-level primers accounted for >77.2% of the PCR-amplified 16S rRNA genes detected using an Archaea-specific primer. The archaeal communities typically consisted of 2 to 7 known methanogen genera within the Methanobacteriales, Methanomicrobiales, and Methanosarcinales and displayed population dynamic and spatial distributions in anaerobic reactor operations. Principal component analysis of the HOPE data further showed that the methanogen communities could be clustered into 3 distinctive groups, in accordance with the distribution of the Methanosaeta, Methanolinea, and Methanomethylovorans, respectively. This finding suggested that in addition to acetotrophic and hydrogenotrophic methanogens, the methylotrophic methanogens might play a key role in the anaerobic treatment of industrial wastewater. Overall, the results demonstrated that the HOPE approach is a specific, rapid, and multiplexing platform to determine the relative abundances of targeted methanogens in PCR-amplified 16S rRNA gene products. PMID:24077716
Self-assembled hierarchically structured organic-inorganic composite systems.
Tritschler, Ulrich; Cölfen, Helmut
2016-05-13
Designing bio-inspired, multifunctional organic-inorganic composite materials is one of the most popular current research objectives. Due to the high complexity of biocomposite structures found in nacre and bone, for example, a one-pot scalable and versatile synthesis approach addressing structural key features of biominerals and affording bio-inspired, multifunctional organic-inorganic composites with advanced physical properties is highly challenging. This article reviews recent progress in synthesizing organic-inorganic composite materials via various self-assembly techniques and in this context highlights a recently developed bio-inspired synthesis concept for the fabrication of hierarchically structured, organic-inorganic composite materials. This one-step self-organization concept based on simultaneous liquid crystal formation of anisotropic inorganic nanoparticles and a functional liquid crystalline polymer turned out to be simple, fast, scalable and versatile, leading to various (multi-)functional composite materials, which exhibit hierarchical structuring over several length scales. Consequently, this synthesis approach is relevant for further progress and scientific breakthrough in the research field of bio-inspired and biomimetic materials.
Egri-Nagy, Attila; Nehaniv, Chrystopher L
2008-01-01
Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.
NASA Astrophysics Data System (ADS)
Zinnecker, Hans
We review the multiplicity of massive stars by compiling the abstracts of the most relevant papers in the field. We start by discussing the massive stars in the Orion Trapezium Cluster and in other Galactic young clusters and OB associations, and end with the R136 cluster in the LMC. The multiplicity of field O-stars and runaway OB stars is also reviewed. The results of both visual and spectroscopic surveys are presented, as well as data for eclipsing systems. Among the latter, we find the most massive known binary system WR20a, with two ~,80M_⊙ components in a 3 day orbit. Some 80% of the wide visual binaries in stellar associations are in fact hierarchical triple systems, where typically the more massive of the binary components is itself a spectroscopic or even eclipsing binary pair. The multiplicity (number of companions) of massive star primaries is significantly higher than for low-mass solar-type primaries or for young low-mass T Tauri stars. There is also a striking preponderance of very close nearly equal mass binary systems (the origin of which has recently been explained in an accretion scenario). Finally, we offer a new idea as to the origin of massive Trapezium systems, frequently found in the centers of dense young clusters.
Hierarchically structured materials for lithium batteries
NASA Astrophysics Data System (ADS)
Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang
2013-10-01
The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg-1), new energy storage systems, such as lithium-oxygen (Li-O2) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li-O2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime.
Semantic Image Segmentation with Contextual Hierarchical Models.
Seyedhosseini, Mojtaba; Tasdizen, Tolga
2016-05-01
Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).
Resilient help to switch and overlap hierarchical subsystems in a small human group
Fujii, K.; Yokoyama, K.; Koyama, T.; Rikukawa, A.; Yamada, H.; Yamamoto, Y.
2016-01-01
Groups of social organisms in nature are resilient systems that can overcome unpredicted threats by helping its members. These social organisms are assumed to behave both autonomously and cooperatively as individuals, the helper, the helped and other part of a group depending on the context such as emergencies. However, the structure and function of these resilient actions, such as how helpers help colleagues and how the helper’s action is effective at multiple subsystem scales remain unclear. Here we investigated the behaviour of organised and efficient small human groups in a ballgame defence, and identified three principles of hierarchical resilient help when under attack. First, at a present high emergency level, the helper simply switched the local roles in the attacked subsystem with the helped. Second, at an intermediate emergency level, the helpers effectively acted in overlapping subsystems. Third, for the most critical emergency, the helpers globally switched the action on the overall system. These resilient actions to the benefit of the system were assumed to be observed in only humans, which help colleagues at flexibly switched and overlapped hierarchical subsystem. We suggest that these multi-layered helping behaviours can help to understand resilient cooperation in social organisms and human groups. PMID:27045443
Bio-inspired Fabrication of Complex Hierarchical Structure in Silicon.
Gao, Yang; Peng, Zhengchun; Shi, Tielin; Tan, Xianhua; Zhang, Deqin; Huang, Qiang; Zou, Chuanping; Liao, Guanglan
2015-08-01
In this paper, we developed a top-down method to fabricate complex three dimensional silicon structure, which was inspired by the hierarchical micro/nanostructure of the Morpho butterfly scales. The fabrication procedure includes photolithography, metal masking, and both dry and wet etching techniques. First, microscale photoresist grating pattern was formed on the silicon (111) wafer. Trenches with controllable rippled structures on the sidewalls were etched by inductively coupled plasma reactive ion etching Bosch process. Then, Cr film was angled deposited on the bottom of the ripples by electron beam evaporation, followed by anisotropic wet etching of the silicon. The simple fabrication method results in large scale hierarchical structure on a silicon wafer. The fabricated Si structure has multiple layers with uniform thickness of hundreds nanometers. We conducted both light reflection and heat transfer experiments on this structure. They exhibited excellent antireflection performance for polarized ultraviolet, visible and near infrared wavelengths. And the heat flux of the structure was significantly enhanced. As such, we believe that these bio-inspired hierarchical silicon structure will have promising applications in photovoltaics, sensor technology and photonic crystal devices.
Multiple memory systems as substrates for multiple decision systems
Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.
2014-01-01
It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and
Microparticles with hierarchical porosity
Petsev, Dimiter N; Atanassov, Plamen; Pylypenko, Svitlana; Carroll, Nick; Olson, Tim
2012-12-18
The present disclosure provides oxide microparticles with engineered hierarchical porosity and methods of manufacturing the same. Also described are structures that are formed by templating, impregnating, and/or precipitating the oxide microparticles and method for forming the same. Suitable applications include catalysts, electrocatalysts, electrocatalysts support materials, capacitors, drug delivery systems, sensors and chromatography.
ERIC Educational Resources Information Center
Zhou, Bo; Konstorum, Anna; Duong, Thao; Tieu, Kinh H.; Wells, William M.; Brown, Gregory G.; Stern, Hal S.; Shahbaba, Babak
2013-01-01
We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model…
Hierarchical modeling for reliability analysis using Markov models. B.S./M.S. Thesis - MIT
NASA Technical Reports Server (NTRS)
Fagundo, Arturo
1994-01-01
Markov models represent an extremely attractive tool for the reliability analysis of many systems. However, Markov model state space grows exponentially with the number of components in a given system. Thus, for very large systems Markov modeling techniques alone become intractable in both memory and CPU time. Often a particular subsystem can be found within some larger system where the dependence of the larger system on the subsystem is of a particularly simple form. This simple dependence can be used to decompose such a system into one or more subsystems. A hierarchical technique is presented which can be used to evaluate these subsystems in such a way that their reliabilities can be combined to obtain the reliability for the full system. This hierarchical approach is unique in that it allows the subsystem model to pass multiple aggregate state information to the higher level model, allowing more general systems to be evaluated. Guidelines are developed to assist in the system decomposition. An appropriate method for determining subsystem reliability is also developed. This method gives rise to some interesting numerical issues. Numerical error due to roundoff and integration are discussed at length. Once a decomposition is chosen, the remaining analysis is straightforward but tedious. However, an approach is developed for simplifying the recombination of subsystem reliabilities. Finally, a real world system is used to illustrate the use of this technique in a more practical context.
ERIC Educational Resources Information Center
Barnes, Clarissa S.
2013-01-01
This investigation evaluated the use of conditional discrimination (CD) instruction and multiple exemplar instruction (MEI) to establish derived relational responding in accordance with hierarchical frames with school aged children. The first experiment used a multiple probe design to evaluate the effectiveness of MEI to teach participants to…
Keck Adaptive Optics Imaging of Nearby Young Stars: Detection of Close Multiple Systems
NASA Astrophysics Data System (ADS)
Brandeker, Alexis; Jayawardhana, Ray; Najita, Joan
2003-10-01
Using adaptive optics on the Keck II 10 m telescope on Mauna Kea, we have surveyed 24 of the nearest young stars known in search of close companions. Our sample includes members of the MBM 12 and TW Hydrae young associations and the classical T Tauri binary UY Aurigae in the Taurus star-forming region. We present relative photometry and accurate astrometry for 10 close multiple systems. The multiplicity frequency in the TW Hydrae and MBM 12 groups are high in comparison to other young regions, although the significance of this result is low because of the small number statistics. We resolve S18 into a triple system, including a tight 63 mas (projected separation of 17 AU at a distance of 275 pc) binary, for the first time, with a hierarchical configuration reminiscent of VW Chamaeleontis and T Tauri. Another tight binary in our sample-TWA 5Aab (54 mas or 3 AU at 55 pc)-offers the prospect of dynamical mass measurement using astrometric observations within a few years and thus could be important for testing pre-main-sequence evolutionary models. Our observations confirm with 9 σ confidence that the brown dwarf TWA 5B is bound to TWA 5A. We find that the flux ratio of UY Aur has changed dramatically, by more than a magnitude in the H band, possibly as a result of variable extinction. With the smaller flux difference, the system may once again become detectable as an optical binary, as it was at the time of its discovery in 1944. Taken together, our results demonstrate that adaptive optics on large telescopes is a powerful tool for detecting tight companions and thus exploring the frequency and configurations of close multiple systems.
Predictability of extremes in non-linear hierarchically organized systems
NASA Astrophysics Data System (ADS)
Kossobokov, V. G.; Soloviev, A.
2011-12-01
Understanding the complexity of non-linear dynamics of hierarchically organized systems progresses to new approaches in assessing hazard and risk of the extreme catastrophic events. In particular, a series of interrelated step-by-step studies of seismic process along with its non-stationary though self-organized behaviors, has led already to reproducible intermediate-term middle-range earthquake forecast/prediction technique that has passed control in forward real-time applications during the last two decades. The observed seismic dynamics prior to and after many mega, great, major, and strong earthquakes demonstrate common features of predictability and diverse behavior in course durable phase transitions in complex hierarchical non-linear system of blocks-and-faults of the Earth lithosphere. The confirmed fractal nature of earthquakes and their distribution in space and time implies that many traditional estimations of seismic hazard (from term-less to short-term ones) are usually based on erroneous assumptions of easy tractable analytical models, which leads to widespread practice of their deceptive application. The consequences of underestimation of seismic hazard propagate non-linearly into inflicted underestimation of risk and, eventually, into unexpected societal losses due to earthquakes and associated phenomena (i.e., collapse of buildings, landslides, tsunamis, liquefaction, etc.). The studies aimed at forecast/prediction of extreme events (interpreted as critical transitions) in geophysical and socio-economical systems include: (i) large earthquakes in geophysical systems of the lithosphere blocks-and-faults, (ii) starts and ends of economic recessions, (iii) episodes of a sharp increase in the unemployment rate, (iv) surge of the homicides in socio-economic systems. These studies are based on a heuristic search of phenomena preceding critical transitions and application of methodologies of pattern recognition of infrequent events. Any study of rare
A hierarchical competing systems model of the emergence and early development of executive function
Marcovitch, Stuart; Zelazo, Philip David
2010-01-01
The hierarchical competing systems model (HCSM) provides a framework for understanding the emergence and early development of executive function – the cognitive processes underlying the conscious control of behavior – in the context of search for hidden objects. According to this model, behavior is determined by the joint influence of a developmentally invariant habit system and a conscious representational system that becomes increasingly influential as children develop. This article describes a computational formalization of the HCSM, reviews behavioral and computational research consistent with the model, and suggests directions for future research on the development of executive function. PMID:19120405
Pérez-Hernández, Guillermo; Noé, Frank
2016-12-13
Analysis of molecular dynamics, for example using Markov models, often requires the identification of order parameters that are good indicators of the rare events, i.e. good reaction coordinates. Recently, it has been shown that the time-lagged independent component analysis (TICA) finds the linear combinations of input coordinates that optimally represent the slow kinetic modes and may serve in order to define reaction coordinates between the metastable states of the molecular system. A limitation of the method is that both computing time and memory requirements scale with the square of the number of input features. For large protein systems, this exacerbates the use of extensive feature sets such as the distances between all pairs of residues or even heavy atoms. Here we derive a hierarchical TICA (hTICA) method that approximates the full TICA solution by a hierarchical, divide-and-conquer calculation. By using hTICA on distances between heavy atoms we identify previously unknown relaxation processes in the bovine pancreatic trypsin inhibitor.
New insight in magnetic saturation behavior of nickel hierarchical structures
NASA Astrophysics Data System (ADS)
Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng
2017-09-01
It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.
Photodynamical modeling of hierarchical stellar system KOI-126
NASA Astrophysics Data System (ADS)
Earl, Nicholas Michael
The power and precision of the Kepler space telescope has provided the astrophysical field with a valuable insight into the dynamics of extra-solar systems. KOI-126 represents the first eclipsing hierarchical triple stellar system identified in the Kepler mission's photometry. The dynamics of the system are such that ascertaining the parameters of each body accurately (better than a few percent) is possible from the photometry alone. This allows determination of the characteristics while avoiding biases inherent in traditional studies of low-mass eclipsing systems. The parameter set for KOI-126 was originally reported on by Carter et al. and is uniquely composed of a low-mass binary, KOI-126 B and KOI-126 C. This pair orbits a third, more massive star KOI-126 A. The original analysis employed a full dynamical-photometric model, utilizing a Levenberg-Marquardt algorithm and least-squares minimization, to fit the short-cadence (i.e. successive 58.84 second cadence exposures) photometric data from the Kepler spacecraft captured over a period of 247 days. The updated catalog of short-cadence data now covers a span of 1,300 days. In light of the new data, and the valuable contribution accurately sampled fully-convective stars offer to theoretical stellar models, it is therefore relevant to refine the parameters of this system. Furthermore, with the ubiquity of multi-stellar systems, a well documented, portable, scalable computer modeling code for N-body systems is introduced. Thus, a new analysis is done on KOI-126 using this parallelized dynamical-photometric modeling package written in Python, based on Carter et al.'s original code, titled Pynamic. Pynamic allows the use of several fitting algorithms, but in this analysis utilizes the affine-invariant Markov chain Monte Carlo ensemble.
Tensegrity I. Cell structure and hierarchical systems biology
NASA Technical Reports Server (NTRS)
Ingber, Donald E.
2003-01-01
In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.
A hierarchical word-merging algorithm with class separability measure.
Wang, Lei; Zhou, Luping; Shen, Chunhua; Liu, Lingqiao; Liu, Huan
2014-03-01
In image recognition with the bag-of-features model, a small-sized visual codebook is usually preferred to obtain a low-dimensional histogram representation and high computational efficiency. Such a visual codebook has to be discriminative enough to achieve excellent recognition performance. To create a compact and discriminative codebook, in this paper we propose to merge the visual words in a large-sized initial codebook by maximally preserving class separability. We first show that this results in a difficult optimization problem. To deal with this situation, we devise a suboptimal but very efficient hierarchical word-merging algorithm, which optimally merges two words at each level of the hierarchy. By exploiting the characteristics of the class separability measure and designing a novel indexing structure, the proposed algorithm can hierarchically merge 10,000 visual words down to two words in merely 90 seconds. Also, to show the properties of the proposed algorithm and reveal its advantages, we conduct detailed theoretical analysis to compare it with another hierarchical word-merging algorithm that maximally preserves mutual information, obtaining interesting findings. Experimental studies are conducted to verify the effectiveness of the proposed algorithm on multiple benchmark data sets. As shown, it can efficiently produce more compact and discriminative codebooks than the state-of-the-art hierarchical word-merging algorithms, especially when the size of the codebook is significantly reduced.
Bayesian Hierarchical Classes Analysis
ERIC Educational Resources Information Center
Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn
2008-01-01
Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…
Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.
Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco
2017-06-27
Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.
Universal Method for Creating Hierarchical Wrinkles on Thin-Film Surfaces.
Jung, Woo-Bin; Cho, Kyeong Min; Lee, Won-Kyu; Odom, Teri W; Jung, Hee-Tae
2018-01-10
One of the most interesting topics in physical science and materials science is the creation of complex wrinkled structures on thin-film surfaces because of their several advantages of high surface area, localized strain, and stress tolerance. In this study, a significant step was taken toward solving limitations imposed by the fabrication of previous artificial wrinkles. A universal method for preparing hierarchical three-dimensional wrinkle structures of thin films on a multiple scale (e.g., nanometers to micrometers) by sequential wrinkling with different skin layers was developed. Notably, this method was not limited to specific materials, and it was applicable to fabricating hierarchical wrinkles on all of the thin-film surfaces tested thus far, including those of metals, two-dimensional and one-dimensional materials, and polymers. The hierarchical wrinkles with multiscale structures were prepared by sequential wrinkling, in which a sacrificial layer was used as the additional skin layer between sequences. For example, a hierarchical MoS 2 wrinkle exhibited highly enhanced catalytic behavior because of the superaerophobicity and effective surface area, which are related to topological effects. As the developed method can be adopted to a majority of thin films, it is thought to be a universal method for enhancing the physical properties of various materials.
Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun
2016-07-08
RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.
Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun
2016-01-01
RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses. PMID:27387525
NASA Astrophysics Data System (ADS)
Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun
2016-07-01
RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.
Stickiness in Hamiltonian systems: From sharply divided to hierarchical phase space
NASA Astrophysics Data System (ADS)
Altmann, Eduardo G.; Motter, Adilson E.; Kantz, Holger
2006-02-01
We investigate the dynamics of chaotic trajectories in simple yet physically important Hamiltonian systems with nonhierarchical borders between regular and chaotic regions with positive measures. We show that the stickiness to the border of the regular regions in systems with such a sharply divided phase space occurs through one-parameter families of marginally unstable periodic orbits and is characterized by an exponent γ=2 for the asymptotic power-law decay of the distribution of recurrence times. Generic perturbations lead to systems with hierarchical phase space, where the stickiness is apparently enhanced due to the presence of infinitely many regular islands and Cantori. In this case, we show that the distribution of recurrence times can be composed of a sum of exponentials or a sum of power laws, depending on the relative contribution of the primary and secondary structures of the hierarchy. Numerical verification of our main results are provided for area-preserving maps, mushroom billiards, and the newly defined magnetic mushroom billiards.
Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)
NASA Astrophysics Data System (ADS)
Raskovic, Dejan
Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.
Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items
ERIC Educational Resources Information Center
Mariano, Louis T.; Junker, Brian W.
2007-01-01
When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…
The k-d Tree: A Hierarchical Model for Human Cognition.
ERIC Educational Resources Information Center
Vandendorpe, Mary M.
This paper discusses a model of information storage and retrieval, the k-d tree (Bentley, 1975), a binary, hierarchical tree with multiple associate terms, which has been explored in computer research, and it is suggested that this model could be useful for describing human cognition. Included are two models of human long-term memory--networks and…
Universality classes of fluctuation dynamics in hierarchical complex systems
NASA Astrophysics Data System (ADS)
Macêdo, A. M. S.; González, Iván R. Roa; Salazar, D. S. P.; Vasconcelos, G. L.
2017-03-01
A unified approach is proposed to describe the statistics of the short-time dynamics of multiscale complex systems. The probability density function of the relevant time series (signal) is represented as a statistical superposition of a large time-scale distribution weighted by the distribution of certain internal variables that characterize the slowly changing background. The dynamics of the background is formulated as a hierarchical stochastic model whose form is derived from simple physical constraints, which in turn restrict the dynamics to only two possible classes. The probability distributions of both the signal and the background have simple representations in terms of Meijer G functions. The two universality classes for the background dynamics manifest themselves in the signal distribution as two types of tails: power law and stretched exponential, respectively. A detailed analysis of empirical data from classical turbulence and financial markets shows excellent agreement with the theory.
A hierarchical SVG image abstraction layer for medical imaging
NASA Astrophysics Data System (ADS)
Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer
2010-03-01
As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.
Convex Clustering: An Attractive Alternative to Hierarchical Clustering
Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth
2015-01-01
The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340
Convex clustering: an attractive alternative to hierarchical clustering.
Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth
2015-05-01
The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.
Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shorikov, A. F., E-mail: afshorikov@mail.ru
We consider a discrete–time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector nonlinear or linear discrete–time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminalmore » approach process with incomplete information and give a general scheme for its solving.« less
3D hierarchical spatial representation and memory of multimodal sensory data
NASA Astrophysics Data System (ADS)
Khosla, Deepak; Dow, Paul A.; Huber, David J.
2009-04-01
This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine
Hierarchical neural network model of the visual system determining figure/ground relation
NASA Astrophysics Data System (ADS)
Kikuchi, Masayuki
2017-07-01
One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.
Hierarchical semi-numeric method for pairwise fuzzy group decision making.
Marimin, M; Umano, M; Hatono, I; Tamura, H
2002-01-01
Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.
Mykrä, Heikki; Heino, Jani; Muotka, Timo
2004-09-01
Streams are naturally hierarchical systems, and their biota are affected by factors effective at regional to local scales. However, there have been only a few attempts to quantify variation in ecological attributes across multiple spatial scales. We examined the variation in several macroinvertebrate metrics and environmental variables at three hierarchical scales (ecoregions, drainage systems, streams) in boreal headwater streams. In nested analyses of variance, significant spatial variability was observed for most of the macroinvertebrate metrics and environmental variables examined. For most metrics, ecoregions explained more variation than did drainage systems. There was, however, much variation attributable to residuals, suggesting high among-stream variation in macroinvertebrate assemblage characteristics. Nonmetric multidimensional scaling (NMDS) and multiresponse permutation procedure (MRPP) showed that assemblage composition differed significantly among both drainage systems and ecoregions. The associated R-statistics were, however, very low, indicating wide variation among sites within the defined landscape classifications. Regional delineations explained most of the variation in stream water chemistry, ecoregions being clearly more influential than drainage systems. For physical habitat characteristics, by contrast, the among-stream component was the major source of variation. Distinct differences attributable to stream size were observed for several metrics, especially total number of taxa and abundance of algae-scraping invertebrates. Although ecoregions clearly account for a considerable amount of variation in macroinvertebrate assemblage characteristics, we suggest that a three-tiered classification system (stratification through ecoregion and habitat type, followed by assemblage prediction within these ecologically meaningful units) will be needed for effective bioassessment of boreal running waters.
Broadband locally resonant metamaterials with graded hierarchical architecture
NASA Astrophysics Data System (ADS)
Liu, Chenchen; Reina, Celia
2018-03-01
We investigate the effect of hierarchical designs on the bandgap structure of periodic lattice systems with inner resonators. A detailed parameter study reveals various interesting features of structures with two levels of hierarchy as compared with one level systems with identical static mass. In particular: (i) their overall bandwidth is approximately equal, yet bounded above by the bandwidth of the single-resonator system; (ii) the number of bandgaps increases with the level of hierarchy; and (iii) the spectrum of bandgap frequencies is also enlarged. Taking advantage of these features, we propose graded hierarchical structures with ultra-broadband properties. These designs are validated over analogous continuum models via finite element simulations, demonstrating their capability to overcome the bandwidth narrowness that is typical of resonant metamaterials.
Teacher and Paraeducator Perceptions of a Hierarchical to Hierarchical-Collaborative Relationship
ERIC Educational Resources Information Center
Dalley, Anna Maria
2017-01-01
This qualitative, descriptive single-case study explored the transition from a hierarchical to a hierarchical-collaborative relationship between special education teachers (SET) and special education paraeducators (SEP). Sixteen participants, including eight veteran SET and eight SEP working in one county located in the Mid-Atlantic region of the…
Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?
Czégel, Dániel; Palla, Gergely
2015-01-01
Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology. PMID:26657012
Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?
Czégel, Dániel; Palla, Gergely
2015-12-10
Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.
Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?
NASA Astrophysics Data System (ADS)
Czégel, Dániel; Palla, Gergely
2015-12-01
Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.
A nontransferring dry adhesive with hierarchical polymer nanohairs.
Jeong, Hoon Eui; Lee, Jin-Kwan; Kim, Hong Nam; Moon, Sang Heup; Suh, Kahp Y
2009-04-07
We present a simple yet robust method for fabricating angled, hierarchically patterned high-aspect-ratio polymer nanohairs to generate directionally sensitive dry adhesives. The slanted polymeric nanostructures were molded from an etched polySi substrate containing slanted nanoholes. An angled etching technique was developed to fabricate slanted nanoholes with flat tips by inserting an etch-stop layer of silicon dioxide. This unique etching method was equipped with a Faraday cage system to control the ion-incident angles in the conventional plasma etching system. The polymeric nanohairs were fabricated with tailored leaning angles, sizes, tip shapes, and hierarchical structures. As a result of controlled leaning angle and bulged flat top of the nanohairs, the replicated, slanted nanohairs showed excellent directional adhesion, exhibiting strong shear attachment (approximately 26 N/cm(2) in maximum) in the angled direction and easy detachment (approximately 2.2 N/cm(2)) in the opposite direction, with a hysteresis value of approximately 10. In addition to single scale nanohairs, monolithic, micro-nanoscale combined hierarchical hairs were also fabricated by using a 2-step UV-assisted molding technique. These hierarchical nanoscale patterns maintained their adhesive force even on a rough surface (roughness <20 microm) because of an increase in the contact area by the enhanced height of hierarchy, whereas simple nanohairs lost their adhesion strength. To demonstrate the potential applications of the adhesive patch, the dry adhesive was used to transport a large-area glass (47.5 x 37.5 cm(2), second-generation TFT-LCD glass), which could replace the current electrostatic transport/holding system with further optimization.
A nontransferring dry adhesive with hierarchical polymer nanohairs
Jeong, Hoon Eui; Lee, Jin-Kwan; Kim, Hong Nam; Moon, Sang Heup; Suh, Kahp Y.
2009-01-01
We present a simple yet robust method for fabricating angled, hierarchically patterned high-aspect-ratio polymer nanohairs to generate directionally sensitive dry adhesives. The slanted polymeric nanostructures were molded from an etched polySi substrate containing slanted nanoholes. An angled etching technique was developed to fabricate slanted nanoholes with flat tips by inserting an etch-stop layer of silicon dioxide. This unique etching method was equipped with a Faraday cage system to control the ion-incident angles in the conventional plasma etching system. The polymeric nanohairs were fabricated with tailored leaning angles, sizes, tip shapes, and hierarchical structures. As a result of controlled leaning angle and bulged flat top of the nanohairs, the replicated, slanted nanohairs showed excellent directional adhesion, exhibiting strong shear attachment (≈26 N/cm2 in maximum) in the angled direction and easy detachment (≈2.2 N/cm2) in the opposite direction, with a hysteresis value of ≈10. In addition to single scale nanohairs, monolithic, micro-nanoscale combined hierarchical hairs were also fabricated by using a 2-step UV-assisted molding technique. These hierarchical nanoscale patterns maintained their adhesive force even on a rough surface (roughness <20 μm) because of an increase in the contact area by the enhanced height of hierarchy, whereas simple nanohairs lost their adhesion strength. To demonstrate the potential applications of the adhesive patch, the dry adhesive was used to transport a large-area glass (47.5 × 37.5 cm2, second-generation TFT-LCD glass), which could replace the current electrostatic transport/holding system with further optimization. PMID:19304801
The Updated Multiple Star Catalog
NASA Astrophysics Data System (ADS)
Tokovinin, Andrei
2018-03-01
The catalog of hierarchical stellar systems with three or more components is an update of the original 1997 version. For 2000 hierarchies, the new Multiple Star Catalog (MSC) provides distances, component masses and periods, and supplementary information (astrometry, photometry, identifiers, orbits, notes). The MSC content and format are explained, and its incompleteness and strong observational selection are stressed. Nevertheless, the MSC can be used for statistical studies and is a valuable source for planning observations of multiple stars. Rare classes of stellar hierarchies found in the MSC (with six or seven components, extremely eccentric orbits, planar and possibly resonant orbits, hosting planets) are briefly presented. High-order hierarchies have smaller velocity dispersion compared to triples and are often associated with moving groups. The paper concludes with an analysis of the ratio of periods and separations between inner and outer subsystems. In wide hierarchies, the ratio of semimajor axes, estimated statistically, is distributed between 3 and 300, with no evidence of dynamically unstable systems.
NASA Astrophysics Data System (ADS)
Shiklomanov, A. N.; Cowdery, E.; Dietze, M.
2016-12-01
Recent syntheses of global trait databases have revealed that although the functional diversity among plant species is immense, this diversity is constrained by trade-offs between plant strategies. However, the use of among-trait and trait-environment correlations at the global scale for both qualitative ecological inference and land surface modeling has several important caveats. An alternative approach is to preserve the existing PFT-based model structure while using statistical analyses to account for uncertainty and variability in model parameters. In this study, we used a hierarchical Bayesian model of foliar traits in the TRY database to test the following hypotheses: (1) Leveraging the covariance between foliar traits will significantly constrain our uncertainty in their distributions; and (2) Among-trait covariance patterns are significantly different among and within PFTs, reflecting differences in trade-offs associated with biome-level evolution, site-level community assembly, and individual-level ecophysiological acclimation. We found that among-trait covariance significantly constrained estimates of trait means, and the additional information provided by across-PFT covariance led to more constraint still, especially for traits and PFTs with low sample sizes. We also found that among-trait correlations were highly variable among PFTs, and were generally inconsistent with correlations within PFTs. The hierarchical multivariate framework developed in our study can readily be enhanced with additional levels of hierarchy to account for geographic, species, and individual-level variability.
Serial, parallel and hierarchical decision making in primates
Zylberberg, Ariel; Lorteije, Jeannette AM; Ouellette, Brian G; De Zeeuw, Chris I; Sigman, Mariano; Roelfsema, Pieter
2017-01-01
The study of decision-making has mainly focused on isolated decisions where choices are associated with motor actions. However, problem-solving often involves considering a hierarchy of sub-decisions. In a recent study (Lorteije et al. 2015), we reported behavioral and neuronal evidence for hierarchical decision making in a task with a small decision tree. We observed a first phase of parallel evidence integration for multiple sub-decisions, followed by a phase in which the overall strategy formed. It has been suggested that a 'flat' competition between the ultimate motor actions might also explain these results. A reanalysis of the data does not support the critical predictions of flat models. We also examined the time-course of decision making in other, related tasks and report conditions where evidence integration for successive decisions is decoupled, which excludes flat models. We conclude that the flexibility of decision-making implies that the strategies are genuinely hierarchical. DOI: http://dx.doi.org/10.7554/eLife.17331.001 PMID:28648172
HiPS - Hierarchical Progressive Survey Version 1.0
NASA Astrophysics Data System (ADS)
Fernique, Pierre; Allen, Mark; Boch, Thomas; Donaldson, Tom; Durand, Daniel; Ebisawa, Ken; Michel, Laurent; Salgado, Jesus; Stoehr, Felix; Fernique, Pierre
2017-05-01
This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.
Hierarchical video summarization based on context clustering
NASA Astrophysics Data System (ADS)
Tseng, Belle L.; Smith, John R.
2003-11-01
A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.
Synthetic observations of protostellar multiple systems
NASA Astrophysics Data System (ADS)
Lomax, O.; Whitworth, A. P.
2018-04-01
Observations of protostars are often compared with synthetic observations of models in order to infer the underlying physical properties of the protostars. The majority of these models have a single protostar, attended by a disc and an envelope. However, observational and numerical evidence suggests that a large fraction of protostars form as multiple systems. This means that fitting models of single protostars to observations may be inappropriate. We produce synthetic observations of protostellar multiple systems undergoing realistic, non-continuous accretion. These systems consist of multiple protostars with episodic luminosities, embedded self-consistently in discs and envelopes. We model the gas dynamics of these systems using smoothed particle hydrodynamics and we generate synthetic observations by post-processing the snapshots using the SPAMCART Monte Carlo radiative transfer code. We present simulation results of three model protostellar multiple systems. For each of these, we generate 4 × 104 synthetic spectra at different points in time and from different viewing angles. We propose a Bayesian method, using similar calculations to those presented here, but in greater numbers, to infer the physical properties of protostellar multiple systems from observations.
NASA Astrophysics Data System (ADS)
Cervero, T.; Gómez, A.; López, S.; Sarmiento, R.; Dondo, J.; Rincón, F.; López, J. C.
2013-05-01
One of the limiting factors that have prevented a widely dissemination of the reconfigurable technology is the absence of an appropriate model for certain target applications capable of offering a reliable control. Moreover, the lack of flexible and easy-to-use scheduling and management systems are also relevant drawbacks to be considered. Under static scenarios, it is relatively easy to schedule and manage the reconfiguration process since all the variations corresponding to predetermined and well-known tasks. However, the difficulty increases when the adaptation needs of the overall system change semi-randomly according to the environmental fluctuations. In this context, this work proposes a change in the paradigm of dynamically reconfigurable systems, by attending to the dynamically reconfigurable control problematic as a whole, in which the scheduling and the placement issues are packed together as a hierarchical management structure, interacting together as one entity from the system point of view, but performing their tasks with certain degree of independence each other. In this sense, the top hierarchical level corresponds with a dynamic scheduler in charge of planning and adjusting all the reconfigurable modules according to the variations of the external stimulus. The lower level interacts with the physical layer of the device by means of instantiating, relocating, removing a reconfigurable module following the scheduler's instructions. In regards to how fast is the proposed solution, the total partial reconfiguration time achieved with this proposal has been measured and compared with other two approaches: 1) using traditional Xilinx's tools; 2) using an optimized version of the Xilinx's drivers. The collected numbers demonstrate that our solution reaches a gain up to 10 times faster than the other approaches.
Scale relativity and hierarchical structuring of planetary systems
NASA Astrophysics Data System (ADS)
Galopeau, P. H. M.; Nottale, L.; da Rocha, D.; Tran Minh, N.
2003-04-01
The theory of scale relativity, applied to macroscopic gravitational systems like planetary systems, allows one to predict quantization laws of several key parameters characterizing those systems (distance between planets and central star, obliquity, eccentricity...) which are organized in a hierarchical way. In the framework of the scale relativity approach, one demonstrates that the motion (at relatively large time-scales) of the bodies in planetary systems, described in terms of fractal geodesic trajectories, is governed by a Schrödinger-like equation. Preferential orbits are predicted in terms of probability density peaks with semi-major axis given by: a_n = GMn^2/w^2 (M is the mass of the central star and w is a velocity close to 144 km s-1 in the case of our inner solar system and of the presently observed exoplanets). The velocity of the planet orbiting at this distance satisfies the relation v_n = w/n. Moreover, the mass distribution of the planets in our solar system can be accounted for in this model. These predictions are in good agreement with the observed values of the actual orbital parameters. Furthermore, the exoplanets which have been recently discovered around nearby stars also follow the same law in terms of the same constant in a highly significant statistical way. The theory of scale relativity also predicts structures for the obliquities and inclinations of the planets and satellites: the probability density of their distribution between 0 and pi are expected to display peaks at particular angles θ_k = kpi/n. A statistical agreement is obtained for our solar system with n=7. Another prediction concerns the distribution of the planets eccentricities e. The theory foresees a quantization law e = k/n where k is an integer and n is the quantum number that characterizes semi-major axes. The presently known exoplanet eccentricities are compatible with this theoretical prediction. Finally, although all these planetary systems may look very
Hierarchical Kohonenen net for anomaly detection in network security.
Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie
2005-04-01
A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.
How hierarchical is language use?
Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.
2012-01-01
It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157
Hierarchical models and Bayesian analysis of bird survey information
Sauer, J.R.; Link, W.A.; Royle, J. Andrew; Ralph, C. John; Rich, Terrell D.
2005-01-01
Summary of bird survey information is a critical component of conservation activities, but often our summaries rely on statistical methods that do not accommodate the limitations of the information. Prioritization of species requires ranking and analysis of species by magnitude of population trend, but often magnitude of trend is a misleading measure of actual decline when trend is poorly estimated. Aggregation of population information among regions is also complicated by varying quality of estimates among regions. Hierarchical models provide a reasonable means of accommodating concerns about aggregation and ranking of quantities of varying precision. In these models the need to consider multiple scales is accommodated by placing distributional assumptions on collections of parameters. For collections of species trends, this allows probability statements to be made about the collections of species-specific parameters, rather than about the estimates. We define and illustrate hierarchical models for two commonly encountered situations in bird conservation: (1) Estimating attributes of collections of species estimates, including ranking of trends, estimating number of species with increasing populations, and assessing population stability with regard to predefined trend magnitudes; and (2) estimation of regional population change, aggregating information from bird surveys over strata. User-friendly computer software makes hierarchical models readily accessible to scientists.
ERIC Educational Resources Information Center
Kong, Siu Cheung; Li, Ping; Song, Yanjie
2018-01-01
This study evaluated a bilingual text-mining system, which incorporated a bilingual taxonomy of key words and provided hierarchical visualization, for understanding learner-generated text in the learning management systems through automatic identification and counting of matching key words. A class of 27 in-service teachers studied a course…
Hierarchical analysis of forest bird species-environment relationships in the Oregon Coast Range
Samuel A. Cushman; Kevin McGarigal
2004-01-01
Species in biological communities respond to environmental variation simultaneously across a range of organizational levels. Accordingly, it is important to quantify the effects of environmental factors at multiple levels on species distribution and abundance. Hierarchical methods that explicitly separate the independent and confounded influences of environmental...
Hierarchical planning for a surface mounting machine placement.
Zeng, You-jiao; Ma, Deng-ze; Jin, Ye; Yan, Jun-qi
2004-11-01
For a surface mounting machine (SMM) in printed circuit board (PCB) assembly line, there are four problems, e.g. CAD data conversion, nozzle selection, feeder assignment and placement sequence determination. A hierarchical planning for them to maximize the throughput rate of an SMM is presented here. To minimize set-up time, a CAD data conversion system was first applied that could automatically generate the data for machine placement from CAD design data files. Then an effective nozzle selection approach implemented to minimize the time of nozzle changing. And then, to minimize picking time, an algorithm for feeder assignment was used to make picking multiple components simultaneously as much as possible. Finally, in order to shorten pick-and-place time, a heuristic algorithm was used to determine optimal component placement sequence according to the decided feeder positions. Experiments were conducted on a four head SMM. The experimental results were used to analyse the assembly line performance.
NASA Astrophysics Data System (ADS)
Yang, Chao; Jiao, Xiaohong; Li, Liang; Zhang, Yuanbo; Chen, Zheng
2018-01-01
To realize a fast and smooth operating mode transition process from electric driving mode to engine-on driving mode, this paper presents a novel robust hierarchical mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics models of powertrain and clutch actuating mechanism, a hierarchical control structure including two robust H∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H∞controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L2-gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed hierarchical control approach can obtain the good control performance: mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.
Royle, J. Andrew; Converse, Sarah J.
2014-01-01
Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.
GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling
NASA Astrophysics Data System (ADS)
Miki, Yohei; Umemura, Masayuki
2017-04-01
The tree method is a widely implemented algorithm for collisionless N-body simulations in astrophysics well suited for GPU(s). Adopting hierarchical time stepping can accelerate N-body simulations; however, it is infrequently implemented and its potential remains untested in GPU implementations. We have developed a Gravitational Oct-Tree code accelerated by HIerarchical time step Controlling named GOTHIC, which adopts both the tree method and the hierarchical time step. The code adopts some adaptive optimizations by monitoring the execution time of each function on-the-fly and minimizes the time-to-solution by balancing the measured time of multiple functions. Results of performance measurements with realistic particle distribution performed on NVIDIA Tesla M2090, K20X, and GeForce GTX TITAN X, which are representative GPUs of the Fermi, Kepler, and Maxwell generation of GPUs, show that the hierarchical time step achieves a speedup by a factor of around 3-5 times compared to the shared time step. The measured elapsed time per step of GOTHIC is 0.30 s or 0.44 s on GTX TITAN X when the particle distribution represents the Andromeda galaxy or the NFW sphere, respectively, with 224 = 16,777,216 particles. The averaged performance of the code corresponds to 10-30% of the theoretical single precision peak performance of the GPU.
Hierarchical clustering of HPV genotype patterns in the ASCUS-LSIL triage study
Wentzensen, Nicolas; Wilson, Lauren E.; Wheeler, Cosette M.; Carreon, Joseph D.; Gravitt, Patti E.; Schiffman, Mark; Castle, Philip E.
2010-01-01
Anogenital cancers are associated with about 13 carcinogenic HPV types in a broader group that cause cervical intraepithelial neoplasia (CIN). Multiple concurrent cervical HPV infections are common which complicate the attribution of HPV types to different grades of CIN. Here we report the analysis of HPV genotype patterns in the ASCUS-LSIL triage study using unsupervised hierarchical clustering. Women who underwent colposcopy at baseline (n = 2780) were grouped into 20 disease categories based on histology and cytology. Disease groups and HPV genotypes were clustered using complete linkage. Risk of 2-year cumulative CIN3+, viral load, colposcopic impression, and age were compared between disease groups and major clusters. Hierarchical clustering yielded four major disease clusters: Cluster 1 included all CIN3 histology with abnormal cytology; Cluster 2 included CIN3 histology with normal cytology and combinations with either CIN2 or high-grade squamous intraepithelial lesion (HSIL) cytology; Cluster 3 included older women with normal or low grade histology/cytology and low viral load; Cluster 4 included younger women with low grade histology/cytology, multiple infections, and the highest viral load. Three major groups of HPV genotypes were identified: Group 1 included only HPV16; Group 2 included nine carcinogenic types plus non-carcinogenic HPV53 and HPV66; and Group 3 included non-carcinogenic types plus carcinogenic HPV33 and HPV45. Clustering results suggested that colposcopy missed a prevalent precancer in many women with no biopsy/normal histology and HSIL. This result was confirmed by an elevated 2-year risk of CIN3+ in these groups. Our novel approach to study multiple genotype infections in cervical disease using unsupervised hierarchical clustering can address complex genotype distributions on a population level. PMID:20959485
Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination
Bhattarai, Bishnu P.; Levesque, Martin; Bak-Jensen, Birgitte; ...
2016-12-07
Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from themore » power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.« less
Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhattarai, Bishnu P.; Levesque, Martin; Bak-Jensen, Birgitte
Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from themore » power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.« less
A hierarchical framework of aquatic ecological units in North America (Nearctic Zone).
James R. Maxwell; Clayton J. Edwards; Mark E. Jensen; Steven J. Paustian; Harry Parrott; Donley M. Hill
1995-01-01
Proposes a framework for classifying and mapping aquatic systems at various scales using ecologically significant physical and biological criteria. Classification and mapping concepts follow tenets of hierarchical theory, pattern recognition, and driving variables. Criteria are provided for the hierarchical classification and mapping of aquatic ecological units of...
Hierarchical approaches for systems modeling in cardiac development.
Gould, Russell A; Aboulmouna, Lina M; Varner, Jeffrey D; Butcher, Jonathan T
2013-01-01
Ordered cardiac morphogenesis and function are essential for all vertebrate life. The heart begins as a simple contractile tube, but quickly grows and morphs into a multichambered pumping organ complete with valves, while maintaining regulation of blood flow and nutrient distribution. Though not identical, cardiac morphogenesis shares many molecular and morphological processes across vertebrate species. Quantitative data across multiple time and length scales have been gathered through decades of reductionist single variable analyses. These range from detailed molecular signaling pathways at the cellular levels to cardiac function at the tissue/organ levels. However, none of these components act in true isolation from others, and each, in turn, exhibits short- and long-range effects in both time and space. With the absence of a gene, entire signaling cascades and genetic profiles may be shifted, resulting in complex feedback mechanisms. Also taking into account local microenvironmental changes throughout development, it is apparent that a systems level approach is an essential resource to accelerate information generation concerning the functional relationships across multiple length scales (molecular data vs physiological function) and structural development. In this review, we discuss relevant in vivo and in vitro experimental approaches, compare different computational frameworks for systems modeling, and the latest information about systems modeling of cardiac development. Finally, we conclude with some important future directions for cardiac systems modeling. Copyright © 2013 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Singh, Santosh Kumar; Ghatak Choudhuri, Sumit
2018-05-01
Parallel connection of UPS inverters to enhance power rating is a widely accepted practice. Inter-modular circulating currents appear when multiple inverter modules are connected in parallel to supply variable critical load. Interfacing of modules henceforth requires an intensive design, using proper control strategy. The potentiality of human intuitive Fuzzy Logic (FL) control with imprecise system model is well known and thus can be utilised in parallel-connected UPS systems. Conventional FL controller is computational intensive, especially with higher number of input variables. This paper proposes application of Hierarchical-Fuzzy Logic control for parallel connected Multi-modular inverters system for reduced computational burden on the processor for a given switching frequency. Simulated results in MATLAB environment and experimental verification using Texas TMS320F2812 DSP are included to demonstrate feasibility of the proposed control scheme.
NASA Astrophysics Data System (ADS)
Yuan, Yuan; Sun, Fuchun; Liu, Huaping
2016-07-01
This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.
Hierarchical Marginal Land Assessment for Land Use Planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kang, Shujiang; Post, Wilfred M; Wang, Dali
2013-01-01
Marginal land provides an alternative potential for food and bioenergy production in the face of limited land resources; however, effective assessment of marginal lands is not well addressed. Concerns over environmental risks, ecosystem services and sustainability for marginal land have been widely raised. The objective of this study was to develop a hierarchical marginal land assessment framework for land use planning and management. We first identified major land functions linking production, environment, ecosystem services and economics, and then classified land resources into four categories of marginal land using suitability and limitations associated with major management goals, including physically marginal land,more » biologically marginal land, environmental-ecological marginal land, and economically marginal land. We tested this assessment framework in south-western Michigan, USA. Our results indicated that this marginal land assessment framework can be potentially feasible on land use planning for food and bioenergy production, and balancing multiple goals of land use management. We also compared our results with marginal land assessment from the Conservation Reserve Program (CRP) and land capability classes (LCC) that are used in the US. The hierarchical assessment framework has advantages of quantitatively reflecting land functions and multiple concerns. This provides a foundation upon which focused studies can be identified in order to improve the assessment framework by quantifying high-resolution land functions associated with environment and ecosystem services as well as their criteria are needed to improve the assessment framework.« less
Morphew, Daniel; Shaw, James; Avins, Christopher; Chakrabarti, Dwaipayan
2018-03-27
Colloidal self-assembly is a promising bottom-up route to a wide variety of three-dimensional structures, from clusters to crystals. Programming hierarchical self-assembly of colloidal building blocks, which can give rise to structures ordered at multiple levels to rival biological complexity, poses a multiscale design problem. Here we explore a generic design principle that exploits a hierarchy of interaction strengths and employ this design principle in computer simulations to demonstrate the hierarchical self-assembly of triblock patchy colloidal particles into two distinct colloidal crystals. We obtain cubic diamond and body-centered cubic crystals via distinct clusters of uniform size and shape, namely, tetrahedra and octahedra, respectively. Such a conceptual design framework has the potential to reliably encode hierarchical self-assembly of colloidal particles into a high level of sophistication. Moreover, the design framework underpins a bottom-up route to cubic diamond colloidal crystals, which have remained elusive despite being much sought after for their attractive photonic applications.
Hierarchical structure in sharply divided phase space for the piecewise linear map
NASA Astrophysics Data System (ADS)
Akaishi, Akira; Aoki, Kazuki; Shudo, Akira
2017-05-01
We have studied a two-dimensional piecewise linear map to examine how the hierarchical structure of stable regions affects the slow dynamics in Hamiltonian systems. In the phase space there are infinitely many stable regions, each of which is polygonal-shaped, and the rest is occupied by chaotic orbits. By using symbolic representation of stable regions, a procedure to compute the edges of the polygons is presented. The stable regions are hierarchically distributed in phase space and the edges of the stable regions show the marginal instability. The cumulative distribution of the recurrence time obeys a power law as ˜t-2 , the same as the one for the system with phase space, which is composed of a single stable region and chaotic components. By studying the symbol sequence of recurrence trajectories, we show that the hierarchical structure of stable regions has no significant effect on the power-law exponent and that only the marginal instability on the boundary of stable regions is responsible for determining the exponent. We also discuss the relevance of the hierarchical structure to those in more generic chaotic systems.
NASA Astrophysics Data System (ADS)
Azarnova, T. V.; Titova, I. A.; Barkalov, S. A.
2018-03-01
The article presents an algorithm for obtaining an integral assessment of the quality of an organization from the perspective of customers, based on the method of aggregating linguistic information on a multilevel hierarchical system of quality assessment. The algorithm is of a constructive nature, it provides not only the possibility of obtaining an integral evaluation, but also the development of a quality improvement strategy based on the method of linguistic decomposition, which forms the minimum set of areas of work with clients whose quality change will allow obtaining the required level of integrated quality assessment.
Butun, Ismail; Ra, In-Ho; Sankar, Ravi
2015-01-01
In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915
A hierarchical instrumental decision theory of nicotine dependence.
Hogarth, Lee; Troisi, Joseph R
2015-01-01
It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.
Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems
Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho
2013-01-01
Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568
Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks
Xu, Jianfeng; Lan, Yueheng
2015-01-01
Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347
Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G
2014-09-30
This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Nemravová, J. A.; Harmanec, P.; Brož, M.; Vokrouhlický, D.; Mourard, D.; Hummel, C. A.; Cameron, C.; Matthews, J. M.; Bolton, C. T.; Božić, H.; Chini, R.; Dembsky, T.; Engle, S.; Farrington, C.; Grunhut, J. H.; Guenther, D. B.; Guinan, E. F.; Korčáková, D.; Koubský, P.; Kříček, R.; Kuschnig, R.; Mayer, P.; McCook, G. P.; Moffat, A. F. J.; Nardetto, N.; Prša, A.; Ribeiro, J.; Rowe, J.; Rucinski, S.; Škoda, P.; Šlechta, M.; Tallon-Bosc, I.; Votruba, V.; Weiss, W. W.; Wolf, M.; Zasche, P.; Zavala, R. T.
2016-10-01
Context. Compact hierarchical systems are important because the effects caused by the dynamical interaction among its members occur ona human timescale. These interactions play a role in the formation of close binaries through Kozai cycles with tides. One such system is ξ Tauri: it has three hierarchical orbits: 7.14 d (eclipsing components Aa, Ab), 145 d (components Aa+Ab, B), and 51 yr (components Aa+Ab+B, C). Aims: We aim to obtain physical properties of the system and to study the dynamical interaction between its components. Methods: Our analysis is based on a large series of spectroscopic photometric (including space-borne) observations and long-baseline optical and infrared spectro-interferometric observations. We used two approaches to infer the system properties: a set of observation-specific models, where all components have elliptical trajectories, and an N-body model, which computes the trajectory of each component by integrating Newton's equations of motion. Results: The triple subsystem exhibits clear signs of dynamical interaction. The most pronounced are the advance of the apsidal line and eclipse-timing variations. We determined the geometry of all three orbits using both observation-specific and N-body models. The latter correctly accounted for observed effects of the dynamical interaction, predicted cyclic variations of orbital inclinations, and determined the sense of motion of all orbits. Using perturbation theory, we demonstrate that prominent secular and periodic dynamical effects are explainable with a quadrupole interaction. We constrained the basic properties of all components, especially of members of the inner triple subsystem and detected rapid low-amplitude light variations that we attribute to co-rotating surface structures of component B. We also estimated the radius of component B. Properties of component C remain uncertain because of its low relative luminosity. We provide an independent estimate of the distance to the system
A knowledge-base generating hierarchical fuzzy-neural controller.
Kandadai, R M; Tien, J M
1997-01-01
We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.
Epidemics and dimensionality in hierarchical networks
NASA Astrophysics Data System (ADS)
Zheng, Da-Fang; Hui, P. M.; Trimper, Steffen; Zheng, Bo
2005-07-01
Epidemiological processes are studied within a recently proposed hierarchical network model using the susceptible-infected-refractory dynamics of an epidemic. Within the network model, a population may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveal that for H>1, global spreading results regardless of the degree of homophily of the individuals forming a social circle. For H=1, a transition from global to local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large-scale outbreaks of infectious diseases (viruses).
A hierarchical modeling methodology for the definition and selection of requirements
NASA Astrophysics Data System (ADS)
Dufresne, Stephane
This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems. At the core of the methodology, the Analytic Network Process (ANP) is used to ensure the traceability between the qualitative and quantitative information present in the hierarchical model. The proposed methodology is implemented to the requirements definition of a hurricane tracker Unmanned Aerial Vehicle. Three research objectives are identified in this work; (1) improve the requirements mapping process by matching the stakeholder expectations with the concept of operations, systems and available resources; (2) reduce the epistemic uncertainty surrounding the requirements and requirements mapping; and (3) improve the requirements down-selection process by taking into account the level of importance of the criteria and the available resources. Several challenges are associated with the identification and definition of requirements. The complexity of the system implies that a large number of requirements are needed to define the systems. These requirements are defined early in the conceptual design, where the level of knowledge is relatively low and the level of uncertainty is large. The proposed methodology intends to increase the level of knowledge and reduce the level of uncertainty by guiding the design team through a structured process. To address these challenges, a new methodology is created to flow-down the requirements from the stakeholder expectations to the systems alternatives. A taxonomy of requirements is created to classify the information gathered during the problem definition. Subsequently, the operational and systems functions and measures of effectiveness are integrated to a hierarchical model to allow the traceability of the information. Monte Carlo methods are used to evaluate the variations of the hierarchical model elements and consequently reduce the
Hierarchical Model for the Evolution of Cloud Complexes
NASA Astrophysics Data System (ADS)
Sánchez D., Néstor M.; Parravano, Antonio
1999-01-01
The structure of cloud complexes appears to be well described by a tree structure (i.e., a simplified ``stick man'') representation when the image is partitioned into ``clouds.'' In this representation, the parent-child relationships are assigned according to containment. Based on this picture, a hierarchical model for the evolution of cloud complexes, including star formation, is constructed. The model follows the mass evolution of each substructure by computing its mass exchange with its parent and children. The parent-child mass exchange (evaporation or condensation) depends on the radiation density at the interphase. At the end of the ``lineage,'' stars may be born or die, so that there is a nonstationary mass flow in the hierarchical structure. For a variety of parameter sets the system follows the same series of steps to transform diffuse gas into stars, and the regulation of the mass flux in the tree by previously formed stars dominates the evolution of the star formation. For the set of parameters used here as a reference model, the system tends to produce initial mass functions (IMFs) that have a maximum at a mass that is too high (~2 Msolar) and the characteristic times for evolution seem too long. We show that these undesired properties can be improved by adjusting the model parameters. The model requires further physics (e.g., allowing for multiple stellar systems and clump collisions) before a definitive comparison with observations can be made. Instead, the emphasis here is to illustrate some general properties of this kind of complex nonlinear model for the star formation process. Notwithstanding the simplifications involved, the model reveals an essential feature that will likely remain if additional physical processes are included, that is, the detailed behavior of the system is very sensitive to the variations on the initial and external conditions, suggesting that a ``universal'' IMF is very unlikely. When an ensemble of IMFs corresponding to a
Silver Films with Hierarchical Chirality.
Ma, Liguo; Cao, Yuanyuan; Duan, Yingying; Han, Lu; Che, Shunai
2017-07-17
Physical fabrication of chiral metallic films usually results in singular or large-sized chirality, restricting the optical asymmetric responses to long electromagnetic wavelengths. The chiral molecule-induced formation of silver films prepared chemically on a copper substrate through a redox reaction is presented. Three levels of chirality were identified: primary twisted nanoflakes with atomic crystal lattices, secondary helical stacking of these nanoflakes to form nanoplates, and tertiary micrometer-sized circinates consisting of chiral arranged nanoplates. The chiral Ag films exhibited multiple plasmonic absorption- and scattering-based optical activities at UV/Vis wavelengths based on their hierarchical chirality. The Ag films showed chiral selectivity for amino acids in catalytic electrochemical reactions, which originated from their primary atomic crystal lattices. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Hierarchical content-based image retrieval by dynamic indexing and guided search
NASA Astrophysics Data System (ADS)
You, Jane; Cheung, King H.; Liu, James; Guo, Linong
2003-12-01
This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.
Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation
NASA Technical Reports Server (NTRS)
Park, Yeonjoon (Inventor); Elliott, James R. (Inventor); Stoakley, Diane M. (Inventor); Chu, Sang-Hyon (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Choi, Sang Hyouk (Inventor); Lillehei, Peter T. (Inventor)
2011-01-01
A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).
Chatterjee, Nivedita; Sinha, Sitabhra
2008-01-01
The nervous system of the nematode C. elegans provides a unique opportunity to understand how behavior ('mind') emerges from activity in the nervous system ('brain') of an organism. The hermaphrodite worm has only 302 neurons, all of whose connections (synaptic and gap junctional) are known. Recently, many of the functional circuits that make up its behavioral repertoire have begun to be identified. In this paper, we investigate the hierarchical structure of the nervous system through k-core decomposition and find it to be intimately related to the set of all known functional circuits. Our analysis also suggests a vital role for the lateral ganglion in processing information, providing an essential connection between the sensory and motor components of the C. elegans nervous system.
NASA Astrophysics Data System (ADS)
Hsieh, Chang-Yu; Cao, Jianshu
2018-01-01
We extend a standard stochastic theory to study open quantum systems coupled to a generic quantum environment. We exemplify the general framework by studying a two-level quantum system coupled bilinearly to the three fundamental classes of non-interacting particles: bosons, fermions, and spins. In this unified stochastic approach, the generalized stochastic Liouville equation (SLE) formally captures the exact quantum dissipations when noise variables with appropriate statistics for different bath models are applied. Anharmonic effects of a non-Gaussian bath are precisely encoded in the bath multi-time correlation functions that noise variables have to satisfy. Starting from the SLE, we devise a family of generalized hierarchical equations by averaging out the noise variables and expand bath multi-time correlation functions in a complete basis of orthonormal functions. The general hierarchical equations constitute systems of linear equations that provide numerically exact simulations of quantum dynamics. For bosonic bath models, our general hierarchical equation of motion reduces exactly to an extended version of hierarchical equation of motion which allows efficient simulation for arbitrary spectral densities and temperature regimes. Similar efficiency and flexibility can be achieved for the fermionic bath models within our formalism. The spin bath models can be simulated with two complementary approaches in the present formalism. (I) They can be viewed as an example of non-Gaussian bath models and be directly handled with the general hierarchical equation approach given their multi-time correlation functions. (II) Alternatively, each bath spin can be first mapped onto a pair of fermions and be treated as fermionic environments within the present formalism.
Royle, J. Andrew; Dorazio, Robert M.
2008-01-01
A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.
Ho, Cheng-Han; Lien, Der-Hsien; Chang, Hung-Chih; Lin, Chin-An; Kang, Chen-Fang; Hsing, Meng-Kai; Lai, Kun-Yu; He, Jr-Hau
2012-12-07
We experimentally and theoretically demonstrated the hierarchical structure of SiO(2) nanorod arrays/p-GaN microdomes as a light harvesting scheme for InGaN-based multiple quantum well solar cells. The combination of nano- and micro-structures leads to increased internal multiple reflection and provides an intermediate refractive index between air and GaN. Cells with the hierarchical structure exhibit improved short-circuit current densities and fill factors, rendering a 1.47 fold efficiency enhancement as compared to planar cells.
Hierarchical and non-hierarchical mineralisation of collagen
Liu, Yan; Kim, Young-Kyung; Dai, Lin; Li, Nan; Khan, Sara; Pashley, David H.; Tay, Franklin R.
2010-01-01
Biomineralisation of collagen involves functional motifs incorporated in extracellular matrix protein molecules to accomplish the objectives of stabilising amorphous calcium phosphate into nanoprecursors and directing the nucleation and growth of apatite within collagen fibrils. Here we report the use of small inorganic polyphosphate molecules to template hierarchical intrafibrillar apatite assembly in reconstituted collagen in the presence of polyacrylic acid to sequester calcium and phosphate into transient amorphous nanophases. The use of polyphosphate without a sequestration analogue resulted only in randomly-oriented extrafibrillar precipitations along the fibrillar surface. Conversely, the use of polyacrylic acid without a templating analogue resulted only in non-hierarchical intrafibrillar mineralisation with continuous apatite strands instead of discrete crystallites. The ability of using simple non-protein molecules to recapitulate different levels of structural hierarchy in mineralised collagen signifies the ultimate simplicity in Nature’s biomineralisation design principles and challenges the need for using more complex recombinant matrix proteins in bioengineering applications. PMID:21040969
On Hierarchical Threshold Access Structures
2010-11-01
One of the recent generalizations of (t, n) secret sharing for hierarchical threshold access structures is given by Tassa, where he answers the...of theoretical background. We give a conceptually simpler alternative for the understanding of the realization of hierarchical threshold access
Abnormal pain perception in patients with Multiple System Atrophy.
Ory-Magne, F; Pellaprat, J; Harroch, E; Galitzsky, M; Rousseau, V; Pavy-Le Traon, A; Rascol, O; Gerdelat, A; Brefel-Courbon, C
2018-03-01
Patients with Parkinson's disease or Multiple System Atrophy frequently experience painful sensations. The few studies investigating pain mechanisms in Multiple System Atrophy patients have reported contradictory results. In our study, we compared pain thresholds in Multiple System Atrophy and Parkinson's disease patients and healthy controls and evaluated the effect of l-DOPA on pain thresholds. We assessed subjective and objective pain thresholds (using a thermotest and RIII reflex), and pain tolerance in OFF and ON conditions, clinical pain, motor and psychological evaluation. Pain was reported in 78.6% of Multiple System Atrophy patients and in 37.5% of Parkinson's disease patients. In the OFF condition, subjective and objective pain thresholds were significantly lower in Multiple System Atrophy patients than in healthy controls (43.8 °C ± 1.3 vs 45.7 °C ± 0.8; p = 0.0005 and 7.4 mA ± 3.8 vs 13.7 mA ± 2.8; p = 0.002, respectively). They were also significantly reduced in Multiple System Atrophy compared to Parkinson's disease patients. No significant difference was found in pain tolerance for the 3 groups and in the effect of l-DOPA on pain thresholds in Multiple System Atrophy and Parkinson's disease patients. In the ON condition, pain tolerance tended to be reduced in Multiple System Atrophy versus Parkinson's disease patients (p = 0.05). Multiple System Atrophy patients had an increase in pain perception compared to Parkinson's disease patients and healthy controls. The l-DOPA effect was similar for pain thresholds in Multiple System Atrophy and Parkinson's disease patients, but tended to worsen pain tolerance in Multiple System Atrophy. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Astionenko, I. O.; Litvinenko, O. I.; Osipova, N. V.; Tuluchenko, G. Ya.; Khomchenko, A. N.
2016-10-01
Recently the interpolation bases of the hierarchical type have been used for the problem solving of the approximation of multiple arguments functions (such as in the finite-element method). In this work the cognitive graphical method of constructing of the hierarchical form bases on the serendipity finite elements is suggested, which allowed to get the alternative bases on a biquadratic finite element from the serendipity family without internal knots' inclusion. The cognitive-graphic method allowed to improve the known interpolation procedure of Taylor and to get the modified elements with irregular arrangement of knots. The proposed procedures are universal and are spread in the area of finite-elements.
Hierarchical structures of amorphous solids characterized by persistent homology
Hiraoka, Yasuaki; Nakamura, Takenobu; Hirata, Akihiko; Escolar, Emerson G.; Matsue, Kaname; Nishiura, Yasumasa
2016-01-01
This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms. Then, specific distributions such as curves and islands in the PDs identify meaningful shape characteristics of the atomic configuration. Although the method can be applied to a wide variety of disordered systems, it is applied here to silica glass, the Lennard-Jones system, and Cu-Zr metallic glass as standard examples of continuous random network and random packing structures. In silica glass, the method classified the atomic rings as short-range and medium-range orders and unveiled hierarchical ring structures among them. These detailed geometric characterizations clarified a real space origin of the first sharp diffraction peak and also indicated that PDs contain information on elastic response. Even in the Lennard-Jones system and Cu-Zr metallic glass, the hierarchical structures in the atomic configurations were derived in a similar way using PDs, although the glass structures and properties substantially differ from silica glass. These results suggest that the PDs provide a unified method that extracts greater depth of geometric information in amorphous solids than conventional methods. PMID:27298351
Urbina, Angel; Mahadevan, Sankaran; Paez, Thomas L.
2012-03-01
Here, performance assessment of complex systems is ideally accomplished through system-level testing, but because they are expensive, such tests are seldom performed. On the other hand, for economic reasons, data from tests on individual components that are parts of complex systems are more readily available. The lack of system-level data leads to a need to build computational models of systems and use them for performance prediction in lieu of experiments. Because their complexity, models are sometimes built in a hierarchical manner, starting with simple components, progressing to collections of components, and finally, to the full system. Quantification of uncertainty inmore » the predicted response of a system model is required in order to establish confidence in the representation of actual system behavior. This paper proposes a framework for the complex, but very practical problem of quantification of uncertainty in system-level model predictions. It is based on Bayes networks and uses the available data at multiple levels of complexity (i.e., components, subsystem, etc.). Because epistemic sources of uncertainty were shown to be secondary, in this application, aleatoric only uncertainty is included in the present uncertainty quantification. An example showing application of the techniques to uncertainty quantification of measures of response of a real, complex aerospace system is included.« less
Hierarchically Structured Non-Intrusive Sign Language Recognition. Chapter 2
NASA Technical Reports Server (NTRS)
Zieren, Jorg; Zieren, Jorg; Kraiss, Karl-Friedrich
2007-01-01
This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.
Hierarchical image segmentation via recursive superpixel with adaptive regularity
NASA Astrophysics Data System (ADS)
Nakamura, Kensuke; Hong, Byung-Woo
2017-11-01
A fast and accurate segmentation algorithm in a hierarchical way based on a recursive superpixel technique is presented. We propose a superpixel energy formulation in which the trade-off between data fidelity and regularization is dynamically determined based on the local residual in the energy optimization procedure. We also present an energy optimization algorithm that allows a pixel to be shared by multiple regions to improve the accuracy and appropriate the number of segments. The qualitative and quantitative evaluations demonstrate that our algorithm, combining the proposed energy and optimization, outperforms the conventional k-means algorithm by up to 29.10% in F-measure. We also perform comparative analysis with state-of-the-art algorithms in the hierarchical segmentation. Our algorithm yields smooth regions throughout the hierarchy as opposed to the others that include insignificant details. Our algorithm overtakes the other algorithms in terms of balance between accuracy and computational time. Specifically, our method runs 36.48% faster than the region-merging approach, which is the fastest of the comparing algorithms, while achieving a comparable accuracy.
Eccentricity growth and orbit flip in near-coplanar hierarchical three-body systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Gongjie; Naoz, Smadar; Kocsis, Bence
2014-04-20
The secular dynamical evolution of a hierarchical three-body system in which a distant third object orbits around a binary has been studied extensively, demonstrating that the inner orbit can undergo large eccentricity and inclination oscillations. It was shown before that starting with a circular inner orbit, large mutual inclination (40°-140°) can produce long timescale modulations that drive the eccentricity to extremely large values and can flip the orbit. Here, we demonstrate that starting with an almost coplanar configuration, for eccentric inner and outer orbits, the eccentricity of the inner orbit can still be excited to high values, and the orbitmore » can flip by ∼180°, rolling over its major axis. The ∼180° flip criterion and the flip timescale are described by simple analytic expressions that depend on the initial orbital parameters. With tidal dissipation, this mechanism can produce counter-orbiting exoplanetary systems. In addition, we also show that this mechanism has the potential to enhance the tidal disruption or collision rates for different systems. Furthermore, we explore the entire e {sub 1} and i {sub 0} parameter space that can produce flips.« less
Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish
2012-01-01
Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable. PMID:22761649
Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish
2012-01-01
Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable.
Hierarchical video summarization
NASA Astrophysics Data System (ADS)
Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.
1998-12-01
We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.
NASA Astrophysics Data System (ADS)
Graham, James; Ternovskiy, Igor V.
2013-06-01
We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.
Biomimetic wall-shaped hierarchical microstructure for gecko-like attachment.
Kasem, Haytam; Tsipenyuk, Alexey; Varenberg, Michael
2015-04-21
Most biological hairy adhesive systems involved in locomotion rely on spatula-shaped terminal elements, whose operation has been actively studied during the last decade. However, though functional principles underlying their amazing performance are now well understood, due to technical difficulties in manufacturing the complex structure of hierarchical spatulate systems, a biomimetic surface structure featuring true shear-induced dynamic attachment still remains elusive. To try bridging this gap, a novel method of manufacturing gecko-like attachment surfaces is devised based on a laser-micromachining technology. This method overcomes the inherent disadvantages of photolithography techniques and opens wide perspectives for future production of gecko-like attachment systems. Advanced smart-performance surfaces featuring thin-film-based hierarchical shear-activated elements are fabricated and found capable of generating friction force of several tens of times the contact load, which makes a significant step forward towards a true gecko-like adhesive.
Hierarchical rendering of trees from precomputed multi-layer z-buffers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Max, N.
1996-02-01
Chen and Williams show how precomputed z-buffer images from different fixed viewing positions can be reprojected to produce an image for a new viewpoint. Here images are precomputed for twigs and branches at various levels in the hierarchical structure of a tree, and adaptively combined, depending on the position of the new viewpoint. The precomputed images contain multiple z levels to avoid missing pixels in the reconstruction, subpixel masks for anti-aliasing, and colors and normals for shading after reprojection.
An effective and secure key-management scheme for hierarchical access control in E-medicine system.
Odelu, Vanga; Das, Ashok Kumar; Goswami, Adrijit
2013-04-01
Recently several hierarchical access control schemes are proposed in the literature to provide security of e-medicine systems. However, most of them are either insecure against 'man-in-the-middle attack' or they require high storage and computational overheads. Wu and Chen proposed a key management method to solve dynamic access control problems in a user hierarchy based on hybrid cryptosystem. Though their scheme improves computational efficiency over Nikooghadam et al.'s approach, it suffers from large storage space for public parameters in public domain and computational inefficiency due to costly elliptic curve point multiplication. Recently, Nikooghadam and Zakerolhosseini showed that Wu-Chen's scheme is vulnerable to man-in-the-middle attack. In order to remedy this security weakness in Wu-Chen's scheme, they proposed a secure scheme which is again based on ECC (elliptic curve cryptography) and efficient one-way hash function. However, their scheme incurs huge computational cost for providing verification of public information in the public domain as their scheme uses ECC digital signature which is costly when compared to symmetric-key cryptosystem. In this paper, we propose an effective access control scheme in user hierarchy which is only based on symmetric-key cryptosystem and efficient one-way hash function. We show that our scheme reduces significantly the storage space for both public and private domains, and computational complexity when compared to Wu-Chen's scheme, Nikooghadam-Zakerolhosseini's scheme, and other related schemes. Through the informal and formal security analysis, we further show that our scheme is secure against different attacks and also man-in-the-middle attack. Moreover, dynamic access control problems in our scheme are also solved efficiently compared to other related schemes, making our scheme is much suitable for practical applications of e-medicine systems.
Oaki, Yuya; Imai, Hiroaki
2005-12-28
A hierarchically organized architecture in multiple scales was generated from potassium hydrogen phthalate crystals and poly(acrylic acid) based on our novel biomimetic approach with an exquisite association of polymers on crystallization.
Hierarchical feature selection for erythema severity estimation
NASA Astrophysics Data System (ADS)
Wang, Li; Shi, Chenbo; Shu, Chang
2014-10-01
At present PASI system of scoring is used for evaluating erythema severity, which can help doctors to diagnose psoriasis [1-3]. The system relies on the subjective judge of doctors, where the accuracy and stability cannot be guaranteed [4]. This paper proposes a stable and precise algorithm for erythema severity estimation. Our contributions are twofold. On one hand, in order to extract the multi-scale redness of erythema, we design the hierarchical feature. Different from traditional methods, we not only utilize the color statistical features, but also divide the detect window into small window and extract hierarchical features. Further, a feature re-ranking step is introduced, which can guarantee that extracted features are irrelevant to each other. On the other hand, an adaptive boosting classifier is applied for further feature selection. During the step of training, the classifier will seek out the most valuable feature for evaluating erythema severity, due to its strong learning ability. Experimental results demonstrate the high precision and robustness of our algorithm. The accuracy is 80.1% on the dataset which comprise 116 patients' images with various kinds of erythema. Now our system has been applied for erythema medical efficacy evaluation in Union Hosp, China.
USDA-ARS?s Scientific Manuscript database
Hyperspectral scattering is a promising technique for rapid and noninvasive measurement of multiple quality attributes of apple fruit. A hierarchical evolutionary algorithm (HEA) approach, in combination with subspace decomposition and partial least squares (PLS) regression, was proposed to select o...
21 CFR 866.5660 - Multiple autoantibodies immunological test system.
Code of Federal Regulations, 2010 CFR
2010-04-01
... SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES Immunological Test Systems § 866.5660 Multiple autoantibodies immunological test system. (a) Identification. A multiple autoantibodies... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Multiple autoantibodies immunological test system...
Protoplanetary Disks in Multiple Star Systems
NASA Astrophysics Data System (ADS)
Harris, Robert J.
Most stars are born in multiple systems, so the presence of a stellar companion may commonly influence planet formation. Theory indicates that companions may inhibit planet formation in two ways. First, dynamical interactions can tidally truncate circumstellar disks. Truncation reduces disk lifetimes and masses, leaving less time and material for planet formation. Second, these interactions might reduce grain-coagulation efficiency, slowing planet formation in its earliest stages. I present three observational studies investigating these issues. First is a spatially resolved Submillimeter Array (SMA) census of disks in young multiple systems in the Taurus-Auriga star-forming region to study their bulk properties. With this survey, I confirmed that disk lifetimes are preferentially decreased in multiples: single stars have detectable millimeter-wave continuum emission twice as often as components of multiples. I also verified that millimeter luminosity (proportional to disk mass) declines with decreasing stellar separation. Furthermore, by measuring resolved-disk radii, I quantitatively tested tidal-truncation theories: results were mixed, with a few disks much larger than expected. I then switch focus to the grain-growth properties of disks in multiple star systems. By combining SMA, Combined Array for Research in Millimeter Astronomy (CARMA), and Jansky Very Large Array (VLA) observations of the circumbinary disk in the UZ Tau quadruple system, I detected radial variations in the grain-size distribution: large particles preferentially inhabit the inner disk. Detections of these theoretically predicted variations have been rare. I related this to models of grain coagulation in gas disks and find that our results are consistent with growth limited by radial drift. I then present a study of grain growth in the disks of the AS 205 and UX Tau multiple systems. By combining SMA, Atacama Large Millimeter/submillimeter Array (ALMA), and VLA observations, I detected radial
NASA Astrophysics Data System (ADS)
Zhang, Jia; Qian, Sheng-Bang; He, Jian-Duo
2017-02-01
Four candidates of eclipsing multiples, based on new extraneous eclipses found on Kepler binary light curves, are presented and studied. KIC 7622486 is a double eclipsing binary candidate with orbital periods of 2.2799960 d and 40.246503 d. The two binary systems do not eclipse each other in the line of sight, but there is mutual gravitational influence between them which leads to the small but definite eccentricity of 0.0035(0.0022) associated with the short 2.2799960 d period orbit. KIC 7668648 is a hierarchical quadruple system candidate, with two sets of solid 203 ± 5 d period extraneous eclipses and another independent set of extraneous eclipses. A clear and credible extraneous eclipse is found on the binary light curve of KIC 7670485 which makes it a triple system candidate. Two sets of extraneous eclipses with periods of about 390 d and 220 d are found on KIC 8938628 binary curves, which not only confirm the previous conclusion of the 388.5 ± 0.3 triple system, but also indicate new additional objects that make KIC 8938628 a hierarchical quadruple system candidate. The results from these four candidates will contribute to the field of eclipsing multiples.
NASA Astrophysics Data System (ADS)
Hoell, Simon; Omenzetter, Piotr
2017-07-01
Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.
Hierarchical Shared Control of Cane-Type Walking-Aid Robot
Tao, Chunjing
2017-01-01
A hierarchical shared-control method of the walking-aid robot for both human motion intention recognition and the obstacle emergency-avoidance method based on artificial potential field (APF) is proposed in this paper. The human motion intention is obtained from the interaction force measurements of the sensory system composed of 4 force-sensing registers (FSR) and a torque sensor. Meanwhile, a laser-range finder (LRF) forward is applied to detect the obstacles and try to guide the operator based on the repulsion force calculated by artificial potential field. An obstacle emergency-avoidance method which comprises different control strategies is also assumed according to the different states of obstacles or emergency cases. To ensure the user's safety, the hierarchical shared-control method combines the intention recognition method with the obstacle emergency-avoidance method based on the distance between the walking-aid robot and the obstacles. At last, experiments validate the effectiveness of the proposed hierarchical shared-control method. PMID:29093805
Hierarchical porous ZnO microflowers with ultra-high ethanol gas-sensing at low concentration
NASA Astrophysics Data System (ADS)
Song, Liming; Yue, He; Li, Haiying; Liu, Li; Li, Yu; Du, Liting; Duan, Haojie; Klyui, N. I.
2018-05-01
Hierarchical porous and non-porous ZnO microflowers have been successfully fabricated by hydrothermal method. Their crystal structure, morphology and gas-sensing properties were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), and chemical gas sensing intelligent analysis system (CGS). Compared with hierarchical non-porous ZnO microflowers, hierarchical porous ZnO microflowers exhibited ultra-high sensitivity with 50 ppm ethanol at 260 °C and the response is 110, which is 1.8 times higher than that of non-porous ZnO microflowers. Moreover, the lowest concentration limit of hierarchical porous ZnO microflowers (non-porous ZnO microflowers) to ethanol is 0.1 (1) ppm, the response value is 1.6 (1).
Conceptual hierarchical modeling to describe wetland plant community organization
Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.
2010-01-01
Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.
Generalized Hill-stability criteria for hierarchical three-body systems at arbitrary inclinations
NASA Astrophysics Data System (ADS)
Grishin, Evgeni; Perets, Hagai B.; Zenati, Yossef; Michaely, Erez
2017-04-01
A fundamental aspect of the three-body problem is its stability. Most stability studies have focused on the co-planar three-body problem, deriving analytic criteria for the dynamical stability of such pro/retrograde systems. Numerical studies of inclined systems phenomenologically mapped their stability regions, but neither complement it by theoretical framework, nor provided satisfactory fit for their dependence on mutual inclinations. Here we present a novel approach to study the stability of hierarchical three-body systems at arbitrary inclinations, which accounts not only for the instantaneous stability of such systems, but also for the secular stability and evolution through Lidov-Kozai cycles and evection. We generalize the Hill-stability criteria to arbitrarily inclined triple systems, explain the existence of quasi-stable regimes and characterize the inclination dependence of their stability. We complement the analytic treatment with an extensive numerical study, to test our analytic results. We find excellent correspondence up to high inclinations (˜120°), beyond which the agreement is marginal. At such high inclinations, the stability radius is larger, the ratio between the outer and inner periods becomes comparable and our secular averaging approach is no longer strictly valid. We therefore combine our analytic results with polynomial fits to the numerical results to obtain a generalized stability formula for triple systems at arbitrary inclinations. Besides providing a generalized secular-based physical explanation for the stability of non-co-planar systems, our results have direct implications for any triple systems and, in particular, binary planets and moon/satellite systems; we briefly discuss the latter as a test case for our models.
Real-time hierarchically distributed processing network interaction simulation
NASA Technical Reports Server (NTRS)
Zimmerman, W. F.; Wu, C.
1987-01-01
The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.
Typical motions in multiple systems
NASA Technical Reports Server (NTRS)
Anosova, Joanna P.
1990-01-01
In very old times, people counted - one, two, many. The author wants to show that they were right. Consider the motions of isolated bodies: (1) N = 1 - simple motion; (2) N = 2 - Keplerian orbits; and (3) N = 3 - this is the difficult problem. In general, this problem can be studied only by computer simulations. The author studied this problem over many years (see, e.g., Agekian and Anosova, 1967; Anosova, 1986, 1989 a,b). The principal result is that two basic types of dynamics take place in triple systems. The first special type is the stable hierarchical systems with two almost Keplerian orbits. The second general type is the unstable triple systems with complicated motions of the bodies. By random choice of the initial conditions, by the Monte-Carlo method, the stable systems comprised about approx. 10% of the examined cases; the unstable systems comprised the other approx. 90% of cases under consideration. In N greater than 3, the studies of dynamics of such systems by computer simulations show that we have in general also the motions roughly as at the cases 1 - 3 with the relative negative or positive energies of the bodies. In the author's picture, the typical trajectories of the bodies in unstable triple systems of the general type of dynamics are seen. Such systems are disrupted always after close triple approaches of the bodies. These approaches play a role like the gravitational slingshot. Often, the velocities of escapers are very large. On the other hand, the movie also shows the dynamical processes of a formation, dynamical evolution and disruption of the temporary wide binaries in triples and a formation of final hard massive binaries in the final evolution of triples.
2007-09-17
been proposed; these include a combination of variable fidelity models, parallelisation strategies and hybridisation techniques (Coello, Veldhuizen et...Coello et al (Coello, Veldhuizen et al. 2002). 4.4.2 HIERARCHICAL POPULATION TOPOLOGY A hierarchical population topology, when integrated into...to hybrid parallel Multi-Objective Evolutionary Algorithms (pMOEA) (Cantu-Paz 2000; Veldhuizen , Zydallis et al. 2003); it uses a master slave
Accurate crop classification using hierarchical genetic fuzzy rule-based systems
NASA Astrophysics Data System (ADS)
Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.
2014-10-01
This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.
Deep convolutional neural network based antenna selection in multiple-input multiple-output system
NASA Astrophysics Data System (ADS)
Cai, Jiaxin; Li, Yan; Hu, Ying
2018-03-01
Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.
Chen, Yongsheng; Persaud, Bhagwant
2014-09-01
Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhao, Jing; Wong, Pak Kin; Ma, Xinbo; Xie, Zhengchao
2017-01-01
This paper proposes a novel integrated controller with three-layer hierarchical structure to coordinate the interactions among active suspension system (ASS), active front steering (AFS) and direct yaw moment control (DYC). First of all, a 14-degree-of-freedom nonlinear vehicle dynamic model is constructed. Then, an upper layer is designed to calculate the total corrected moment for ASS and intermediate layer based on linear moment distribution. By considering the working regions of the AFS and DYC, the intermediate layer is functionalised to determine the trigger signal for the lower layer with corresponding weights. The lower layer is utilised to separately trace the desired value of each local controller and achieve the local control objectives of each subsystem. Simulation results show that the proposed three-layer hierarchical structure is effective in handling the working region of the AFS and DYC, while the quasi-experimental result shows that the proposed integrated controller is able to improve the lateral and vertical dynamics of the vehicle effectively as compared with a conventional electronic stability controller.
An Energy Efficient Cooperative Hierarchical MIMO Clustering Scheme for Wireless Sensor Networks
Nasim, Mehwish; Qaisar, Saad; Lee, Sungyoung
2012-01-01
In this work, we present an energy efficient hierarchical cooperative clustering scheme for wireless sensor networks. Communication cost is a crucial factor in depleting the energy of sensor nodes. In the proposed scheme, nodes cooperate to form clusters at each level of network hierarchy ensuring maximal coverage and minimal energy expenditure with relatively uniform distribution of load within the network. Performance is enhanced by cooperative multiple-input multiple-output (MIMO) communication ensuring energy efficiency for WSN deployments over large geographical areas. We test our scheme using TOSSIM and compare the proposed scheme with cooperative multiple-input multiple-output (CMIMO) clustering scheme and traditional multihop Single-Input-Single-Output (SISO) routing approach. Performance is evaluated on the basis of number of clusters, number of hops, energy consumption and network lifetime. Experimental results show significant energy conservation and increase in network lifetime as compared to existing schemes. PMID:22368459
NASA Astrophysics Data System (ADS)
Sang, Lixia; Zhao, Yangbo; Niu, Youchen; Bai, Guangmei
2018-02-01
TiO2 with Nanoring/Nanotube (R/T) hierarchical structure can be prepared by tuning the oxidation time and oxidation voltage in the second step anodization. The resulting multiabsorption oscillating peaks in the visible light region present a strong dependence on the tube length which are derived from the interference of light reflected from the top nanorings and the bottom Ti substrate, and the optical path length in TiO2 R/T hierarchical structure can be estimated as about 2 μm. The tube length of the as-prepared TiO2 photoelectrode affects greatly its saturation photocurrent density, and the different tube-wall thickness can change the photocurrent-saturation potential. Under simulated AM 1.5 irradiation (100 mW/cm2), TiO2 R/T hierarchical structure with tube diameters of 20-40 nm and tube length of about 1.5 μm shows higher photocurrent density and hydrogen production rate at the bias of 0 V (vs. Ag/AgCl). The results from the IPCE plots and I-t curves verify that TiO2 R/T hierarchical structure can exhibit the visible light activity, which is more related to the absorption induced by the defects rather than oscillating peaks. Based on the unique multiple light reflection in TiO2 R/T hierarchical structure, surface treatment will pave a way for the better utilization of oscillating peaks in the visible light region.
Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong
2010-01-01
Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information
Superhydrophobicity of Hierarchical and ZNO Nanowire Coatings
2014-01-01
AFRL-RX-WP-TP-2014-0141 SUPERHYDROPHOBICITY OF HIERARCHICAL ZNO NANOWIRE COATINGS (POSTPRINT) Shin Mou AFRL/RXAN JANUARY... SUPERHYDROPHOBICITY OF HIERARCHICAL ZNO NANOWIRE COATINGS (POSTPRINT) 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...or disclose the work. The final publication is available at www.rsc.org/MaterialsA. 14. ABSTRACT Hierarchical superhydrophobic surfaces were
Why We (Usually) Don't Have to Worry about Multiple Comparisons
ERIC Educational Resources Information Center
Gelman, Andrew; Hill, Jennifer; Yajima, Masanao
2012-01-01
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies these corrections. Moreover we posit that the problem of multiple comparisons can disappear entirely when viewed from a hierarchical Bayesian…
Stability and Evolution of Multiple Planet and Satellite Systems
NASA Astrophysics Data System (ADS)
Quillen, Alice
Numerous multiple planet systems have recently been discovered with the Kepler Mission, suggesting that multiple planet systems are common. Multiple- body nearly coplanar satellite systems are also found in the Solar system. Multiple planet and satellite systems exhibit rich dynamics as they are affected by three-body and secular resonances affecting short timescale behavior and long timescale stability. Interactions with debris disks and planetesimal belts and tidal interactions can both reduce and induce instability. Using both numerical and analytical studies, we propose to develop a broadly applicable framework to estimate diffusion rates and stability regimes both in resonant and non- resonant configurations. Understanding of resonant dynamics is needed to understand each of these systems and a broader general theory would cover scenarios and mechanisms that are relevant for all of them. Architectures and dynamical mechanisms will be used to test scenarios for formation and evolution of multiple body systems and constrain poorly known quantities such as masses, eccentricities, inclinations, radii, and the existence of undetected bodies.
Assessing exposure to violence using multiple informants: application of hierarchical linear model.
Kuo, M; Mohler, B; Raudenbush, S L; Earls, F J
2000-11-01
The present study assesses the effects of demographic risk factors on children's exposure to violence (ETV) and how these effects vary by informants. Data on exposure to violence of 9-, 12-, and 15-year-olds were collected from both child participants (N = 1880) and parents (N = 1776), as part of the assessment of the Project on Human Development in Chicago Neighborhoods (PHDCN). A two-level hierarchical linear model (HLM) with multivariate outcomes was employed to analyze information obtained from these two different groups of informants. The findings indicate that parents generally report less ETV than do their children and that associations of age, gender, and parent education with ETV are stronger in the self-reports than in the parent reports. The findings support a multivariate approach when information obtained from different sources is being integrated. The application of HLM allows an assessment of interactions between risk factors and informants and uses all available data, including data from one informant when data from the other informant is missing.
2010-09-01
SIMULATION OF DISADVANTAGED RECEIVERS FOR MULTIPLE-INPUT MULTIPLE- OUTPUT COMMUNICATIONS SYSTEMS by Tracy A. Martin September 2010 Thesis...DATE September 2010 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Analysis and Simulation of Disadvantaged Receivers...Channel State Information at the Transmitter (CSIT). A disadvantaged receiver is subsequently introduced to the system lacking the optimization enjoyed
Wei Wu; James Clark; James Vose
2010-01-01
Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model â GR4J â by coherently assimilating the uncertainties from the...
The Advantages of Hierarchical Linear Modeling. ERIC/AE Digest.
ERIC Educational Resources Information Center
Osborne, Jason W.
This digest introduces hierarchical data structure, describes how hierarchical models work, and presents three approaches to analyzing hierarchical data. Hierarchical, or nested data, present several problems for analysis. People or creatures that exist within hierarchies tend to be more similar to each other than people randomly sampled from the…
Hierarchical Rhetorical Sentence Categorization for Scientific Papers
NASA Astrophysics Data System (ADS)
Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.
2018-03-01
Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.
Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging.
Zald, David H; Lahey, Benjamin B
2017-05-01
Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior.
Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging
Zald, David H.; Lahey, Benjamin B.
2017-01-01
Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior. PMID:28713866
Hierarchical relaxation dynamics in a tilted two-band Bose-Hubbard model
NASA Astrophysics Data System (ADS)
Cosme, Jayson G.
2018-04-01
We numerically examine slow and hierarchical relaxation dynamics of interacting bosons described by a tilted two-band Bose-Hubbard model. The system is found to exhibit signatures of quantum chaos within the spectrum and the validity of the eigenstate thermalization hypothesis for relevant physical observables is demonstrated for certain parameter regimes. Using the truncated Wigner representation in the semiclassical limit of the system, dynamics of relevant observables reveal hierarchical relaxation and the appearance of prethermalized states is studied from the perspective of statistics of the underlying mean-field trajectories. The observed prethermalization scenario can be attributed to different stages of glassy dynamics in the mode-time configuration space due to dynamical phase transition between ergodic and nonergodic trajectories.
Mastering algebra retrains the visual system to perceive hierarchical structure in equations.
Marghetis, Tyler; Landy, David; Goldstone, Robert L
2016-01-01
Formal mathematics is a paragon of abstractness. It thus seems natural to assume that the mathematical expert should rely more on symbolic or conceptual processes, and less on perception and action. We argue instead that mathematical proficiency relies on perceptual systems that have been retrained to implement mathematical skills. Specifically, we investigated whether the visual system-in particular, object-based attention-is retrained so that parsing algebraic expressions and evaluating algebraic validity are accomplished by visual processing. Object-based attention occurs when the visual system organizes the world into discrete objects, which then guide the deployment of attention. One classic signature of object-based attention is better perceptual discrimination within, rather than between, visual objects. The current study reports that object-based attention occurs not only for simple shapes but also for symbolic mathematical elements within algebraic expressions-but only among individuals who have mastered the hierarchical syntax of algebra. Moreover, among these individuals, increased object-based attention within algebraic expressions is associated with a better ability to evaluate algebraic validity. These results suggest that, in mastering the rules of algebra, people retrain their visual system to represent and evaluate abstract mathematical structure. We thus argue that algebraic expertise involves the regimentation and reuse of evolutionarily ancient perceptual processes. Our findings implicate the visual system as central to learning and reasoning in mathematics, leading us to favor educational approaches to mathematics and related STEM fields that encourage students to adapt, not abandon, their use of perception.
Exoplanet orbital eccentricity: multiplicity relation and the Solar System.
Limbach, Mary Anne; Turner, Edwin L
2015-01-06
The known population of exoplanets exhibits a much wider range of orbital eccentricities than Solar System planets and has a much higher average eccentricity. These facts have been widely interpreted to indicate that the Solar System is an atypical member of the overall population of planetary systems. We report here on a strong anticorrelation of orbital eccentricity with multiplicity (number of planets in the system) among cataloged radial velocity (RV) systems. The mean, median, and rough distribution of eccentricities of Solar System planets fits an extrapolation of this anticorrelation to the eight-planet case rather precisely despite the fact that no more than two Solar System planets would be detectable with RV data comparable to that in the exoplanet sample. Moreover, even if regarded as a single or double planetary system, the Solar System lies in a reasonably heavily populated region of eccentricity-multiplicity space. Thus, the Solar System is not anomalous among known exoplanetary systems with respect to eccentricities when its multiplicity is taken into account. Specifically, as the multiplicity of a system increases, the eccentricity decreases roughly as a power law of index -1.20. A simple and plausible but ad hoc and model-dependent interpretation of this relationship implies that ∼ 80% of the one-planet and 25% of the two-planet systems in our sample have additional, as yet undiscovered, members but that systems of higher observed multiplicity are largely complete (i.e., relatively rarely contain additional undiscovered planets). If low eccentricities indeed favor high multiplicities, habitability may be more common in systems with a larger number of planets.
Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.
Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong
Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep
Telerobotic management system: coordinating multiple human operators with multiple robots
NASA Astrophysics Data System (ADS)
King, Jamie W.; Pretty, Raymond; Brothers, Brendan; Gosine, Raymond G.
2003-09-01
This paper describes an application called the Tele-robotic management system (TMS) for coordinating multiple operators with multiple robots for applications such as underground mining. TMS utilizes several graphical interfaces to allow the user to define a partially ordered plan for multiple robots. This plan is then converted to a Petri net for execution and monitoring. TMS uses a distributed framework to allow robots and operators to easily integrate with the applications. This framework allows robots and operators to join the network and advertise their capabilities through services. TMS then decides whether tasks should be dispatched to a robot or a remote operator based on the services offered by the robots and operators.
A hierarchical approach for simulating northern forest dynamics
Don C. Bragg; David W. Roberts; Thomas R. Crow
2004-01-01
Complexity in ecological systems has challenged forest simulation modelers for years, resulting in a number of approaches with varying degrees of success. Arguments in favor of hierarchical modeling are made, especially for considering a complex environmental issue like widespread eastern hemlock regeneration failure. We present the philosophy and basic framework for...
Applying Hierarchical Model Calibration to Automatically Generated Items.
ERIC Educational Resources Information Center
Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.
This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…
Biomimetic Hierarchical Assembly of Helical Supraparticles from Chiral Nanoparticles
Zhou, Yunlong; Marson, Ryan L.; van Anders, Greg; ...
2016-02-22
Chiroptical materials found in butterflies, beetles, stomatopod crustaceans, and other creatures are attributed to biocomposites with helical motifs and multiscale hierarchical organization. These structurally sophisticated materials self-assemble from primitive nanoscale building blocks, a process that is simpler and more energy efficient than many top-down methods currently used to produce similarly sized three-dimensional materials. In this paper, we report that molecular-scale chirality of a CdTe nanoparticle surface can be translated to nanoscale helical assemblies, leading to chiroptical activity in the visible electromagnetic range. Chiral CdTe nanoparticles coated with cysteine self-organize around Te cores to produce helical supraparticles. D-/L-Form of the aminomore » acid determines the dominant left/right helicity of the supraparticles. Coarse-grained molecular dynamics simulations with a helical pair-potential confirm the assembly mechanism and the origin of its enantioselectivity, providing a framework for engineering three-dimensional chiral materials by self-assembly. Finally, the helical supraparticles further self-organize into lamellar crystals with liquid crystalline order, demonstrating the possibility of hierarchical organization and with multiple structural motifs and length scales determined by molecular-scale asymmetry of nanoparticle interactions.« less
RESONANT POST-NEWTONIAN ECCENTRICITY EXCITATION IN HIERARCHICAL THREE-BODY SYSTEMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Naoz, Smadar; Kocsis, Bence; Loeb, Abraham
2013-08-20
We study the secular, hierarchical three-body problem to first-order in a post-Newtonian expansion of general relativity (GR). We expand the first-order post-Newtonian Hamiltonian to leading-order in the ratio of the semi-major axis of the two orbits. In addition to the well-known terms that correspond to the GR precession of the inner and outer orbits, we find a new secular post-Newtonian interaction term that can affect the long-term evolution of the triple. We explore the parameter space for highly inclined and eccentric systems, where the Kozai-Lidov mechanism can produce large-amplitude oscillations in the eccentricities. The standard lore, i.e., that GR effectsmore » suppress eccentricity, is only consistent with the parts of phase space where the GR timescales are several orders of magnitude shorter than the secular Newtonian one. In other parts of phase space, however, post-Newtonian corrections combined with the three-body ones can excite eccentricities. In particular, for systems where the GR timescale is comparable to the secular Newtonian timescales, the three-body interactions give rise to a resonant-like eccentricity excitation. Furthermore, for triples with a comparable-mass inner binary, where the eccentric Kozai-Lidov mechanism is suppressed, post-Newtonian corrections can further increase the eccentricity and lead to orbital flips even when the timescale of the former is much longer than the timescale of the secular Kozai-Lidov quadrupole perturbations.« less
Linear regulator design for stochastic systems by a multiple time scales method
NASA Technical Reports Server (NTRS)
Teneketzis, D.; Sandell, N. R., Jr.
1976-01-01
A hierarchically-structured, suboptimal controller for a linear stochastic system composed of fast and slow subsystems is considered. The controller is optimal in the limit as the separation of time scales of the subsystems becomes infinite. The methodology is illustrated by design of a controller to suppress the phugoid and short period modes of the longitudinal dynamics of the F-8 aircraft.
Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael
2013-03-27
Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.
Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew
2013-01-01
Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092
Processing of hierarchical syntactic structure in music.
Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian
2013-09-17
Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.
Genetics Home Reference: multiple system atrophy
... inability to hold the body upright and balanced (postural instability). The other type of multiple system atrophy , ... cells in parts of the nervous system that control movement, balance and coordination, and autonomic functioning. The ...
Star formation in a hierarchical model for Cloud Complexes
NASA Astrophysics Data System (ADS)
Sanchez, N.; Parravano, A.
The effects of the external and initial conditions on the star formation processes in Molecular Cloud Complexes are examined in the context of a schematic model. The model considers a hierarchical system with five predefined phases: warm gas, neutral gas, low density molecular gas, high density molecular gas and protostars. The model follows the mass evolution of each substructure by computing its mass exchange with their parent and children. The parent-child mass exchange depends on the radiation density at the interphase, which is produced by the radiation coming from the stars that form at the end of the hierarchical structure, and by the external radiation field. The system is chaotic in the sense that its temporal evolution is very sensitive to small changes in the initial or external conditions. However, global features such as the star formation efficience and the Initial Mass Function are less affected by those variations.
The relational database model and multiple multicenter clinical trials.
Blumenstein, B A
1989-12-01
The Southwest Oncology Group (SWOG) chose to use a relational database management system (RDBMS) for the management of data from multiple clinical trials because of the underlying relational model's inherent flexibility and the natural way multiple entity types (patients, studies, and participants) can be accommodated. The tradeoffs to using the relational model as compared to using the hierarchical model include added computing cycles due to deferred data linkages and added procedural complexity due to the necessity of implementing protections against referential integrity violations. The SWOG uses its RDBMS as a platform on which to build data operations software. This data operations software, which is written in a compiled computer language, allows multiple users to simultaneously update the database and is interactive with respect to the detection of conditions requiring action and the presentation of options for dealing with those conditions. The relational model facilitates the development and maintenance of data operations software.
The Case for a Hierarchical Cosmology
ERIC Educational Resources Information Center
Vaucouleurs, G. de
1970-01-01
The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)
Exoplanet orbital eccentricity: Multiplicity relation and the Solar System
Limbach, Mary Anne; Turner, Edwin L.
2015-01-01
The known population of exoplanets exhibits a much wider range of orbital eccentricities than Solar System planets and has a much higher average eccentricity. These facts have been widely interpreted to indicate that the Solar System is an atypical member of the overall population of planetary systems. We report here on a strong anticorrelation of orbital eccentricity with multiplicity (number of planets in the system) among cataloged radial velocity (RV) systems. The mean, median, and rough distribution of eccentricities of Solar System planets fits an extrapolation of this anticorrelation to the eight-planet case rather precisely despite the fact that no more than two Solar System planets would be detectable with RV data comparable to that in the exoplanet sample. Moreover, even if regarded as a single or double planetary system, the Solar System lies in a reasonably heavily populated region of eccentricity−multiplicity space. Thus, the Solar System is not anomalous among known exoplanetary systems with respect to eccentricities when its multiplicity is taken into account. Specifically, as the multiplicity of a system increases, the eccentricity decreases roughly as a power law of index –1.20. A simple and plausible but ad hoc and model-dependent interpretation of this relationship implies that ∼80% of the one-planet and 25% of the two-planet systems in our sample have additional, as yet undiscovered, members but that systems of higher observed multiplicity are largely complete (i.e., relatively rarely contain additional undiscovered planets). If low eccentricities indeed favor high multiplicities, habitability may be more common in systems with a larger number of planets. PMID:25512527
Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.
Li, Yasong; Gates, Byron D; Menon, Carlo
2015-08-05
The gecko relies on van der Waals forces to cling onto surfaces with a variety of topography and composition. The hierarchical fibrillar structures on their climbing feet, ranging from mesoscale to nanoscale, are hypothesized to be key elements for the animal to conquer both smooth and rough surfaces. An epoxy-based artificial hierarchical fibrillar adhesive was prepared to study the influence of the hierarchical structures on the properties of a dry adhesive. The presented experiments highlight the advantages of a hierarchical structure despite a reduction of overall density and aspect ratio of nanofibrils. In contrast to an adhesive containing only nanometer-size fibrils, the hierarchical fibrillar adhesives exhibited a higher adhesion force and better compliancy when tested on an identical substrate.
A Hierarchical Bayesian Model for Crowd Emotions
Urizar, Oscar J.; Baig, Mirza S.; Barakova, Emilia I.; Regazzoni, Carlo S.; Marcenaro, Lucio; Rauterberg, Matthias
2016-01-01
Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the behavior of individuals and of the crowd as a single entity, and explore the relation between behavior and emotions to infer emotional states. Information about the motion patterns of individuals are described using a self-organizing map, and a hierarchical Bayesian network builds probabilistic models to identify behaviors and infer the emotional state of individuals and the crowd. This model is trained and tested using data produced from simulated scenarios that resemble real-life environments. The conducted experiments tested the efficiency of our method to learn, detect and associate behaviors with emotional states yielding accuracy levels of 74% for individuals and 81% for the crowd, similar in performance with existing methods for pedestrian behavior detection but with novel concepts regarding the analysis of crowds. PMID:27458366
Multiple operating system rotation environment moving target defense
DOE Office of Scientific and Technical Information (OSTI.GOV)
Evans, Nathaniel; Thompson, Michael
Systems and methods for providing a multiple operating system rotation environment ("MORE") moving target defense ("MTD") computing system are described. The MORE-MTD system provides enhanced computer system security through a rotation of multiple operating systems. The MORE-MTD system increases attacker uncertainty, increases the cost of attacking the system, reduces the likelihood of an attacker locating a vulnerability, and reduces the exposure time of any located vulnerability. The MORE-MTD environment is effectuated by rotation of the operating systems at a given interval. The rotating operating systems create a consistently changing attack surface for remote attackers.
Adaptations in a hierarchical food web of southeastern Lake Michigan
Krause, Ann E.; Frank, Ken A.; Jones, Michael L.; Nalepa, Thomas F.; Barbiero, Richard P.; Madenjian, Charles P.; Agy, Megan; Evans, Marlene S.; Taylor, William W.; Mason, Doran M.; Léonard, Nancy J.
2009-01-01
Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more
Anisotropic and Hierarchical Porosity in Multifunctional Ceramics
NASA Astrophysics Data System (ADS)
Lichtner, Aaron Zev
The performance of multifunctional porous ceramics is often hindered by the seemingly contradictory effects of porosity on both mechanical and non-structural properties and yet a sufficient body of knowledge linking microstructure to these properties does not exist. Using a combination of tailored anisotropic and hierarchical materials, these disparate effects may be reconciled. In this project, a systematic investigation of the processing, characterization and properties of anisotropic and isotropic hierarchically porous ceramics was conducted. The system chosen was a composite ceramic intended as the cathode for a solid oxide fuel cell (SOFC). Comprehensive processing investigations led to the development of approaches to make hierarchical, anisotropic porous microstructures using directional freeze-casting of well dispersed slurries. The effect of all the important processing parameters was investigated. This resulted in an ability to tailor and control the important microstructural features including the scale of the microstructure, the macropore size and total porosity. Comparable isotropic porous ceramics were also processed using fugitive pore formers. A suite of characterization techniques including x-ray tomography and 3-D sectional scanning electron micrographs (FIB-SEM) was used to characterize and quantify the green and partially sintered microstructures. The effect of sintering temperature on the microstructure was quantified and discrete element simulations (DEM) were used to explain the experimental observations. Finally, the comprehensive mechanical properties, at room temperature, were investigated, experimentally and using DEM, for the different microstructures.
The mathematical relationship between Zipf’s law and the hierarchical scaling law
NASA Astrophysics Data System (ADS)
Chen, Yanguang
2012-06-01
The empirical studies of city-size distribution show that Zipf's law and the hierarchical scaling law are linked in many ways. The rank-size scaling and hierarchical scaling seem to be two different sides of the same coin, but their relationship has never been revealed by strict mathematical proof. In this paper, the Zipf's distribution of cities is abstracted as a q-sequence. Based on this sequence, a self-similar hierarchy consisting of many levels is defined and the numbers of cities in different levels form a geometric sequence. An exponential distribution of the average size of cities is derived from the hierarchy. Thus we have two exponential functions, from which follows a hierarchical scaling equation. The results can be statistically verified by simple mathematical experiments and observational data of cities. A theoretical foundation is then laid for the conversion from Zipf's law to the hierarchical scaling law, and the latter can show more information about city development than the former. Moreover, the self-similar hierarchy provides a new perspective for studying networks of cities as complex systems. A series of mathematical rules applied to cities such as the allometric growth law, the 2n principle and Pareto's law can be associated with one another by the hierarchical organization.
NASA Astrophysics Data System (ADS)
Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.
2016-02-01
The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.
Delegation control of multiple unmanned systems
NASA Astrophysics Data System (ADS)
Flaherty, Susan R.; Shively, Robert J.
2010-04-01
Maturing technologies and complex payloads coupled with a future objective to reduce the logistics burden of current unmanned aerial systems (UAS) operations require a change to the 2-crew employment paradigm. Increased automation and operator supervisory control of unmanned systems have been advocated to meet the objective of reducing the crew requirements, while managing future technologies. Specifically, a delegation control employment strategy has resulted in reduced workload and higher situation awareness for single operators controlling multiple unmanned systems in empirical studies1,2. Delegation control is characterized by the ability for an operator to call a single "play" that initiates prescribed default actions for each vehicle and associated sensor related to a common mission goal. Based upon the effectiveness of delegation control in simulation, the U.S. Army Aeroflightdynamics Directorate (AFDD) developed a Delegation Control (DelCon) operator interface with voice recognition implementation for play selection, real-time play modification, and play status with automation transparency to enable single operator control of multiple unmanned systems in flight. AFDD successfully demonstrated delegation control in a Troops-in-Contact mission scenario at Ft. Ord in 2009. This summary showcases the effort as a beneficial advance in single operator control of multiple UAS.
Asymptotic analysis of hierarchical martensitic microstructure
NASA Astrophysics Data System (ADS)
Cesana, Pierluigi; Porta, Marcel; Lookman, Turab
2014-12-01
We consider a hierarchical nested microstructure, which also contains a point of singularity (disclination) at the origin, observed in lead orthovanadate. We show how to exactly compute the energy cost and associated displacement field within linearized elasticity by enforcing geometric compatibility of strains across interfaces of the three-phase mixture of distortions (variants) in the microstructure. We prove that the mechanical deformation is purely elastic and discuss the behavior of the system close to the origin.
A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context
NASA Astrophysics Data System (ADS)
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
NASA Astrophysics Data System (ADS)
Xu, Xing; Zhou, Kongkang; Zou, Nannan; Jiang, Hong; Cui, Xiaoli
2015-09-01
The current research of air suspension mainly focuses on the characteristics and design of the air spring. In fact, electronically controlled air suspension (ECAS) has excellent performance in flexible height adjustment during different driving conditions. However, the nonlinearity of the ride height adjusting system and the uneven distribution of payload affect the control accuracy of ride height and the body attitude. Firstly, the three-point measurement system of three height sensors is used to establish the mathematical model of the ride height adjusting system. The decentralized control of ride height and the centralized control of body attitude are presented to design the ride height control system for ECAS. The exact feedback linearization method is adopted for the nonlinear mathematical model of the ride height system. Secondly, according to the hierarchical control theory, the variable structure control (VSC) technique is used to design a controller that is able to adjust the ride height for the quarter-vehicle anywhere, and each quarter-vehicle height control system is independent. Meanwhile, the three-point height signals obtained by three height sensors are tracked to calculate the body pitch and roll attitude over time, and then by calculating the deviation of pitch and roll and its rates, the height control correction is reassigned based on the fuzzy algorithm. Finally, to verify the effectiveness and performance of the proposed combined control strategy, a validating test of ride height control system with and without road disturbance is carried out. Testing results show that the height adjusting time of both lifting and lowering is over 5 s, and the pitch angle and the roll angle of body attitude are less than 0.15°. This research proposes a hierarchical control method that can guarantee the attitude stability, as well as satisfy the ride height tracking system.
Hierarchical control of procedural and declarative category-learning systems
Turner, Benjamin O.; Crossley, Matthew J.; Ashby, F. Gregory
2017-01-01
Substantial evidence suggests that human category learning is governed by the interaction of multiple qualitatively distinct neural systems. In this view, procedural memory is used to learn stimulus-response associations, and declarative memory is used to apply explicit rules and test hypotheses about category membership. However, much less is known about the interaction between these systems: how is control passed between systems as they interact to influence motor resources? Here, we used fMRI to elucidate the neural correlates of switching between procedural and declarative categorization systems. We identified a key region of the cerebellum (left Crus I) whose activity was bidirectionally modulated depending on switch direction. We also identified regions of the default mode network (DMN) that were selectively connected to left Crus I during switching. We propose that the cerebellum—in coordination with the DMN—serves a critical role in passing control between procedural and declarative memory systems. PMID:28213114
Multiple-Primitives Hierarchical Classification of Airborne Laser Scanning Data in Urban Areas
NASA Astrophysics Data System (ADS)
Ni, H.; Lin, X. G.; Zhang, J. X.
2017-09-01
A hierarchical classification method for Airborne Laser Scanning (ALS) data of urban areas is proposed in this paper. This method is composed of three stages among which three types of primitives are utilized, i.e., smooth surface, rough surface, and individual point. In the first stage, the input ALS data is divided into smooth surfaces and rough surfaces by employing a step-wise point cloud segmentation method. In the second stage, classification based on smooth surfaces and rough surfaces is performed. Points in the smooth surfaces are first classified into ground and buildings based on semantic rules. Next, features of rough surfaces are extracted. Then, points in rough surfaces are classified into vegetation and vehicles based on the derived features and Random Forests (RF). In the third stage, point-based features are extracted for the ground points, and then, an individual point classification procedure is performed to classify the ground points into bare land, artificial ground and greenbelt. Moreover, the shortages of the existing studies are analyzed, and experiments show that the proposed method overcomes these shortages and handles more types of objects.
Leadership styles across hierarchical levels in nursing departments.
Stordeur, S; Vandenberghe, C; D'hoore, W
2000-01-01
Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.
NASA Astrophysics Data System (ADS)
Vallé, Karine; Belleville, Philippe; Pereira, Franck; Sanchez, Clément
2006-02-01
The elaborate performances characterizing natural materials result from functional hierarchical constructions at scales ranging from nanometres to millimetres, each construction allowing the material to fit the physical or chemical demands occurring at these different levels. Hierarchically structured materials start to demonstrate a high input in numerous promising applied domains such as sensors, catalysis, optics, fuel cells, smart biologic and cosmetic vectors. In particular, hierarchical hybrid materials permit the accommodation of a maximum of elementary functions in a small volume, thereby optimizing complementary possibilities and properties between inorganic and organic components. The reported strategies combine sol-gel chemistry, self-assembly routes using templates that tune the material's architecture and texture with the use of larger inorganic, organic or biological templates such as latex, organogelator-derived fibres, nanolithographic techniques or controlled phase separation. We propose an approach to forming transparent hierarchical hybrid functionalized membranes using in situ generation of mesostructured hybrid phases inside a non-porogenic hydrophobic polymeric host matrix. We demonstrate that the control of the multiple affinities existing between organic and inorganic components allows us to design the length-scale partitioning of hybrid nanomaterials with tuned functionalities and desirable size organization from ångström to centimetre. After functionalization of the mesoporous hybrid silica component, the resulting membranes have good ionic conductivity offering interesting perspectives for the design of solid electrolytes, fuel cells and other ion-transport microdevices.
Wang, Shoupei; Zhang, Jianan; Shang, Pei; Li, Yuanyuan; Chen, Zhimin; Xu, Qun
2014-10-18
N-doped carbon spheres with hierarchical micropore-nanosheet networks (HPSCSs) were facilely fabricated by a one-step carbonization and activation process of N containing polymer spheres by KOH. With the synergy effect of the multiple structures, HPSCSs exhibit a very high specific capacitance of 407.9 F g(-1) at 1 mV s(-1) (1.2 times higher than that of porous carbon spheres) and a robust cycling stability for supercapacitors.
Hierarchical optimal control of large-scale nonlinear chemical processes.
Ramezani, Mohammad Hossein; Sadati, Nasser
2009-01-01
In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.
A hierarchical anatomical classification schema for prediction of phenotypic side effects.
Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh
2018-01-01
Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.
Using the Language of Sets to Describe Nested Systems in Emergy Evaluations
The language of set theory has been recently used to describe the emergy evaluation of a process. In this paper this mathematical language is used as a guide to evaluate the emergy of nested systems. We analyze a territorial system on multiple scales as an example of hierarchical...
Pauly, Hannah M; Sathy, Binulal N; Olvera, Dinorath; McCarthy, Helen O; Kelly, Daniel J; Popat, Ketul C; Dunne, Nicholas J; Haut Donahue, Tammy Lynn
2017-08-01
The anterior cruciate ligament (ACL) of the knee is vital for proper joint function and is commonly ruptured during sports injuries or car accidents. Due to a lack of intrinsic healing capacity and drawbacks with allografts and autografts, there is a need for a tissue-engineered ACL replacement. Our group has previously used aligned sheets of electrospun polycaprolactone nanofibers to develop solid cylindrical bundles of longitudinally aligned nanofibers. We have shown that these nanofiber bundles support cell proliferation and elongation and the hierarchical structure and material properties are similar to the native human ACL. It is possible to combine multiple nanofiber bundles to create a scaffold that attempts to mimic the macroscale structure of the ACL. The goal of this work was to develop a hierarchical bioactive scaffold for ligament tissue engineering using connective tissue growth factor (CTGF)-conjugated nanofiber bundles and evaluate the behavior of mesenchymal stem cells (MSCs) on these scaffolds in vitro and in vivo. CTGF was immobilized onto the surface of individual nanofiber bundles or scaffolds consisting of multiple nanofiber bundles. The conjugation efficiency and the release of conjugated CTGF were assessed using X-ray photoelectron spectroscopy, assays, and immunofluorescence staining. Scaffolds were seeded with MSCs and maintained in vitro for 7 days (individual nanofiber bundles), in vitro for 21 days (scaled-up scaffolds of 20 nanofiber bundles), or in vivo for 6 weeks (small scaffolds of 4 nanofiber bundles), and ligament-specific tissue formation was assessed in comparison to non-CTGF-conjugated control scaffolds. Results showed that CTGF conjugation encouraged cell proliferation and ligament-specific tissue formation in vitro and in vivo. The results suggest that hierarchical electrospun nanofiber bundles conjugated with CTGF are a scalable and bioactive scaffold for ACL tissue engineering.
Li, Xiangwei; Ma, Chi; Xie, Xiaohua; Sun, Hongchen; Liu, Xiaohua
2016-04-15
While pulp regeneration using tissue engineering strategy has been explored for over a decade, successful regeneration of pulp tissues in a full-length human root with a one-end seal that truly simulates clinical endodontic treatment has not been achieved. To address this challenge, we designed and synthesized a unique hierarchical growth factor-loaded nanofibrous microsphere scaffolding system. In this system, vascular endothelial growth factor (VEGF) binds with heparin and is encapsulated in heparin-conjugated gelatin nanospheres, which are further immobilized in the nanofibers of an injectable poly(l-lactic acid) (PLLA) microsphere. This hierarchical microsphere system not only protects the VEGF from denaturation and degradation, but also provides excellent control of its sustained release. In addition, the nanofibrous PLLA microsphere integrates the extracellular matrix-mimicking architecture with a highly porous injectable form, efficiently accommodating dental pulp stem cells (DPSCs) and supporting their proliferation and pulp tissue formation. Our in vivo study showed the successful regeneration of pulp-like tissues that fulfilled the entire apical and middle thirds and reached the coronal third of the full-length root canal. In addition, a large number of blood vessels were regenerated throughout the canal. For the first time, our work demonstrates the success of pulp tissue regeneration in a full-length root canal, making it a significant step toward regenerative endodontics. The regeneration of pulp tissues in a full-length tooth root canal has been one of the greatest challenges in the field of regenerative endodontics, and one of the biggest barriers for its clinical application. In this study, we developed a unique approach to tackle this challenge, and for the first time, we successfully regenerated living pulp tissues in a full-length root canal, making it a significant step toward regenerative endodontics. This study will make positive scientific
NASA Astrophysics Data System (ADS)
Srivastava, D. P.; Sahni, V.; Satsangi, P. S.
2014-08-01
Graph-theoretic quantum system modelling (GTQSM) is facilitated by considering the fundamental unit of quantum computation and information, viz. a quantum bit or qubit as a basic building block. Unit directional vectors "ket 0" and "ket 1" constitute two distinct fundamental quantum across variable orthonormal basis vectors, for the Hilbert space, specifying the direction of propagation of information, or computation data, while complementary fundamental quantum through, or flow rate, variables specify probability parameters, or amplitudes, as surrogates for scalar quantum information measure (von Neumann entropy). This paper applies GTQSM in continuum of protein heterodimer tubulin molecules of self-assembling polymers, viz. microtubules in the brain as a holistic system of interacting components representing hierarchical clustered quantum Hopfield network, hQHN, of networks. The quantum input/output ports of the constituent elemental interaction components, or processes, of tunnelling interactions and Coulombic bidirectional interactions are in cascade and parallel interconnections with each other, while the classical output ports of all elemental components are interconnected in parallel to accumulate micro-energy functions generated in the system as Hamiltonian, or Lyapunov, energy function. The paper presents an insight, otherwise difficult to gain, for the complex system of systems represented by clustered quantum Hopfield network, hQHN, through the application of GTQSM construct.
Hierarchical socioeconomic fractality: The rich, the poor, and the middle-class
NASA Astrophysics Data System (ADS)
Eliazar, Iddo; Cohen, Morrel H.
2014-05-01
Since the seminal work of the Italian economist Vilfredo Pareto, the study of wealth and income has been a topic of active scientific exploration engaging researches ranging from economics and political science to econophysics and complex systems. This paper investigates the intrinsic fractality of wealth and income. To that end we introduce and characterize three forms of socioeconomic scale-invariance-poor fractality, rich fractality, and middle-class fractality-and construct hierarchical fractal approximations of general wealth and income distributions, based on the stitching of these three forms of fractality. Intertwining the theoretical results with real-world empirical data we then establish that the three forms of socioeconomic fractality-amalgamated into a composite hierarchical structure-underlie the distributions of wealth and income in human societies. We further establish that the hierarchical socioeconomic fractality of wealth and income is also displayed by empirical rank distributions observed across the sciences.
Bayesian hierarchical modeling for detecting safety signals in clinical trials.
Xia, H Amy; Ma, Haijun; Carlin, Bradley P
2011-09-01
Detection of safety signals from clinical trial adverse event data is critical in drug development, but carries a challenging statistical multiplicity problem. Bayesian hierarchical mixture modeling is appealing for its ability to borrow strength across subgroups in the data, as well as moderate extreme findings most likely due merely to chance. We implement such a model for subject incidence (Berry and Berry, 2004 ) using a binomial likelihood, and extend it to subject-year adjusted incidence rate estimation under a Poisson likelihood. We use simulation to choose a signal detection threshold, and illustrate some effective graphics for displaying the flagged signals.
Noise enhances information transfer in hierarchical networks.
Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A
2013-01-01
We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.
Noise enhances information transfer in hierarchical networks
Czaplicka, Agnieszka; Holyst, Janusz A.; Sloot, Peter M. A.
2013-01-01
We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor. PMID:23390574
Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks
Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.
2014-01-01
Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks. PMID:24949877
Dynamic resource allocation in a hierarchical multiprocessor system: A preliminary study
NASA Technical Reports Server (NTRS)
Ngai, Tin-Fook
1986-01-01
An integrated system approach to dynamic resource allocation is proposed. Some of the problems in dynamic resource allocation and the relationship of these problems to system structures are examined. A general dynamic resource allocation scheme is presented. A hierarchial system architecture which dynamically maps between processor structure and programs at multiple levels of instantiations is described. Simulation experiments were conducted to study dynamic resource allocation on the proposed system. Preliminary evaluation based on simple dynamic resource allocation algorithms indicates that with the proposed system approach, the complexity of dynamic resource management could be significantly reduced while achieving reasonable effective dynamic resource allocation.
Reasons for Hierarchical Linear Modeling: A Reminder.
ERIC Educational Resources Information Center
Wang, Jianjun
1999-01-01
Uses examples of hierarchical linear modeling (HLM) at local and national levels to illustrate proper applications of HLM and dummy variable regression. Raises cautions about the circumstances under which hierarchical data do not need HLM. (SLD)
Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method
NASA Astrophysics Data System (ADS)
Tsai, F. T. C.; Elshall, A. S.
2014-12-01
Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.
Efficient Parallel Formulations of Hierarchical Methods and Their Applications
NASA Astrophysics Data System (ADS)
Grama, Ananth Y.
1996-01-01
Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel
Multimodal emotional state recognition using sequence-dependent deep hierarchical features.
Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan
2015-12-01
Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Glassy nature of hierarchical organizations.
Zamani, Maryam; Vicsek, Tamas
2017-05-03
The question of why and how animal and human groups form temporarily stable hierarchical organizations has long been a great challenge from the point of quantitative interpretations. The prevailing observation/consensus is that a hierarchical social or technological structure is optimal considering a variety of aspects. Here we introduce a simple quantitative interpretation of this situation using a statistical mechanics-type approach. We look for the optimum of the efficiency function [Formula: see text] with J ij denoting the nature of the interaction between the units i and j and a i standing for the ability of member i to contribute to the efficiency of the system. Notably, this expression for E eff has a similar structure to that of the energy as defined for spin-glasses. Unconventionally, we assume that J ij -s can have the values 0 (no interaction), +1 and -1; furthermore, a direction is associated with each edge. The essential and novel feature of our approach is that instead of optimizing the state of the nodes of a pre-defined network, we search for extrema for given a i -s in the complex efficiency landscape by finding locally optimal network topologies for a given number of edges of the subgraphs considered.
Discursive Hierarchical Patterning in Economics Cases
ERIC Educational Resources Information Center
Lung, Jane
2011-01-01
This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…
HierarchicalTopics: visually exploring large text collections using topic hierarchies.
Dou, Wenwen; Yu, Li; Wang, Xiaoyu; Ma, Zhiqiang; Ribarsky, William
2013-12-01
Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be generated in order to capture the meaningful latent themes and nuances in the corpora. However, it is difficult for most of current topic-based visualizations to represent large number of topics without being cluttered or illegible. To facilitate the representation and navigation of a large number of topics, we propose a visual analytics system--HierarchicalTopic (HT). HT integrates a computational algorithm, Topic Rose Tree, with an interactive visual interface. The Topic Rose Tree constructs a topic hierarchy based on a list of topics. The interactive visual interface is designed to present the topic content as well as temporal evolution of topics in a hierarchical fashion. User interactions are provided for users to make changes to the topic hierarchy based on their mental model of the topic space. To qualitatively evaluate HT, we present a case study that showcases how HierarchicalTopics aid expert users in making sense of a large number of topics and discovering interesting patterns of topic groups. We have also conducted a user study to quantitatively evaluate the effect of hierarchical topic structure. The study results reveal that the HT leads to faster identification of large number of relevant topics. We have also solicited user feedback during the experiments and incorporated some suggestions into the current version of HierarchicalTopics.
Ai, Wei; Wang, Xuewan; Zou, Chenji; Du, Zhuzhu; Fan, Zhanxi; Zhang, Hua; Chen, Peng; Yu, Ting; Huang, Wei
2017-02-01
Hierarchically porous carbons are attracting tremendous attention in sustainable energy systems, such as lithium ion battery (LIB) and fuel cell, due to their excellent transport properties that arise from the high surface area and rich porosity. The state-of-the-art approaches for synthesizing hierarchically porous carbons normally require chemical- and/or template-assisted activation techniques, which is complicate, time consuming, and not feasible for large scale production. Here, a molecular-level design principle toward large-scale synthesis of nitrogen and phosphorus codoped hierarchically porous carbon (NPHPC) through an in situ self-activation process is proposed. The material is fabricated based on the direct pyrolysis of a well-designed polymer, melamine polyphosphate, which is capable of in situ self-activation to generate large specific surface area (1479 m 2 g -1 ) and hierarchical pores in the final NPHPC. As an anode material for LIB, NPHPC delivers a high reversible capacity of 1073 mAh g -1 and an excellent cyclic stability for 300 cycles with negligible capacity decay. The peculiar structural properties and synergistic effect of N and P codopants also enable NPHPC a promising electrocatalyst for oxygen reduction reaction, a key cathodic reaction process of many energy conversion devices (for example, fuel cells and metal air batteries). Electrochemical measurements show NPHPC a comparable electrocatalytic performance to commercial Pt/C catalyst (onset potential of 0.88 V vs reversible hydrogen electrode in alkaline medium) with excellent stability (89.8% retention after 20 000 s continuous operation) and superior methanol tolerance. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Reynolds, Richard J.; Ahmed, Altan F.; Danila, Maria I.; Hughes, Laura B.; Gregersen, Peter K.; Raychaudhuri, Soumya; Plenge, Robert M.; Bridges, S. Louis
2014-01-01
Objective To evaluate African American rheumatoid arthritis HLA-DRB1 genetic risk by three validated allele classification systems, and by amino acid position and residue. To compare the genetic risk between African American and European ancestries. Methods Four-digit HLA-DRB1 genotyping was performed on 561 autoantibody-positive African American cases and 776 African American controls. Association analysis was performed on Tezenas du Montcel (TdM); de Vries (DV); and Mattey classification system alleles and separately by amino acid position and individual residues. Results TdM S2 and S3P alleles were associated with RA (odds ratios (95% CI) 2.8 (2.0, 3.9) and 2.1 (1.7, 2.7), respectively). The DV (P-value=3.2 x 10−12) and Mattey (P-value=6.5 x 10−13) system alleles were both protective in African Americans. Amino acid position 11 (permutation P-value < 0.00001) accounted for nearly all variability explained by HLA-DRB1, although conditional analysis demonstrated that position 57 was also significant (0.01<= permutation P-val <=0.05). The valine and aspartic acid residues at position 11 conferred the highest risk for RA in African Americans. Conclusion With some exceptions, the genetic risk conferred by HLA-DRB1 in African Americans is similar to European ancestry at multiple levels: classification system (e.g., TdM), amino acid position (e.g. 11) and residue (Val 11). Unlike that reported from European ancestry, amino acid position 57 was associated with RA in African Americans, but positions 71 and 74 were not. Asp11 (OR = 1 in European ancestry) corresponds to the four digit classical allele, *09:01, also a risk allele for RA in Koreans. PMID:25524867
Hierarchical and coupling model of factors influencing vessel traffic flow.
Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi
2017-01-01
Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.
Spacecraft Multiple Array Communication System Performance Analysis
NASA Technical Reports Server (NTRS)
Hwu, Shian U.; Desilva, Kanishka; Sham, Catherine C.
2010-01-01
The Communication Systems Simulation Laboratory (CSSL) at the NASA Johnson Space Center is tasked to perform spacecraft and ground network communication system simulations, design validation, and performance verification. The CSSL has developed simulation tools that model spacecraft communication systems and the space and ground environment in which the tools operate. In this paper, a spacecraft communication system with multiple arrays is simulated. Multiple array combined technique is used to increase the radio frequency coverage and data rate performance. The technique is to achieve phase coherence among the phased arrays to combine the signals at the targeting receiver constructively. There are many technical challenges in spacecraft integration with a high transmit power communication system. The array combining technique can improve the communication system data rate and coverage performances without increasing the system transmit power requirements. Example simulation results indicate significant performance improvement can be achieved with phase coherence implementation.
Koh, Kyung; Kwon, Hyun Joon; Yoon, Bum Chul; Cho, Yongseok; Shin, Joon-Ho; Hahn, Jin-Oh; Miller, Ross H; Kim, Yoon Hyuk; Shim, Jae Kun
2015-09-01
The hand, one of the most versatile but mechanically redundant parts of the human body, must overcome imperfect motor commands and inherent noise in both the sensory and motor systems in order to produce desired motor actions. For example, it is nearly impossible to produce a perfectly consistent note during a single violin stroke or to produce the exact same note over multiple strokes, which we denote online and offline control, respectively. To overcome these challenges, the central nervous system synergistically integrates multiple sensory modalities and coordinates multiple motor effectors. Among these sensory modalities, tactile sensation plays an important role in manual motor tasks by providing hand-object contact information. The purpose of this study was to investigate the role of tactile feedback in individual finger actions and multi-finger interactions during constant force production tasks. We developed analytical techniques for the linear decomposition of the overall variance in the motor system in both online and offline control. We removed tactile feedback from the fingers and demonstrated that tactile sensors played a critical role in the online control of synergistic interactions between fingers. In contrast, the same sensors did not contribute to offline control. We also demonstrated that when tactile feedback was removed from the fingers, the combined motor output of individual fingers did not change while individual finger behaviors did. This finding supports the idea of hierarchical control where individual fingers at the lower level work together to stabilize the performance of combined motor output at the higher level.
Tian, Ting; McLachlan, Geoffrey J.; Dieters, Mark J.; Basford, Kaye E.
2015-01-01
It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances. PMID:26689369
Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E
2015-01-01
It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.
A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.
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.
Coordinated Voltage Control of Transformer Taps on account of Hierarchical Structure in Power System
NASA Astrophysics Data System (ADS)
Nakachi, Yoshiki; Kato, Satoshi; Ukai, Hiroyuki
Participation of distributed generators (DG), such as wind turbines, co-generation system etc., is natural trend from ecological point of view and will increase more and more. The outputs of these DGs mainly depend on weather condition but don't correspond to the changes of electrical load demand necessarily. On the other hand, due to the deregulation of electric power market, the power flow in power system will uncertainly vary with several power transactions. Thus, complex power flow by DGs or transactions will cause the voltage deviation. It will be difficult to sustain the voltage quality by using the conventional voltage/reactive power control in near future. In this paper, in order to avoid such a voltage deviation and to decrease the frequency of transformer tap actions, the coordinated voltage control scheme of transformer taps on account of hierarchical structure in power system is proposed. In the proposed scheme, integral of voltage deviation at each layer bus is applied to decide the timing of each transformer tap action. It is confirmed by some numerical simulations that the proposed scheme is able to respond to every conditions on voltage deviation.
NASA Technical Reports Server (NTRS)
Houlahan, Padraig; Scalo, John
1992-01-01
A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.
Sparsey™: event recognition via deep hierarchical sparse distributed codes
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
NASA Technical Reports Server (NTRS)
Padovan, J.; Lackney, J.
1986-01-01
The current paper develops a constrained hierarchical least square nonlinear equation solver. The procedure can handle the response behavior of systems which possess indefinite tangent stiffness characteristics. Due to the generality of the scheme, this can be achieved at various hierarchical application levels. For instance, in the case of finite element simulations, various combinations of either degree of freedom, nodal, elemental, substructural, and global level iterations are possible. Overall, this enables a solution methodology which is highly stable and storage efficient. To demonstrate the capability of the constrained hierarchical least square methodology, benchmarking examples are presented which treat structure exhibiting highly nonlinear pre- and postbuckling behavior wherein several indefinite stiffness transitions occur.
A hierarchical anatomical classification schema for prediction of phenotypic side effects
Kanji, Rakesh
2018-01-01
Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708
Content Consumption and Hierarchical Structures of Web-Supported Courses
ERIC Educational Resources Information Center
Hershkovitz, Arnon; Hardof-Jaffe, Sharon; Nachmias, Rafi
2014-01-01
This study presents an empirical investigation of the relationship between the hierarchical structure of content delivered to students within a Learning Management System (LMS) and its actual consumption. To this end, campus-wide data relating to 1,203 courses were collected from the LMS' servers and were subsequently analyzed using data mining…
A hierarchical model of the evolution of human brain specializations
Barrett, H. Clark
2012-01-01
The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised. PMID:22723350
Advanced multiple access concepts in mobile satellite systems
NASA Technical Reports Server (NTRS)
Ananasso, Fulvio
1990-01-01
Some multiple access strategies for Mobile Satellite Systems (MSS) are discussed. These strategies were investigated in the context of three separate studies conducted for the International Maritime Satellite Organization (INMARSAT) and the European Space Agency (ESA). Satellite-Switched Frequency Division Multiple Access (SS-FDMA), Code Division Multiple Access (CDMA), and Frequency-Addressable Beam architectures are addressed, discussing both system and technology aspects and outlining advantages and drawbacks of either solution with associated relevant hardware issues. An attempt is made to compare the considered option from the standpoint of user terminal/space segment complexity, synchronization requirements, spectral efficiency, and interference rejection.
A bioscaffolding strategy for hierarchical zeolites with a nanotube-trimodal network.
Li, Guannan; Huang, Haibo; Yu, Bowen; Wang, Yun; Tao, Jiawei; Wei, Yingxu; Li, Shougui; Liu, Zhongmin; Xu, Yan; Xu, Ruren
2016-02-01
Hierarchical zeolite monoliths with multimodal porosity are of paramount importance as they open up new horizons for advanced applications. So far, hierarchical zeolites based on nanotube scaffolds have never been reported. Inspired by the organization of biominerals, we have developed a novel precursor scaffolding-solid phase crystallization strategy for hierarchical zeolites with a unique nanotube scaffolding architecture and nanotube-trimodal network, where biomolecular self-assembly (BSA) provides a scaffolding blueprint. By vapor-treating Sil-1 seeded precursor scaffolds, zeolite MFI nanotube scaffolds are self-generated, during which evolution phenomena such as segmented voids and solid bridges are observed, in agreement with the Kirkendall effect in a solid-phase crystallization system. The nanotube walls are made of intergrown single crystals rendering good mechanical stability. The inner diameter of the nanotube is tunable between 30 and 90 nm by varying the thickness of the precursor layers. Macropores enclosed by cross-linked nanotubes can be modulated by the choice of BSA. Narrow mesopores are formed by intergrown nanocrystals. Hierarchical ZSM-5 monoliths with nanotube (90 nm), micropore (0.55 nm), mesopore (2 nm) and macropore (700 nm) exhibit superior catalytic performance in the methanol-to-hydrocarbon (MTH) conversion compared to conventional ZSM-5. BSA remains intact after crystallization, allowing a higher level of organization and functionalization of the zeolite nanotube scaffolds. The current work may afford a versatile strategy for hierarchical zeolite monoliths with nanotube scaffolding architectures and a nanotube-multimodal network leading to self-supporting and active zeolite catalysts, and for applications beyond.
Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas
2007-01-01
This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.
Bone-like crack resistance in hierarchical metastable nanolaminate steels
NASA Astrophysics Data System (ADS)
Koyama, Motomichi; Zhang, Zhao; Wang, Meimei; Ponge, Dirk; Raabe, Dierk; Tsuzaki, Kaneaki; Noguchi, Hiroshi; Tasan, Cemal Cem
2017-03-01
Fatigue failures create enormous risks for all engineered structures, as well as for human lives, motivating large safety factors in design and, thus, inefficient use of resources. Inspired by the excellent fracture toughness of bone, we explored the fatigue resistance in metastability-assisted multiphase steels. We show here that when steel microstructures are hierarchical and laminated, similar to the substructure of bone, superior crack resistance can be realized. Our results reveal that tuning the interface structure, distribution, and phase stability to simultaneously activate multiple micromechanisms that resist crack propagation is key for the observed leap in mechanical response. The exceptional properties enabled by this strategy provide guidance for all fatigue-resistant alloy design efforts.
Local complexity predicts global synchronization of hierarchically networked oscillators
NASA Astrophysics Data System (ADS)
Xu, Jin; Park, Dong-Ho; Jo, Junghyo
2017-07-01
We study the global synchronization of hierarchically-organized Stuart-Landau oscillators, where each subsystem consists of three oscillators with activity-dependent couplings. We considered all possible coupling signs between the three oscillators, and found that they can generate different numbers of phase attractors depending on the network motif. Here, the subsystems are coupled through mean activities of total oscillators. Under weak inter-subsystem couplings, we demonstrate that the synchronization between subsystems is highly correlated with the number of attractors in uncoupled subsystems. Among the network motifs, perfect anti-symmetric ones are unique to generate both single and multiple attractors depending on the activities of oscillators. The flexible local complexity can make global synchronization controllable.
Tschechne, Stephan; Neumann, Heiko
2014-01-01
Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy
Tschechne, Stephan; Neumann, Heiko
2014-01-01
Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1-V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.
Multiple energy synchrotron biomedical imaging system
NASA Astrophysics Data System (ADS)
Bassey, B.; Martinson, M.; Samadi, N.; Belev, G.; Karanfil, C.; Qi, P.; Chapman, D.
2016-12-01
A multiple energy imaging system that can extract multiple endogenous or induced contrast materials as well as water and bone images would be ideal for imaging of biological subjects. The continuous spectrum available from synchrotron light facilities provides a nearly perfect source for multiple energy x-ray imaging. A novel multiple energy x-ray imaging system, which prepares a horizontally focused polychromatic x-ray beam, has been developed at the BioMedical Imaging and Therapy bend magnet beamline at the Canadian Light Source. The imaging system is made up of a cylindrically bent Laue single silicon (5,1,1) crystal monochromator, scanning and positioning stages for the subjects, flat panel (area) detector, and a data acquisition and control system. Depending on the crystal’s bent radius, reflection type, and the horizontal beam width of the filtered synchrotron radiation (20-50 keV) used, the size and spectral energy range of the focused beam prepared varied. For example, with a bent radius of 95 cm, a (1,1,1) type reflection and a 50 mm wide beam, a 0.5 mm wide focused beam of spectral energy range 27 keV-43 keV was obtained. This spectral energy range covers the K-edges of iodine (33.17 keV), xenon (34.56 keV), cesium (35.99 keV), and barium (37.44 keV) some of these elements are used as biomedical and clinical contrast agents. Using the developed imaging system, a test subject composed of iodine, xenon, cesium, and barium along with water and bone were imaged and their projected concentrations successfully extracted. The estimated dose rate to test subjects imaged at a ring current of 200 mA is 8.7 mGy s-1, corresponding to a cumulative dose of 1.3 Gy and a dose of 26.1 mGy per image. Potential biomedical applications of the imaging system will include projection imaging that requires any of the extracted elements as a contrast agent and multi-contrast K-edge imaging.
Linguistic steganography on Twitter: hierarchical language modeling with manual interaction
NASA Astrophysics Data System (ADS)
Wilson, Alex; Blunsom, Phil; Ker, Andrew D.
2014-02-01
This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.
System For Research On Multiple-Arm Robots
NASA Technical Reports Server (NTRS)
Backes, Paul G.; Hayati, Samad; Tso, Kam S.; Hayward, Vincent
1991-01-01
Kali system of computer programs and equipment provides environment for research on distributed programming and distributed control of coordinated-multiple-arm robots. Suitable for telerobotics research involving sensing and execution of low level tasks. Software and configuration of hardware designed flexible so system modified easily to test various concepts in control and programming of robots, including multiple-arm control, redundant-arm control, shared control, traded control, force control, force/position hybrid control, design and integration of sensors, teleoperation, task-space description and control, methods of adaptive control, control of flexible arms, and human factors.
Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree
ERIC Educational Resources Information Center
Chen, Wei-Bang
2012-01-01
The purpose of this research is to develop a new visual information analysis, representation, and retrieval framework for automatic discovery of salient objects of user's interest in large-scale image databases. In particular, this dissertation describes a content-based image retrieval framework which supports multiple-object retrieval. The…
Hierarchical competitions subserving multi-attribute choice
Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ
2015-01-01
Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549
Dynamical investigations of the multiple stars
NASA Astrophysics Data System (ADS)
Kiyaeva, Olga V.; Zhuchkov, Roman Ya.
2017-11-01
Two multiple stars - the quadruple star - Bootis (ADS 9173) and the triple star T Taury were investigated. The visual double star - Bootiswas studied on the basis of the Pulkovo 26-inch refractor observations 1982-2013. An invisible satellite of the component A was discovered due to long-term uniform series of observations. Its orbital period is 20 ± 2 years. The known invisible satellite of the component B with near 5 years period was confirmed due to high precision CCD observations. The astrometric orbits of the both components were calculated. The orbits of inner and outer pairs of the pre-main sequence binary T Taury were calculated on the basis of high precision observations by the VLT and on the Keck II Telescope. This weakly hierarchical triple system is stable with probability more than 70%.
Stress Effects on Multiple Memory System Interactions
Ness, Deborah; Calabrese, Pasquale
2016-01-01
Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory systems, we review recent animal and human studies exploring the effects of stress on multiple memory systems. Apart from discussing the interaction between distinct memory systems in stressful situations, we will also outline the fundamental role of the amygdala in mediating such stress effects. Additionally, based on the methods applied in the herein discussed studies, we will discuss how memory translates into behaviour. PMID:27034845
Hierarchical damage mechanisms in composite materials subjected to fatigue loadings
NASA Astrophysics Data System (ADS)
D'Amore, Alberto; Grassia, Luigi
2018-02-01
The strength degradation of fiber reinforced composites subjected to constant amplitude (CA) fatigue loadings can be described by a two-parameter residual strength model. From the analytical approach it results that under moderate loadings the multiple damage mechanisms develop with different kinetics and manifest their effectiveness at different time scales highlighting the three-Stage hierarchical nature of damage accumulation in composites. The model captures the sequence of damage accumulation mechanisms from diffuse matrix cracking (I), to fiber/matrix interface failure (II) to fiber and ply rupture and delamination (III). Further, by increasing the loading severity it appears that the different mechanisms superpose witnessing their simultaneous co-existence.
Integration of Hierarchical Goal Network Planning and Autonomous Path Planning
2016-03-01
Conference on Robotics and Automation (ICRA); 2010 May 3– 7; Anchorage, AK. p. 2902–2908. 4. Ayan NF, Kuter U, Yaman F, Goldman RP. Hotride...DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Automated planning has...world robotic systems. This report documents work to integrate a hierarchical goal network planning algorithm with low-level path planning. The system
Inventory and Billing Systems for Multiple Users.
ERIC Educational Resources Information Center
Frazier, Lavon
Washington State University developed a comprehensive supplies inventory system and a generalized billing system with multiple users in mind. The supplies inventory control system developed for Central Stores, a self-sustaining service center that purchases and warehouses office, laboratory, and hardware supplies, was called AIMS, An Inventory…
Hierarchical organization in the temporal structure of infant-direct speech and song.
Falk, Simone; Kello, Christopher T
2017-06-01
Caregivers alter the temporal structure of their utterances when talking and singing to infants compared with adult communication. The present study tested whether temporal variability in infant-directed registers serves to emphasize the hierarchical temporal structure of speech. Fifteen German-speaking mothers sang a play song and told a story to their 6-months-old infants, or to an adult. Recordings were analyzed using a recently developed method that determines the degree of nested clustering of temporal events in speech. Events were defined as peaks in the amplitude envelope, and clusters of various sizes related to periods of acoustic speech energy at varying timescales. Infant-directed speech and song clearly showed greater event clustering compared with adult-directed registers, at multiple timescales of hundreds of milliseconds to tens of seconds. We discuss the relation of this newly discovered acoustic property to temporal variability in linguistic units and its potential implications for parent-infant communication and infants learning the hierarchical structures of speech and language. Copyright © 2017 Elsevier B.V. All rights reserved.
System-wide versus component-specific trust using multiple aids.
Keller, David; Rice, Stephen
2010-01-01
Previous research in operator trust toward automated aids has focused primarily on single aids. The current study focuses on how operator trust is affected by the presence of multiple aids. Two competing theories of multiple-trust are presented. A component-specific trust theory predicts that operators will differentially place their trust in automated aids that vary in reliability. A system-wide trust theory predicts that operators will treat multiple imperfect aids as one "system" and merge their trust across aids despite differences in the aids' reliability. A simulated flight task was used to test these theories, whereby operators performed a pursuit tracking task while concurrently monitoring multiple system gauges that were augmented with perfect or imperfect automated aids. The data revealed that a system-wide trust theory best predicted the data; operators merged their trust across both aids, behaving toward a perfectly reliable aid in the same manner as they did towards unreliable aids.
NASA Astrophysics Data System (ADS)
He, Fang; Chen, Xi
2016-11-01
The accelerating accumulation and risk concentration of Chinese local financing platforms debts have attracted wide attention throughout the world. Due to the network of financial exposures among institutions, the failure of several platforms or regions of systemic importance will probably trigger systemic risk and destabilize the financial system. However, the complex network of credit relationships in Chinese local financing platforms at the state level remains unknown. To fill this gap, we presented the first complex networks and hierarchical cluster analysis of the credit market of Chinese local financing platforms using the ;bottom up; method from firm-level data. Based on balance-sheet channel, we analyzed the topology and taxonomy by applying the analysis paradigm of subdominant ultra-metric space to an empirical data in 2013. It is remarked that we chose to extract the network of co-financed financing platforms in order to evaluate the effect of risk contagion from platforms to bank system. We used the new credit similarity measure by combining the factor of connectivity and size, to extract minimal spanning trees (MSTs) and hierarchical trees (HTs). We found that: (1) the degree distributions of credit correlation backbone structure of Chinese local financing platforms are fat tailed, and the structure is unstable with respect to targeted failures; (2) the backbone is highly hierarchical, and largely explained by the geographic region; (3) the credit correlation backbone structure based on connectivity and size is significantly heterogeneous; (4) key platforms and regions of systemic importance, and contagion path of systemic risk are obtained, which are contributed to preventing systemic risk and regional risk of Chinese local financing platforms and preserving financial stability under the framework of macro prudential supervision. Our approach of credit similarity measure provides a means of recognizing ;systemically important; institutions and regions
Liu, Xiaodong; Baoyin, Hexi; Marchis, Franck
In this study, the hierarchical stability of the seven known large size ratio triple asteroids is investigated. The effect of the solar gravity and primary's J 2 are considered. The force function is expanded in terms of mass ratios based on the Hill's approximation and the large size ratio property. The empirical stability parameters are used to examine the hierarchical stability of the triple asteroids. It is found that the all the known large size ratio triple asteroid systems are hierarchically stable. This study provides useful information for future evolutions of the triple asteroids.
A hierarchical exact accelerated stochastic simulation algorithm
NASA Astrophysics Data System (ADS)
Orendorff, David; Mjolsness, Eric
2012-12-01
A new algorithm, "HiER-leap" (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled "blocks" and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms.
A neural network with modular hierarchical learning
NASA Technical Reports Server (NTRS)
Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)
1994-01-01
This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.
Pillar-structured neutron detector based multiplicity system
NASA Astrophysics Data System (ADS)
Murphy, John W.; Shao, Qinghui; Voss, Lars F.; Kerr, Phil L.; Fabris, Lorenzo; Conway, Adam M.; Nikolic, Rebecca J.
2018-01-01
This work demonstrates the potential of silicon pillars filled with boron-10 as a sensor technology for a compact and portable neutron multiplicity system. Solid-state, semiconductor based neutron detectors may enable completely new detector form factors, offer an alternate approach to helium-3 based systems, and reduce detector weight and volume requirements. Thirty-two pillar-structured neutron detectors were assembled into a system with an active area of over 20 cm2 and were used in this work to demonstrate the feasibility of this sensor technology as a potential replacement for helium-3 based gas detectors. Multiplicity measurements were successfully carried out using a californium-252 neutron source, in which the source mass, system efficiency, and die-away time were determined. This demonstration shows that these solid-state detectors could allow for a more compact and portable system that could be used for special nuclear material identification in the field.
Gomelsky, Larissa; Moskvin, Oleg V; Stenzel, Rachel A; Jones, Denise F; Donohue, Timothy J; Gomelsky, Mark
2008-12-01
In the facultatively phototrophic proteobacterium Rhodobacter sphaeroides, formation of the photosynthetic apparatus is oxygen dependent. When oxygen tension decreases, the response regulator PrrA of the global two-component PrrBA system is believed to directly activate transcription of the puf, puh, and puc operons, encoding structural proteins of the photosynthetic complexes, and to indirectly upregulate the photopigment biosynthesis genes bch and crt. Decreased oxygen also results in inactivation of the photosynthesis-specific repressor PpsR, bringing about derepression of the puc, bch, and crt operons. We uncovered a hierarchical relationship between these two regulatory systems, earlier thought to function independently. We also more accurately assessed the spectrum of gene targets of the PrrBA system. First, expression of the appA gene, encoding the PpsR antirepressor, is PrrA dependent, which establishes one level of hierarchical dominance of the PrrBA system over AppA-PpsR. Second, restoration of the appA transcript to the wild-type level is insufficient for rescuing phototrophic growth impairment of the prrA mutant, whereas inactivation of ppsR is sufficient. This suggests that in addition to controlling appA transcription, PrrA affects the activity of the AppA-PpsR system via an as yet unidentified mechanism(s). Third, PrrA directly activates several bch and crt genes, traditionally considered to be the PpsR targets. Therefore, in R. sphaeroides, the global PrrBA system regulates photosynthesis gene expression (i) by rigorous control over the photosynthesis-specific AppA-PpsR regulatory system and (ii) by extensive direct transcription activation of genes encoding structural proteins of photosynthetic complexes as well as genes encoding photopigment biosynthesis enzymes.
A hierarchical approach to forest landscape pattern characterization.
Wang, Jialing; Yang, Xiaojun
2012-01-01
Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.
Emerging Hierarchical Aerogels: Self-Assembly of Metal and Semiconductor Nanocrystals.
Cai, Bin; Sayevich, Vladimir; Gaponik, Nikolai; Eychmüller, Alexander
2018-06-19
Aerogels assembled from colloidal metal or semiconductor nanocrystals (NCs) feature large surface area, ultralow density, and high porosity, thus rendering them attractive in various applications, such as catalysis, sensors, energy storage, and electronic devices. Morphological and structural modification of the aerogel backbones while maintaining the aerogel properties enables a second stage of the aerogel research, which is defined as hierarchical aerogels. Different from the conventional aerogels with nanowire-like backbones, those hierarchical aerogels are generally comprised of at least two levels of architectures, i.e., an interconnected porous structure on the macroscale and a specially designed configuration at local backbones at the nanoscale. This combination "locks in" the inherent properties of the NCs, so that the beneficial genes obtained by nanoengineering are retained in the resulting monolithic hierarchical aerogels. Herein, groundbreaking advances in the design, synthesis, and physicochemical properties of the hierarchical aerogels are reviewed and organized in three sections: i) pure metallic hierarchical aerogels, ii) semiconductor hierarchical aerogels, and iii) metal/semiconductor hybrid hierarchical aerogels. This report aims to define and demonstrate the concept, potential, and challenges of the hierarchical aerogels, thereby providing a perspective on the further development of these materials. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Identification of limit cycles in multi-nonlinearity, multiple path systems
NASA Technical Reports Server (NTRS)
Mitchell, J. R.; Barron, O. L.
1979-01-01
A method of analysis which identifies limit cycles in autonomous systems with multiple nonlinearities and multiple forward paths is presented. The FORTRAN code for implementing the Harmonic Balance Algorithm is reported. The FORTRAN code is used to identify limit cycles in multiple path and nonlinearity systems while retaining the effects of several harmonic components.
Hierarchical Traces for Reduced NSM Memory Requirements
NASA Astrophysics Data System (ADS)
Dahl, Torbjørn S.
This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.
Understanding Diffusion in Hierarchical Zeolites with House-of-Cards Nanosheets.
Bai, Peng; Haldoupis, Emmanuel; Dauenhauer, Paul J; Tsapatsis, Michael; Siepmann, J Ilja
2016-08-23
Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of n-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length.
A spatial analysis of hierarchical waste transport structures under growing demand.
Tanguy, Audrey; Glaus, Mathias; Laforest, Valérie; Villot, Jonathan; Hausler, Robert
2016-10-01
The design of waste management systems rarely accounts for the spatio-temporal evolution of the demand. However, recent studies suggest that this evolution affects the planning of waste management activities like the choice and location of treatment facilities. As a result, the transport structure could also be affected by these changes. The objective of this paper is to study the influence of the spatio-temporal evolution of the demand on the strategic planning of a waste transport structure. More particularly this study aims at evaluating the effect of varying spatial parameters on the economic performance of hierarchical structures (with one transfer station). To this end, three consecutive generations of three different spatial distributions were tested for hierarchical and non-hierarchical transport structures based on costs minimization. Results showed that a hierarchical structure is economically viable for large and clustered spatial distributions. The distance parameter was decisive but the loading ratio of trucks and the formation of clusters of sources also impacted the attractiveness of the transfer station. Thus the territories' morphology should influence strategies as regards to the installation of transfer stations. The use of spatial-explicit tools such as the transport model presented in this work that take into account the territory's evolution are needed to help waste managers in the strategic planning of waste transport structures. © The Author(s) 2016.
Morton, Lindsay M.; Linet, Martha S.; Clarke, Christina A.; Kadin, Marshall E.; Vajdic, Claire M.; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C.-H.; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R.; Weisenburger, Dennis D.
2010-01-01
After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and “in situ” lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications. PMID:20699439
Turner, Jennifer J; Morton, Lindsay M; Linet, Martha S; Clarke, Christina A; Kadin, Marshall E; Vajdic, Claire M; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C-H; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R; Weisenburger, Dennis D
2010-11-18
After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.
Hierarchical and coupling model of factors influencing vessel traffic flow
Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi
2017-01-01
Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747
ARCHITECTURE AND DYNAMICS OF KEPLER'S CANDIDATE MULTIPLE TRANSITING PLANET SYSTEMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lissauer, Jack J.; Jenkins, Jon M.; Borucki, William J.
About one-third of the {approx}1200 transiting planet candidates detected in the first four months of Kepler data are members of multiple candidate systems. There are 115 target stars with two candidate transiting planets, 45 with three, 8 with four, and 1 each with five and six. We characterize the dynamical properties of these candidate multi-planet systems. The distribution of observed period ratios shows that the vast majority of candidate pairs are neither in nor near low-order mean-motion resonances. Nonetheless, there are small but statistically significant excesses of candidate pairs both in resonance and spaced slightly too far apart to bemore » in resonance, particularly near the 2:1 resonance. We find that virtually all candidate systems are stable, as tested by numerical integrations that assume a nominal mass-radius relationship. Several considerations strongly suggest that the vast majority of these multi-candidate systems are true planetary systems. Using the observed multiplicity frequencies, we find that a single population of planetary systems that matches the higher multiplicities underpredicts the number of singly transiting systems. We provide constraints on the true multiplicity and mutual inclination distribution of the multi-candidate systems, revealing a population of systems with multiple super-Earth-size and Neptune-size planets with low to moderate mutual inclinations.« less
A hierarchical, automated target recognition algorithm for a parallel analog processor
NASA Technical Reports Server (NTRS)
Woodward, Gail; Padgett, Curtis
1997-01-01
A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1x4096 every 250 nanoseconds.
On the design of a hierarchical SS7 network: A graph theoretical approach
NASA Astrophysics Data System (ADS)
Krauss, Lutz; Rufa, Gerhard
1994-04-01
This contribution is concerned with the design of Signaling System No. 7 networks based on graph theoretical methods. A hierarchical network topology is derived by combining the advantage of the hierarchical network structure with the realization of node disjoint routes between nodes of the network. By using specific features of this topology, we develop an algorithm to construct circle-free routing data and to assure bidirectionality also in case of failure situations. The methods described are based on the requirements that the network topology, as well as the routing data, may be easily changed.
Pillar-structured neutron detector based multiplicity system
Murphy, John W.; Shao, Qinghui; Voss, Lars F.; ...
2017-10-04
This work demonstrates the potential of silicon pillars filled with boron-10 as a sensor technology for a compact and portable neutron multiplicity system. Solid-state, semiconductor based neutron detectors may enable completely new detector form factors, offer an alternate approach to helium-3 based systems, and reduce detector weight and volume requirements. Thirty-two pillar-structured neutron detectors were assembled into a system with an active area of over 20 cm 2 and were used in this work to demonstrate the feasibility of this sensor technology as a potential replacement for helium-3 based gas detectors. Multiplicity measurements were successfully carried out using a californium-252more » neutron source, in which the source mass, system efficiency, and die-away time were determined. As a result, this demonstration shows that these solid-state detectors could allow for a more compact and portable system that could be used for special nuclear material identification in the field.« less
Multiple-Parameter, Low-False-Alarm Fire-Detection Systems
NASA Technical Reports Server (NTRS)
Hunter, Gary W.; Greensburg, Paul; McKnight, Robert; Xu, Jennifer C.; Liu, C. C.; Dutta, Prabir; Makel, Darby; Blake, D.; Sue-Antillio, Jill
2007-01-01
Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can
Hierarchical nanostructures for functional materials.
Qin, Zhao; Buehler, Markus J
2018-07-13
Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.
Hierarchical nanostructures for functional materials
NASA Astrophysics Data System (ADS)
Qin, Zhao; Buehler, Markus J.
2018-07-01
Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.
Modular and hierarchical structure of social contact networks
NASA Astrophysics Data System (ADS)
Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong
2013-10-01
Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.
ERIC Educational Resources Information Center
Kordaki, Maria
2015-01-01
This study focuses on the role of multiple solution tasks (MST) incorporating multiple learning tools and representation systems (MTRS) in encouraging each student to develop multiple perspectives on the learning concepts under study and creativity of thought. Specifically, two types of MST were used, namely tasks that allowed and demanded…
Hierarchical Dirichlet process model for gene expression clustering
2013-01-01
Clustering is an important data processing tool for interpreting microarray data and genomic network inference. In this article, we propose a clustering algorithm based on the hierarchical Dirichlet processes (HDP). The HDP clustering introduces a hierarchical structure in the statistical model which captures the hierarchical features prevalent in biological data such as the gene express data. We develop a Gibbs sampling algorithm based on the Chinese restaurant metaphor for the HDP clustering. We apply the proposed HDP algorithm to both regulatory network segmentation and gene expression clustering. The HDP algorithm is shown to outperform several popular clustering algorithms by revealing the underlying hierarchical structure of the data. For the yeast cell cycle data, we compare the HDP result to the standard result and show that the HDP algorithm provides more information and reduces the unnecessary clustering fragments. PMID:23587447
NASA Astrophysics Data System (ADS)
Chen, Jiawen; Leung, Franco King-Chi; Stuart, Marc C. A.; Kajitani, Takashi; Fukushima, Takanori; van der Giessen, Erik; Feringa, Ben L.
2018-02-01
A striking feature of living systems is their ability to produce motility by amplification of collective molecular motion from the nanoscale up to macroscopic dimensions. Some of nature's protein motors, such as myosin in muscle tissue, consist of a hierarchical supramolecular assembly of very large proteins, in which mechanical stress induces a coordinated movement. However, artificial molecular muscles have often relied on covalent polymer-based actuators. Here, we describe the macroscopic contractile muscle-like motion of a supramolecular system (comprising 95% water) formed by the hierarchical self-assembly of a photoresponsive amphiphilic molecular motor. The molecular motor first assembles into nanofibres, which further assemble into aligned bundles that make up centimetre-long strings. Irradiation induces rotary motion of the molecular motors, and propagation and accumulation of this motion lead to contraction of the fibres towards the light source. This system supports large-amplitude motion, fast response, precise control over shape, as well as weight-lifting experiments in water and air.
Ji, Guipeng; Yang, Zhenzhen; Zhang, Hongye; Zhao, Yanfei; Yu, Bo; Ma, Zhishuang; Liu, Zhimin
2016-08-08
The synthesis of hierarchically mesoporous polymers with multiple functionalities is challenging. Herein we reported a template-free strategy for synthesis of phenolic azo-polymers with hierarchical porous structures based on diazo-coupling reaction in aqueous solution under mild conditions. The resultant polymers have surface areas up to 593 m(2) g(-1) with the mesopore ratio of >80 %, and a good ability to complex with metal ions, such as Cu(2+) , Zn(2+) ,Ni(2+) , achieving a metal loading up to 26.24 wt %. Moreover, the polymers complexed with Zn showed excellent performance for catalyzing the reaction of CO2 with epoxide, affording a TOF of 2570 h(-1) in the presence of tetrabutyl ammonium bromide (7.2 mol %). The polymer complexed with Cu could catalyze the oxidation of alcohol with high efficiency. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Mean-field hierarchical equations for some A+BC catalytic reaction models
NASA Astrophysics Data System (ADS)
Cortés, Joaquín; Puschmann, Heinrich; Valencia, Eliana
1998-10-01
A mean-field study of the (A+BC→AC+1/2B2) system is developed from hierarchical equations, considering mechanisms that include dissociation, reaction with finite rates, desorption, and diffusion of the adsorbed species. The phase diagrams are compared to Monte Carlo simulations.
Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso
2013-09-26
Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function
Naturalizing Sense of Agency with a Hierarchical Event-Control Approach
Kumar, Devpriya; Srinivasan, Narayanan
2014-01-01
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. PMID:24642834
Cities and regions in Britain through hierarchical percolation
NASA Astrophysics Data System (ADS)
Arcaute, Elsa; Molinero, Carlos; Hatna, Erez; Murcio, Roberto; Vargas-Ruiz, Camilo; Masucci, A. Paolo; Batty, Michael
2016-04-01
Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations which are the outcome of complex geographical, political and historical processes which leave almost indelible footprints on infrastructure such as the street network. In this work, we uncover a set of hierarchies in Britain at different scales using percolation theory on the street network and on its intersections which are the primary points of interaction and urban agglomeration. At the larger scales, the observed hierarchical structures can be interpreted as regional fractures of Britain, observed in various forms, from natural boundaries, such as National Parks, to regional divisions based on social class and wealth such as the well-known North-South divide. At smaller scales, cities are generated through recursive percolations on each of the emerging regional clusters. We examine the evolution of the morphology of the system as a whole, by measuring the fractal dimension of the clusters at each distance threshold in the percolation. We observe that this reaches a maximum plateau at a specific distance. The clusters defined at this distance threshold are in excellent correspondence with the boundaries of cities recovered from satellite images, and from previous methods using population density.
Hierarchical virtual screening approaches in small molecule drug discovery.
Kumar, Ashutosh; Zhang, Kam Y J
2015-01-01
Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.
A Study of Hierarchical Classification in Concrete and Formal Thought.
ERIC Educational Resources Information Center
Lowell, Walter E.
This researcher investigated the relationship of hierarchical classification processes in subjects categorized as to developmental level as defined by Piaget's theory, and explored the validity of the hierarchical model and test used in the study. A hierarchical classification test and a battery of four Piaget-type tasks were administered…
Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.
2016-01-01
It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345
Diniz, Daniel G; Silva, Geane O; Naves, Thaís B; Fernandes, Taiany N; Araújo, Sanderson C; Diniz, José A P; de Farias, Luis H S; Sosthenes, Marcia C K; Diniz, Cristovam G; Anthony, Daniel C; da Costa Vasconcelos, Pedro F; Picanço Diniz, Cristovam W
2016-01-01
It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous.
NASA Astrophysics Data System (ADS)
Huang, Niu; Xie, Yanan; Sebo, Bobby; Liu, Yumin; Sun, Xiaohua; Peng, Tao; Sun, Weiwei; Bu, Chenghao; Guo, Shishang; Zhao, Xingzhong
2013-11-01
The concentration of tetrabutyl titanate (TBT) and H2O influence on the reaction kinetics of TBT and acetic acid (AcOH) solvothermal system are systematically studied. It is found that TBT and H2O have greatly accelerated the hydrolysis-condensation process of the TBT-AcOH system. By adjusting those concentrations with reaction time, we prepare five kinds of sub-micron/micron precursors, which are hierarchical structures consisting of different primary building blocks. The morphology of these precursors varies from noninterlaced structures composed of flower-like microsphere and ellipsoid sphere to interlaced structures composed of flower-like microsphere interlaced nanofibers, ellipsoid spheres interlaced flower-like microsphere and nanoparticles interlaced flower-like microsphere. These interlaced structures are synthesized for the first time and are not ordinary mixtures of the noninterlaced structures. After heat treatment, these precursors are transformed to anatase TiO2. Shape-dependent photovoltaic performances of dye-sensitized solar cells (DSSCs) are also discussed. DSSCs based on these hierarchical sub-micron/micron TiO2 show 7.3%-7.9% energy conversion efficiencies, and the devices based on interlaced structures have higher efficiencies (7.4%-7.9%) than those of the devices based on noninterlaced structures (7.3%-7.6%).
ERIC Educational Resources Information Center
Zhang, Zhidong
2016-01-01
This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…
Kang, Ningxuan; Zhao, Cong; Li, Jingshan; Horst, John A.
2018-01-01
Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI. PMID:29398722
Kang, Ningxuan; Zhao, Cong; Li, Jingshan; Horst, John A
2016-01-01
Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.
NASA Astrophysics Data System (ADS)
Khristoforov, Mikhail; Kleptsyn, Victor; Triestino, Michele
2016-07-01
This paper is inspired by the problem of understanding in a mathematical sense the Liouville quantum gravity on surfaces. Here we show how to define a stationary random metric on self-similar spaces which are the limit of nice finite graphs: these are the so-called hierarchical graphs. They possess a well-defined level structure and any level is built using a simple recursion. Stopping the construction at any finite level, we have a discrete random metric space when we set the edges to have random length (using a multiplicative cascade with fixed law {m}). We introduce a tool, the cut-off process, by means of which one finds that renormalizing the sequence of metrics by an exponential factor, they converge in law to a non-trivial metric on the limit space. Such limit law is stationary, in the sense that glueing together a certain number of copies of the random limit space, according to the combinatorics of the brick graph, the obtained random metric has the same law when rescaled by a random factor of law {m} . In other words, the stationary random metric is the solution of a distributional equation. When the measure m has continuous positive density on {mathbf{R}+}, the stationary law is unique up to rescaling and any other distribution tends to a rescaled stationary law under the iterations of the hierarchical transformation. We also investigate topological and geometric properties of the random space when m is log-normal, detecting a phase transition influenced by the branching random walk associated to the multiplicative cascade.
Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective
Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.
2009-01-01
Research on human and animal behavior has long emphasized its hierarchical structure — the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely considered to reflect prefrontal cortical functions. In this paper, we reexamine behavioral hierarchy and its neural substrates from the point of view of recent developments in computational reinforcement learning. Specifically, we consider a set of approaches known collectively as hierarchical reinforcement learning, which extend the reinforcement learning paradigm by allowing the learning agent to aggregate actions into reusable subroutines or skills. A close look at the components of hierarchical reinforcement learning suggests how they might map onto neural structures, in particular regions within the dorsolateral and orbital prefrontal cortex. It also suggests specific ways in which hierarchical reinforcement learning might provide a complement to existing psychological models of hierarchically structured behavior. A particularly important question that hierarchical reinforcement learning brings to the fore is that of how learning identifies new action routines that are likely to provide useful building blocks in solving a wide range of future problems. Here and at many other points, hierarchical reinforcement learning offers an appealing framework for investigating the computational and neural underpinnings of hierarchically structured behavior. PMID:18926527
SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3
Smith, Lucian P.; Hucka, Michael; Hoops, Stefan; Finney, Andrew; Ginkel, Martin; Myers, Chris J.; Moraru, Ion; Liebermeister, Wolfram
2017-01-01
Summary Constructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models. PMID:26528566
The hierarchical expert tuning of PID controllers using tools of soft computing.
Karray, F; Gueaieb, W; Al-Sharhan, S
2002-01-01
We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.
Hierarchical Parallelization of Gene Differential Association Analysis
2011-01-01
Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels. PMID:21936916
Hierarchical parallelization of gene differential association analysis.
Needham, Mark; Hu, Rui; Dwarkadas, Sandhya; Qiu, Xing
2011-09-21
Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.
Hierarchical cluster-tendency analysis of the group structure in the foreign exchange market
NASA Astrophysics Data System (ADS)
Wu, Xin-Ye; Zheng, Zhi-Gang
2013-08-01
A hierarchical cluster-tendency (HCT) method in analyzing the group structure of networks of the global foreign exchange (FX) market is proposed by combining the advantages of both the minimal spanning tree (MST) and the hierarchical tree (HT). Fifty currencies of the top 50 World GDP in 2010 according to World Bank's database are chosen as the underlying system. By using the HCT method, all nodes in the FX market network can be "colored" and distinguished. We reveal that the FX networks can be divided into two groups, i.e., the Asia-Pacific group and the Pan-European group. The results given by the hierarchical cluster-tendency method agree well with the formerly observed geographical aggregation behavior in the FX market. Moreover, an oil-resource aggregation phenomenon is discovered by using our method. We find that gold could be a better numeraire for the weekly-frequency FX data.
Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui
2016-01-01
Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for
NASA Astrophysics Data System (ADS)
Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui
2016-05-01
Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for
Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A; Huang, Yonggang; Zhang, Yihui
2016-05-01
Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for
Topological dimension tunes activity patterns in hierarchical modular networks
NASA Astrophysics Data System (ADS)
Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.
2017-11-01
Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.
Deng, De-Ming; Lu, Yi-Ta; Chang, Cheng-Hung
2017-06-01
The legality of using simple kinetic schemes to determine the stochastic properties of a complex system depends on whether the fluctuations generated from hierarchical equivalent schemes are consistent with one another. To analyze this consistency, we perform lumping processes on the stochastic differential equations and the generalized fluctuation-dissipation theorem and apply them to networks with the frequently encountered Arrhenius-type transition rates. The explicit Langevin force derived from those networks enables us to calculate the state fluctuations caused by the intrinsic and extrinsic noises on the free energy surface and deduce their relations between kinetically equivalent networks. In addition to its applicability to wide classes of network related systems, such as those in structural and systems biology, the result sheds light on the fluctuation relations for general physical variables in Keizer's canonical theory.
NASA Astrophysics Data System (ADS)
Chen, Shih-Hao; Chow, Chi-Wai
2015-01-01
Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) based visible light communication (VLC) systems. The MIMO VLC system that uses the mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from the n×n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding this signal is to detect the signal direction. If the LED transmitter (Tx) is rotated, the Rx may not realize the rotation and transmission error can occur. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n×n RGB LED array as the MIMO Tx. In our study, a novel two dimensional Hadamard coding scheme is proposed. Using the different LED color layers to indicate the rotation, a low complexity rotation detection method can be used for improving the quality of received signal. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.
Kotliar, Natasha B.; Wiens, John A.
1990-01-01
We develop a hierarchical model of heterogeneity that provides a framework for classifying patch structure across a range of scales. Patches at lower levels in the hierarchy are more simplistic and correspond to the traditional view of patches. At levels approaching the upper bounds of the hierarchy the internal structure becomes more heterogeneous and boundaries more ambiguous. At each level in the hierarchy, patch structure will be influenced by both contrast among patches as well as the degree of aggregation of patches at lower levels in the hierarchy. We apply this model to foraging theory, but it has wider applications as in the study of habitat selection, population dynamics, and habitat fragmentation. It may also be useful in expanding the realm of landscape ecology beyond the current focus on anthropocentric scales.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.
Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694
HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.
Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye
2017-02-09
In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paik, Taejong; Yun, Hongseok; Fleury, Blaise
We demonstrate the fabrication of hierarchical materials by controlling the structure of highly ordered binary nanocrystal superlattices (BNSLs) on multiple length scales. Combinations of magnetic, plasmonic, semiconducting, and insulating colloidal nanocrystal (NC) building blocks are self-assembled into BNSL membranes via the liquid–interfacial assembly technique. Free-standing BNSL membranes are transferred onto topographically structured poly(dimethylsiloxane) molds via the Langmuir–Schaefer technique and then deposited in patterns onto substrates via transfer printing. BNSLs with different structural motifs are successfully patterned into various meso- and microstructures such as lines, circles, and even three-dimensional grids across large-area substrates. A combination of electron microscopy and grazing incidencemore » small-angle X-ray scattering (GISAXS) measurements confirm the ordering of NC building blocks in meso- and micropatterned BNSLs. This technique demonstrates structural diversity in the design of hierarchical materials by assembling BNSLs from NC building blocks of different composition and size by patterning BNSLs into various size and shape superstructures of interest for a broad range of applications.« less
Hierarchically clustered adaptive quantization CMAC and its learning convergence.
Teddy, S D; Lai, E M K; Quek, C
2007-11-01
The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically
Field-aligned currents associated with multiple arc systems
NASA Astrophysics Data System (ADS)
Wu, J.; Knudsen, D. J.; Gillies, D. M.; Donovan, E.; Burchill, J. K.
2016-12-01
It is often thought that auroral arcs are a direct consequence of upward field-aligned currents. In fact, the relation between currents and brightness is more complicated. Multiple auroral arc systems provide and opportunity to study this relation in detail; this information can be used as a test of models for quasi-static arc formation. In this study, we have identified two types of FAC configurations in multiple parallel arc systems using ground-based optical data from the THEMIS all-sky imagers (ASIs), magnetometers and electric field instruments onboard the Swarm satellites during the period from December 2013 to March 2015. In type 1 events, each arc is an intensification within a broad, unipolar current sheet and downward currents only exist outside the upward current sheet. In type 2 events, multiple arc systems represent a collection of multiple up/down current pairs. By collecting 12 events for type 1 and 17 events for type 2, we find that (1) Type 1 events are mainly located between 22-23MLT. Type 2 events are mainly located around midnight. (2) The typical size of upward and downward FAC in type 2 events are comparable, while upward FAC in type 1 events are larger than downward FAC. (3) Upward currents with more arcs embedded have larger intensities and widths. (4) There is no significant difference between the characteristic widths of multiple arcs and single arcs.
Multiple pass laser amplifier system
Brueckner, Keith A.; Jorna, Siebe; Moncur, N. Kent
1977-01-01
A laser amplification method for increasing the energy extraction efficiency from laser amplifiers while reducing the energy flux that passes through a flux limited system which includes apparatus for decomposing a linearly polarized light beam into multiple components, passing the components through an amplifier in delayed time sequence and recombining the amplified components into an in phase linearly polarized beam.
Dynamical configurations of celestial systems comprised of multiple irregular bodies
NASA Astrophysics Data System (ADS)
Jiang, Yu; Zhang, Yun; Baoyin, Hexi; Li, Junfeng
2016-09-01
This manuscript considers the main features of the nonlinear dynamics of multiple irregular celestial body systems. The gravitational potential, static electric potential, and magnetic potential are considered. Based on the three established potentials, we show that three conservative values exist for this system, including a Jacobi integral. The equilibrium conditions for the system are derived and their stability analyzed. The equilibrium conditions of a celestial system comprised of n irregular bodies are reduced to 12n - 9 equations. The dynamical results are applied to simulate the motion of multiple-asteroid systems. The simulation is useful for the study of the stability of multiple irregular celestial body systems and for the design of spacecraft orbits to triple-asteroid systems discovered in the solar system. The dynamical configurations of the five triple-asteroid systems 45 Eugenia, 87 Sylvia, 93 Minerva, 216 Kleopatra, and 136617 1994CC, and the six-body system 134340 Pluto are calculated and analyzed.
Dynamic Organization of Hierarchical Memories
Kurikawa, Tomoki; Kaneko, Kunihiko
2016-01-01
In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a “dynamic categorization”; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity. PMID:27618549
Hierarchically nested river landform sequences
NASA Astrophysics Data System (ADS)
Pasternack, G. B.; Weber, M. D.; Brown, R. A.; Baig, D.
2017-12-01
River corridors exhibit landforms nested within landforms repeatedly down spatial scales. In this study we developed, tested, and implemented a new way to create river classifications by mapping domains of fluvial processes with respect to the hierarchical organization of topographic complexity that drives fluvial dynamism. We tested this approach on flow convergence routing, a morphodynamic mechanism with different states depending on the structure of nondimensional topographic variability. Five nondimensional landform types with unique functionality (nozzle, wide bar, normal channel, constricted pool, and oversized) represent this process at any flow. When this typology is nested at base flow, bankfull, and floodprone scales it creates a system with up to 125 functional types. This shows how a single mechanism produces complex dynamism via nesting. Given the classification, we answered nine specific scientific questions to investigate the abundance, sequencing, and hierarchical nesting of these new landform types using a 35-km gravel/cobble river segment of the Yuba River in California. The nested structure of flow convergence routing landforms found in this study revealed that bankfull landforms are nested within specific floodprone valley landform types, and these types control bankfull morphodynamics during moderate to large floods. As a result, this study calls into question the prevailing theory that the bankfull channel of a gravel/cobble river is controlled by in-channel, bankfull, and/or small flood flows. Such flows are too small to initiate widespread sediment transport in a gravel/cobble river with topographic complexity.
Multiple Imputation of Multilevel Missing Data-Rigor versus Simplicity
ERIC Educational Resources Information Center
Drechsler, Jörg
2015-01-01
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Hierarchical coefficient of a multifractal based network
NASA Astrophysics Data System (ADS)
Moreira, Darlan A.; Lucena, Liacir dos Santos; Corso, Gilberto
2014-02-01
The hierarchical property for a general class of networks stands for a power-law relation between clustering coefficient, CC and connectivity k: CC∝kβ. This relation is empirically verified in several biologic and social networks, as well as in random and deterministic network models, in special for hierarchical networks. In this work we show that the hierarchical property is also present in a Lucena network. To create a Lucena network we use the dual of a multifractal lattice ML, the vertices are the sites of the ML and links are established between neighbouring lattices, therefore this network is space filling and planar. Besides a Lucena network shows a scale-free distribution of connectivity. We deduce a relation for the maximal local clustering coefficient CCimax of a vertex i in a planar graph. This condition expresses that the number of links among neighbour, N△, of a vertex i is equal to its connectivity ki, that means: N△=ki. The Lucena network fulfils the condition N△≃ki independent of ki and the anisotropy of ML. In addition, CCmax implies the threshold β=1 for the hierarchical property for any scale-free planar network.
Sankar, Sharanya; Sharma, Chandra S; Rath, Subha N; Ramakrishna, Seeram
2018-01-01
Biomimetic scaffolds mimicking the natural hierarchical structure of tissues have recently attracted the interest of researchers and provide a promising strategy to resemble the nonhomogeneous property of tissues. This review provides an overview of the various hierarchical length scales in the native tissues of the musculoskeletal system. It further focuses on electrospinning as a technique to mimic the tissue structures with specific emphasis on bone. The effect of cellular alignment, infiltration, vascularisation, and differentiation in these nanostructures has also been discussed. An outline of the various additive manufacturing techniques in combination with electrospinning has been elaborated. The review concludes with the challenges and future directions to understand the intricacies of bottom-up approach to engineer the systems at a macroscale. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Wang, Mingyang; Zhang, Feifei; Song, Chao; Shi, Pengfei; Zhu, Jin
2016-07-01
Innovation in hypotheses is a key transformative driver for scientific development. The conventional centralized hypothesis formulation approach, where a dominant hypothesis is typically derived from a primary phenomenon, can, inevitably, impose restriction on the range of conceivable experiments and legitimate hypotheses, and ultimately impede understanding of the system of interest. We report herein the proposal of a decentralized approach for the formulation of hypotheses, through initial preconception-free phenomenon accumulation and subsequent reticular logical reasoning processes. The two-step approach can provide an unbiased, panoramic view of the system and as such should enable the generation of a set of more coherent and therefore plausible hypotheses. As a proof-of-concept demonstration of the utility of this open-ended approach, a hierarchical model has been developed for a prion self-assembled system, allowing insight into hitherto elusive static and dynamic features associated with this intriguing structure.
Signaling Hierarchical and Sequential Organization in Expository Text
ERIC Educational Resources Information Center
Lorch, Robert; Lemarie, Julie; Grant, Russell
2011-01-01
Four experiments tested a hypothesized function of signaling devices, namely, to communicate information about text organization. Experiments 1 and 2 compared headings that communicated the hierarchical organization of text topics with headings that did not communicate the hierarchical organization. Signaling organization led to more complete and…
Multiple Fault Isolation in Redundant Systems
NASA Technical Reports Server (NTRS)
Pattipati, Krishna R.; Patterson-Hine, Ann; Iverson, David
1997-01-01
Fault diagnosis in large-scale systems that are products of modern technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption.
Multiple Fault Isolation in Redundant Systems
NASA Technical Reports Server (NTRS)
Pattipati, Krishna R.
1997-01-01
Fault diagnosis in large-scale systems that are products of modem technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption.
Hu, Ming-Hsia; Yeh, Chih-Jun; Chen, Tou-Rong; Wang, Ching-Yi
2014-01-01
A valid, time-efficient and easy-to-use instrument is important for busy clinical settings, large scale surveys, or community screening use. The purpose of this study was to validate the mobility hierarchical disability categorization model (an abbreviated model) by investigating its concurrent validity with the multidimensional hierarchical disability categorization model (a comprehensive model) and triangulating both models with physical performance measures in older adults. 604 community-dwelling older adults of at least 60 years in age volunteered to participate. Self-reported function on mobility, instrumental activities of daily living (IADL) and activities of daily living (ADL) domains were recorded and then the disability status determined based on both the multidimensional hierarchical categorization model and the mobility hierarchical categorization model. The physical performance measures, consisting of grip strength and usual and fastest gait speeds (UGS, FGS), were collected on the same day. Both categorization models showed high correlation (γs = 0.92, p < 0.001) and agreement (kappa = 0.61, p < 0.0001). Physical performance measures demonstrated significant different group means among the disability subgroups based on both categorization models. The results of multiple regression analysis indicated that both models individually explain similar amount of variance on all physical performances, with adjustments for age, sex, and number of comorbidities. Our results found that the mobility hierarchical disability categorization model is a valid and time efficient tool for large survey or screening use.
Multiple access techniques and spectrum utilization of the GLOBALSTAR mobile satellite system
NASA Astrophysics Data System (ADS)
Louie, Ming; Cohen, Michel; Rouffet, Denis; Gilhousen, Klein S.
The GLOBALSTAR System is a Low Earth Orbit (LEO) satellite-based mobile communications system that is interoperable with the current and future Public Land Mobile Network (PLMN). The GLOBALSTAR System concept is based upon technological advancement in two key areas: (1) the advancement in LEO satellite technology; (2) the advancement in cellular telephone technology, including the commercial applications of Code Division Multiple Access (CDMA) technologies, and of the most recent progress in Time Division Multiple Access technologies. The GLOBALSTAR System uses elements of CDMA, Frequency Division Multiple Access (FDMA), and Time Division Multiple Access (TDMA) technology, combining with satellite Multiple Beam Antenna (MBA) technology, to arrive at one of the most efficient modulation and multiple access system ever proposed for a satellite communications system. The technology used in GLOBALSTAR exploits the following techniques in obtaining high spectral efficiency and affordable cost per channel, with minimum coordination among different systems: power control, in open and closed loops, voice activation, spot beam satellite antenna for frequency reuse, weighted satellite antenna gain, multiple satellite coverage, and handoff between satellites. The GLOBALSTAR system design will use the following frequency bands: 1610-1626.5 MHz for up-link and 2483.5-2500 MHz for down-link.
Multiple channel data acquisition system
Crawley, H. Bert; Rosenberg, Eli I.; Meyer, W. Thomas; Gorbics, Mark S.; Thomas, William D.; McKay, Roy L.; Homer, Jr., John F.
1990-05-22
A multiple channel data acquisition system for the transfer of large amounts of data from a multiplicity of data channels has a plurality of modules which operate in parallel to convert analog signals to digital data and transfer that data to a communications host via a FASTBUS. Each module has a plurality of submodules which include a front end buffer (FEB) connected to input circuitry having an analog to digital converter with cache memory for each of a plurality of channels. The submodules are interfaced with the FASTBUS via a FASTBUS coupler which controls a module bus and a module memory. The system is triggered to effect rapid parallel data samplings which are stored to the cache memories. The cache memories are uploaded to the FEBs during which zero suppression occurs. The data in the FEBs is reformatted and compressed by a local processor during transfer to the module memory. The FASTBUS coupler is used by the communications host to upload the compressed and formatted data from the module memory. The local processor executes programs which are downloaded to the module memory through the FASTBUS coupler.
Multiple channel data acquisition system
Crawley, H.B.; Rosenberg, E.I.; Meyer, W.T.; Gorbics, M.S.; Thomas, W.D.; McKay, R.L.; Homer, J.F. Jr.
1990-05-22
A multiple channel data acquisition system for the transfer of large amounts of data from a multiplicity of data channels has a plurality of modules which operate in parallel to convert analog signals to digital data and transfer that data to a communications host via a FASTBUS. Each module has a plurality of submodules which include a front end buffer (FEB) connected to input circuitry having an analog to digital converter with cache memory for each of a plurality of channels. The submodules are interfaced with the FASTBUS via a FASTBUS coupler which controls a module bus and a module memory. The system is triggered to effect rapid parallel data samplings which are stored to the cache memories. The cache memories are uploaded to the FEBs during which zero suppression occurs. The data in the FEBs is reformatted and compressed by a local processor during transfer to the module memory. The FASTBUS coupler is used by the communications host to upload the compressed and formatted data from the module memory. The local processor executes programs which are downloaded to the module memory through the FASTBUS coupler. 25 figs.
Generic hierarchical engine for mask data preparation
NASA Astrophysics Data System (ADS)
Kalus, Christian K.; Roessl, Wolfgang; Schnitker, Uwe; Simecek, Michal
2002-07-01
Electronic layouts are usually flattened on their path from the hierarchical source downstream to the wafer. Mask data preparation has certainly been identified as a severe bottleneck since long. Data volumes are not only doubling every year along the ITRS roadmap. With the advent of optical proximity correction and phase-shifting masks data volumes are escalating up to non-manageable heights. Hierarchical treatment is one of the most powerful means to keep memory and CPU consumption in reasonable ranges. Only recently, however, has this technique acquired more public attention. Mask data preparation is the most critical area calling for a sound infrastructure to reduce the handling problem. Gaining more and more attention though, are other applications such as large area simulation and manufacturing rule checking (MRC). They all would profit from a generic engine capable to efficiently treat hierarchical data. In this paper we will present a generic engine for hierarchical treatment which solves the major problem, steady transitions along cell borders. Several alternatives exist how to walk through the hierarchy tree. They have, to date, not been thoroughly investigated. One is a bottom-up attempt to treat cells starting with the most elementary cells. The other one is a top-down approach which lends itself to creating a new hierarchy tree. In addition, since the variety, degree of hierarchy and quality of layouts extends over a wide range a generic engine has to take intelligent decisions when exploding the hierarchy tree. Several applications will be shown, in particular how far the limits can be pushed with the current hierarchical engine.
Hierarchical effects on target detection and conflict monitoring
Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong
2016-01-01
Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989
Multiple-Agent Air/Ground Autonomous Exploration Systems
NASA Technical Reports Server (NTRS)
Fink, Wolfgang; Chao, Tien-Hsin; Tarbell, Mark; Dohm, James M.
2007-01-01
Autonomous systems of multiple-agent air/ground robotic units for exploration of the surfaces of remote planets are undergoing development. Modified versions of these systems could be used on Earth to perform tasks in environments dangerous or inaccessible to humans: examples of tasks could include scientific exploration of remote regions of Antarctica, removal of land mines, cleanup of hazardous chemicals, and military reconnaissance. A basic system according to this concept (see figure) would include a unit, suspended by a balloon or a blimp, that would be in radio communication with multiple robotic ground vehicles (rovers) equipped with video cameras and possibly other sensors for scientific exploration. The airborne unit would be free-floating, controlled by thrusters, or tethered either to one of the rovers or to a stationary object in or on the ground. Each rover would contain a semi-autonomous control system for maneuvering and would function under the supervision of a control system in the airborne unit. The rover maneuvering control system would utilize imagery from the onboard camera to navigate around obstacles. Avoidance of obstacles would also be aided by readout from an onboard (e.g., ultrasonic) sensor. Together, the rover and airborne control systems would constitute an overarching closed-loop control system to coordinate scientific exploration by the rovers.
Catalogue of Exoplanets in Multiple-Star-Systems
NASA Astrophysics Data System (ADS)
Schwarz, Richard; Funk, Barbara; Bazsó, Ákos; Pilat-Lohinger, Elke
2017-07-01
Cataloguing the data of exoplanetary systems becomes more and more important, due to the fact that they conclude the observations and support the theoretical studies. Since 1995 there is a database which list most of the known exoplanets (The Extrasolar Planets Encyclopaedia is available at http://exoplanet.eu/ and described at Schneider et al. 2011). With the growing number of detected exoplanets in binary and multiple star systems it became more important to mark and to separate them into a new database. Therefore we started to compile a catalogue for binary and multiple star systems. Since 2013 the catalogue can be found at http://www.univie.ac.at/adg/schwarz/multiple.html (description can be found at Schwarz et al. 2016) which will be updated regularly and is linked to the Extrasolar Planets Encyclopaedia. The data of the binary catalogue can be downloaded as a file (.csv) and used for statistical purposes. Our database is divided into two parts: the data of the stars and the planets, given in a separate list. Every columns of the list can be sorted in two directions: ascending, meaning from the lowest value to the highest, or descending. In addition an introduction and help is also given in the menu bar of the catalogue including an example list.
The Role of Prototype Learning in Hierarchical Models of Vision
ERIC Educational Resources Information Center
Thomure, Michael David
2014-01-01
I conduct a study of learning in HMAX-like models, which are hierarchical models of visual processing in biological vision systems. Such models compute a new representation for an image based on the similarity of image sub-parts to a number of specific patterns, called prototypes. Despite being a central piece of the overall model, the issue of…
Hierarchical structure and dynamics of oligocarbonate-functionalized PEG block copolymer gels
NASA Astrophysics Data System (ADS)
Prabhu, Vivek; Wei, Guangmin; Ali, Samim; Venkataraman, Shrinivas; Yang, Yi Yan; Hedrick, James
Hierarchical, self-assembled block copolymers in aqueous solutions provide advanced materials for biomaterial applications. Recent advancements in the synthesis of aliphatic polycarbonates have shown nontraditional micellar and hierarchical structures driven by the supramolecular assembly of the carbonate block functionality that includes cholesterol, vitamin D, and fluorene. This presentation shall describe the supramolecular assembly structure and dynamics observed by static and dynamic light scattering, small-angle neutron scattering and transmission electron microscopy in a model pi-pi stacking driven fluorene system. The combination of real-space and reciprocal space methods to develop appropriate models that quantify the structure from the micelle to transient gel network will be discussed. 1) Biomedical Research Council, Agency for Science, Technology and Research, Singapore, 2) NIST Materials Genome Initiative.
Hierarchical drug release of pH-sensitive liposomes encapsulating aqueous two phase system.
Zhang, Xunan; Zong, Wei; Bi, Hongmei; Zhao, Kunming; Fuhs, Thomas; Hu, Ying; Cheng, Wenlong; Han, Xiaojun
2018-06-01
As promising drug delivery vehicles, previous investigations of liposomes as carriers are primarily focused on insertion and modification of lipid membrane interfaces. The utility of the inner core seems to be overlooked. Herein, we developed pH-sensitive liposomes (PSLs) containing an aqueous two phase system (ATPS), and intriguingly discovered their hierarchical release under acidic stimuli. ATPS containing two polymers (poly(ethylene glycol) (PEG) and dextran) is homogeneous above phase transition temperature when producing ATPS-liposomes, and separated into PEG-rich phase and dextran-rich phase after cooling down to room temperature. The overall release time of ATPS-liposomes is divided into two stages and prolonged compared to simple aqueous liposomes. The unique release profile is due to the disproportional distribution of drugs in two phases. Doxorubicin (DOX) is loaded in the ATPS-liposomes, and their half maximum inhibition concentration on HeLa cells is 0.018 μmol L -1 , which means 27.5 fold increase in inhibition efficiency over free DOX. Copyright © 2018 Elsevier B.V. All rights reserved.
The judgement of simultaneous commutation failure in HVDC about hierarchical connection to AC grid
NASA Astrophysics Data System (ADS)
Li, Ming; Song, Xinli; Huang, Daoshan; Liu, Wenzhuo; Zhao, Shutao; Ye, Xiaohui; Meng, Hang
2017-09-01
The hierarchical connection to AC grid at inverter sides in UHVDC has been take in several projects. This paper introduced the frame of the connection mode in hierarchical access system and compared it with the traditional one at the case of HVDC-Cigre. Then the criterion of commutation failure according to the same valves current was deduced. In order to verify the accuracy of the criterion, this paper used PSD-BPA (Bonneville Power Administration) to simulate the setting voltage drop in the East China power grid and certified the correctness of the formula.
Ma, Songyun; Scheider, Ingo; Bargmann, Swantje
2016-09-01
An anisotropic constitutive model is proposed in the framework of finite deformation to capture several damage mechanisms occurring in the microstructure of dental enamel, a hierarchical bio-composite. It provides the basis for a homogenization approach for an efficient multiscale (in this case: multiple hierarchy levels) investigation of the deformation and damage behavior. The influence of tension-compression asymmetry and fiber-matrix interaction on the nonlinear deformation behavior of dental enamel is studied by 3D micromechanical simulations under different loading conditions and fiber lengths. The complex deformation behavior and the characteristics and interaction of three damage mechanisms in the damage process of enamel are well captured. The proposed constitutive model incorporating anisotropic damage is applied to the first hierarchical level of dental enamel and validated by experimental results. The effect of the fiber orientation on the damage behavior and compressive strength is studied by comparing micro-pillar experiments of dental enamel at the first hierarchical level in multiple directions of fiber orientation. A very good agreement between computational and experimental results is found for the damage evolution process of dental enamel. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah
2015-01-01
The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.
Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring
2012-01-01
Background Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. Results The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function
Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.
Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl
2012-07-13
Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results
The hierarchical structure of self-reported impulsivity
Kirby, Kris N.; Finch, Julia C.
2010-01-01
The hierarchical structure of 95 self-reported impulsivity items, along with delay-discount rates for money, was examined. A large sample of college students participated in the study (N = 407). Items represented every previously proposed dimension of self-reported impulsivity. Exploratory PCA yielded at least 7 interpretable components: Prepared/Careful, Impetuous, Divertible, Thrill and Risk Seeking, Happy-Go-Lucky, Impatiently Pleasure Seeking, and Reserved. Discount rates loaded on Impatiently Pleasure Seeking, and correlated with the impulsiveness and venturesomeness scales from the I7 (Eysenck, Pearson, Easting, & Allsopp, 1985). The hierarchical emergence of the components was explored, and we show how this hierarchical structure may help organize conflicting dimensions found in previous analyses. Finally, we argue that the discounting model (Ainslie, 1975) provides a qualitative framework for understanding the dimensions of impulsivity. PMID:20224803
NASA Astrophysics Data System (ADS)
Wu, Zhijing; Li, Fengming; Zhang, Chuanzeng
2018-05-01
Inspired by the hierarchical structures of butterfly wing surfaces, a new kind of lattice structures with a two-order hierarchical periodicity is proposed and designed, and the band-gap properties are investigated by the spectral element method (SEM). The equations of motion of the whole structure are established considering the macro and micro periodicities of the system. The efficiency of the SEM is exploited in the modeling process and validated by comparing the results with that of the finite element method (FEM). Based on the highly accurate results in the frequency domain, the dynamic behaviors of the proposed two-order hierarchical structures are analyzed. An original and interesting finding is the existence of the distinct macro and micro stop-bands in the given frequency domain. The mechanisms for these two types of band-gaps are also explored. Finally, the relations between the hierarchical periodicities and the different types of the stop-bands are investigated by analyzing the parametrical influences.
Multiple-User, Multitasking, Virtual-Memory Computer System
NASA Technical Reports Server (NTRS)
Generazio, Edward R.; Roth, Don J.; Stang, David B.
1993-01-01
Computer system designed and programmed to serve multiple users in research laboratory. Provides for computer control and monitoring of laboratory instruments, acquisition and anlaysis of data from those instruments, and interaction with users via remote terminals. System provides fast access to shared central processing units and associated large (from megabytes to gigabytes) memories. Underlying concept of system also applicable to monitoring and control of industrial processes.
NASA Astrophysics Data System (ADS)
Guo, Mei; Li, Yu; Du, Kewen; Qiu, Chaochao; Dou, Gang; Zhang, Guoxin
2018-05-01
Improving specific energy of supercapacitors (SCs) at high power has been intensively investigated as a hot and challengeable topic. In this work, hierarchically porous carbon (HPC) materials with well-defined meso-/macro-pores are reported via the dehalogenation reaction of polyvinyl fluoride (PVDF) by NaNH2. The pore hierarchy is achievable mainly because of the coupled effects of NaNH2 activation and the template/bubbling effects of byproducts of NaF and NH3. Electron microscopy studies and Brunauer-Emmett-Teller (BET) measurements confirm that the structures of HPC samples contain multiple-scale pores assembled in a hierarchical pattern, and most of their volumes are contributed by mesopores. Aqueous symmetric supercapacitors (ASSCs) were fabricated using HPC-M7 materials, achieving an ultrahigh specific energy of 18.8 Wh kg-1 at specific power of 986.8 W kg-1. Remarkably, at the ultrahigh power of 14.3 kW kg-1, the HPC-ASSCs still output a very high specific energy of 16.7 Wh kg-1, which means the ASSCs can be charged or discharged within 4 s. The outstanding rate capacitive performance is mainly benefited from the hierarchical porous structure that allows highly efficient ion diffusion.
The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.
Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina
2018-05-23
Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional
Information processing in the primate visual system - An integrated systems perspective
NASA Technical Reports Server (NTRS)
Van Essen, David C.; Anderson, Charles H.; Felleman, Daniel J.
1992-01-01
The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.
Dynamical evolution of young binaries and multiple systems
NASA Astrophysics Data System (ADS)
Reipurth, B.
Most stars, and perhaps all, are born in small multiple systems whose components interact, leading to chaotic dynamic behavior. Some components are ejected, either into distant orbits or into outright escapes, while the remaining components form temporary and eventually permanent binary systems. More than half of all such breakups of multiple systems occur during the protostellar phase, leading to the occasional ejection of protostars outside their nascent cloud cores. Such orphaned protostars are observed as wide companions to embedded protostars, and thus allow the direct study of protostellar objects. Dynamic interactions during early stellar evolution explain the shape and enormous width of the separation distribution function of binaries, from close spectroscopic binaries to the widest binaries.
NASA Astrophysics Data System (ADS)
Mangaud, E.; Puthumpally-Joseph, R.; Sugny, D.; Meier, C.; Atabek, O.; Desouter-Lecomte, M.
2018-04-01
Optimal control theory is implemented with fully converged hierarchical equations of motion (HEOM) describing the time evolution of an open system density matrix strongly coupled to the bath in a spin-boson model. The populations of the two-level sub-system are taken as control objectives; namely, their revivals or exchange when switching off the field. We, in parallel, analyze how the optimal electric field consequently modifies the information back flow from the environment through different non-Markovian witnesses. Although the control field has a dipole interaction with the central sub-system only, its indirect influence on the bath collective mode dynamics is probed through HEOM auxiliary matrices, revealing a strong correlation between control and dissipation during a non-Markovian process. A heterojunction is taken as an illustrative example for modeling in a realistic way the two-level sub-system parameters and its spectral density function leading to a non-perturbative strong coupling regime with the bath. Although, due to strong system-bath couplings, control performances remain rather modest, the most important result is a noticeable increase of the non-Markovian bath response induced by the optimally driven processes.
Feng, Liang; Yuan, Shuai; Zhang, Liang-Liang; Tan, Kui; Li, Jia-Luo; Kirchon, Angelo; Liu, Ling-Mei; Zhang, Peng; Han, Yu; Chabal, Yves J; Zhou, Hong-Cai
2018-02-14
Sufficient pore size, appropriate stability, and hierarchical porosity are three prerequisites for open frameworks designed for drug delivery, enzyme immobilization, and catalysis involving large molecules. Herein, we report a powerful and general strategy, linker thermolysis, to construct ultrastable hierarchically porous metal-organic frameworks (HP-MOFs) with tunable pore size distribution. Linker instability, usually an undesirable trait of MOFs, was exploited to create mesopores by generating crystal defects throughout a microporous MOF crystal via thermolysis. The crystallinity and stability of HP-MOFs remain after thermolabile linkers are selectively removed from multivariate metal-organic frameworks (MTV-MOFs) through a decarboxylation process. A domain-based linker spatial distribution was found to be critical for creating hierarchical pores inside MTV-MOFs. Furthermore, linker thermolysis promotes the formation of ultrasmall metal oxide nanoparticles immobilized in an open framework that exhibits high catalytic activity for Lewis acid-catalyzed reactions. Most importantly, this work provides fresh insights into the connection between linker apportionment and vacancy distribution, which may shed light on probing the disordered linker apportionment in multivariate systems, a long-standing challenge in the study of MTV-MOFs.
Multiple-Flat-Panel System Displays Multidimensional Data
NASA Technical Reports Server (NTRS)
Gundo, Daniel; Levit, Creon; Henze, Christopher; Sandstrom, Timothy; Ellsworth, David; Green, Bryan; Joly, Arthur
2006-01-01
The NASA Ames hyperwall is a display system designed to facilitate the visualization of sets of multivariate and multidimensional data like those generated in complex engineering and scientific computations. The hyperwall includes a 77 matrix of computer-driven flat-panel video display units, each presenting an image of 1,280 1,024 pixels. The term hyperwall reflects the fact that this system is a more capable successor to prior computer-driven multiple-flat-panel display systems known by names that include the generic term powerwall and the trade names PowerWall and Powerwall. Each of the 49 flat-panel displays is driven by a rack-mounted, dual-central-processing- unit, workstation-class personal computer equipped with a hig-hperformance graphical-display circuit card and with a hard-disk drive having a storage capacity of 100 GB. Each such computer is a slave node in a master/ slave computing/data-communication system (see Figure 1). The computer that acts as the master node is similar to the slave-node computers, except that it runs the master portion of the system software and is equipped with a keyboard and mouse for control by a human operator. The system utilizes commercially available master/slave software along with custom software that enables the human controller to interact simultaneously with any number of selected slave nodes. In a powerwall, a single rendering task is spread across multiple processors and then the multiple outputs are tiled into one seamless super-display. It must be noted that the hyperwall concept subsumes the powerwall concept in that a single scene could be rendered as a mosaic image on the hyperwall. However, the hyperwall offers a wider set of capabilities to serve a different purpose: The hyperwall concept is one of (1) simultaneously displaying multiple different but related images, and (2) providing means for composing and controlling such sets of images. In place of elaborate software or hardware crossbar switches, the
Multiplicity fluctuations and collective flow in small colliding systems
NASA Astrophysics Data System (ADS)
Kawaguchi, Koji; Murase, Koichi; Hirano, Tetsufumi
2017-11-01
Recent observation of collective-flow-like behaviours in small colliding systems attracts significant theoretical and experimental interests. In large colliding systems, large collective flow has been interpreted as manifestation of almost-perfect fluidity of the quark gluon plasma (QGP). So it is quite intriguing to explore how small the QGP can be as a fluid. Multiplicity fluctuations play a crucial role in centrality definition of the events in small colliding systems since the fluctuations are, in general, more important as the system size is getting smaller. To consider the correct multiplicity fluctuations, we employ PYTHIA which naturally describes multiplicity distribution in p+p collisions. We superpose p+p collisions by taking into account the number of participants and that of binary collisions from Monte-Carlo version of Glauber model and evaluate initial entropy density distributions which contain not only multiplicity fluctuations but also fluctuations of longitudinal profiles. Solving hydrodynamic equations followed by the hadronic afterburner, we calculate transverse momentum spectra, elliptic and triangular flow parameters in p+Au, d+Au and 3He+Au collisions at the RHIC energy and p+Pb collisions at the LHC energy. Although a large fraction of final anisotropic flow parameters comes from the fluid-dynamical stage, the effects of hadronic rescatterings turn out to be also important as well in understanding of the flow data in small colliding systems.
Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data
Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...
2016-10-02
Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less
Multiple Object Based RFID System Using Security Level
NASA Astrophysics Data System (ADS)
Kim, Jiyeon; Jung, Jongjin; Ryu, Ukjae; Ko, Hoon; Joe, Susan; Lee, Yongjun; Kim, Boyeon; Chang, Yunseok; Lee, Kyoonha
2007-12-01
RFID systems are increasingly applied for operational convenience in wide range of industries and individual life. However, it is uneasy for a person to control many tags because common RFID systems have the restriction that a tag used to identify just a single object. In addition, RFID systems can make some serious problems in violation of privacy and security because of their radio frequency communication. In this paper, we propose a multiple object RFID tag which can keep multiple object identifiers for different applications in a same tag. The proposed tag allows simultaneous access for their pair applications. We also propose an authentication protocol for multiple object tag to prevent serious problems of security and privacy in RFID applications. Especially, we focus on efficiency of the authentication protocol by considering security levels of applications. In the proposed protocol, the applications go through different authentication procedures according to security level of the object identifier stored in the tag. We implemented the proposed RFID scheme and made experimental results about efficiency and stability for the scheme.
3D Printing of Hierarchical Silk Fibroin Structures.
Sommer, Marianne R; Schaffner, Manuel; Carnelli, Davide; Studart, André R
2016-12-21
Like many other natural materials, silk is hierarchically structured from the amino acid level up to the cocoon or spider web macroscopic structures. Despite being used industrially in a number of applications, hierarchically structured silk fibroin objects with a similar degree of architectural control as in natural structures have not been produced yet due to limitations in fabrication processes. In a combined top-down and bottom-up approach, we exploit the freedom in macroscopic design offered by 3D printing and the template-guided assembly of ink building blocks at the meso- and nanolevel to fabricate hierarchical silk porous materials with unprecedented structural control. Pores with tunable sizes in the range 40-350 μm are generated by adding sacrificial organic microparticles as templates to a silk fibroin-based ink. Commercially available wax particles or monodisperse polycaprolactone made by microfluidics can be used as microparticle templates. Since closed pores are generated after template removal, an ultrasonication treatment can optionally be used to achieve open porosity. Such pore templating particles can be further modified with nanoparticles to create a hierarchical template that results in porous structures with a defined nanotopography on the pore walls. The hierarchically porous silk structures obtained with this processing technique can potentially be utilized in various application fields from structural materials to thermal insulation to tissue engineering scaffolds.
The Capacity Gain of Orbital Angular Momentum Based Multiple-Input-Multiple-Output System
Zhang, Zhuofan; Zheng, Shilie; Chen, Yiling; Jin, Xiaofeng; Chi, Hao; Zhang, Xianmin
2016-01-01
Wireless communication using electromagnetic wave carrying orbital angular momentum (OAM) has attracted increasing interest in recent years, and its potential to increase channel capacity has been explored widely. In this paper, we compare the technique of using uniform linear array consist of circular traveling-wave OAM antennas for multiplexing with the conventional multiple-in-multiple-out (MIMO) communication method, and numerical results show that the OAM based MIMO system can increase channel capacity while communication distance is long enough. An equivalent model is proposed to illustrate that the OAM multiplexing system is equivalent to a conventional MIMO system with a larger element spacing, which means OAM waves could decrease the spatial correlation of MIMO channel. In addition, the effects of some system parameters, such as OAM state interval and element spacing, on the capacity advantage of OAM based MIMO are also investigated. Our results reveal that OAM waves are complementary with MIMO method. OAM waves multiplexing is suitable for long-distance line-of-sight (LoS) communications or communications in open area where the multi-path effect is weak and can be used in massive MIMO systems as well. PMID:27146453
Architecture of the parallel hierarchical network for fast image recognition
NASA Astrophysics Data System (ADS)
Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule
2016-09-01
Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.
Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions
Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.
2014-01-01
We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630
Zeki, Semir
2016-10-01
Results from a variety of sources, some many years old, lead ineluctably to a re-appraisal of the twin strategies of hierarchical and parallel processing used by the brain to construct an image of the visual world. Contrary to common supposition, there are at least three 'feed-forward' anatomical hierarchies that reach the primary visual cortex (V1) and the specialized visual areas outside it, in parallel. These anatomical hierarchies do not conform to the temporal order with which visual signals reach the specialized visual areas through V1. Furthermore, neither the anatomical hierarchies nor the temporal order of activation through V1 predict the perceptual hierarchies. The latter shows that we see (and become aware of) different visual attributes at different times, with colour leading form (orientation) and directional visual motion, even though signals from fast-moving, high-contrast stimuli are among the earliest to reach the visual cortex (of area V5). Parallel processing, on the other hand, is much more ubiquitous than commonly supposed but is subject to a barely noticed but fundamental aspect of brain operations, namely that different parallel systems operate asynchronously with respect to each other and reach perceptual endpoints at different times. This re-assessment leads to the conclusion that the visual brain is constituted of multiple, parallel and asynchronously operating task- and stimulus-dependent hierarchies (STDH); which of these parallel anatomical hierarchies have temporal and perceptual precedence at any given moment is stimulus and task related, and dependent on the visual brain's ability to undertake multiple operations asynchronously. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Validity and Realibility of Chemistry Systemic Multiple Choices Questions (CSMCQs)
ERIC Educational Resources Information Center
Priyambodo, Erfan; Marfuatun
2016-01-01
Nowadays, Rasch model analysis is used widely in social research, moreover in educational research. In this research, Rasch model is used to determine the validation and the reliability of systemic multiple choices question in chemistry teaching and learning. There were 30 multiple choices question with systemic approach for high school student…
English Pyramids: Using Hierarchical Diagrams for Communication Activities.
ERIC Educational Resources Information Center
Johnson, Tia; Sheetz-Brunetti, Judy
The pyramid, or hierarchical diagram, is used in teaching writing English as a second language (ESL) as a visual representation of the way English speakers and writers organize ideas, for comparison with discourse organization in other cultures. A common problem of ESL students is an inability to organize ideas hierarchically. One class activity…
NASA Astrophysics Data System (ADS)
Yang, Can; Ma, Cheng; Hu, Linxi; He, Guangqiang
2018-06-01
We present a hierarchical modulation coherent communication protocol, which simultaneously achieves classical optical communication and continuous-variable quantum key distribution. Our hierarchical modulation scheme consists of a quadrature phase-shifting keying modulation for classical communication and a four-state discrete modulation for continuous-variable quantum key distribution. The simulation results based on practical parameters show that it is feasible to transmit both quantum information and classical information on a single carrier. We obtained a secure key rate of 10^{-3} bits/pulse to 10^{-1} bits/pulse within 40 kilometers, and in the meantime the maximum bit error rate for classical information is about 10^{-7}. Because continuous-variable quantum key distribution protocol is compatible with standard telecommunication technology, we think our hierarchical modulation scheme can be used to upgrade the digital communication systems to extend system function in the future.
Alpha-synuclein levels in patients with multiple system atrophy: a meta-analysis.
Yang, Fei; Li, Wan-Jun; Huang, Xu-Sheng
2018-05-01
This study evaluates the relationship between multiple system atrophy and α-synuclein levels in the cerebrospinal fluid, plasma and neural tissue. Literature search for relevant research articles was undertaken in electronic databases and study selection was based on a priori eligibility criteria. Random-effects meta-analyses of standardized mean differences in α-synuclein levels between multiple system atrophy patients and normal controls were conducted to obtain the overall and subgroup effect sizes. Meta-regression analyses were performed to evaluate the effect of age, gender and disease severity on standardized mean differences. Data were obtained from 11 studies involving 378 multiple system atrophy patients and 637 healthy controls (age: multiple system atrophy patients 64.14 [95% confidence interval 62.05, 66.23] years; controls 64.16 [60.06, 68.25] years; disease duration: 44.41 [26.44, 62.38] months). Cerebrospinal fluid α-synuclein levels were significantly lower in multiple system atrophy patients than in controls but in plasma and neural tissue, α-synuclein levels were significantly higher in multiple system atrophy patients (standardized mean difference: -0.99 [-1.65, -0.32]; p = 0.001). Percentage of male multiple system atrophy patients was significantly positively associated with the standardized mean differences of cerebrospinal fluid α-synuclein levels (p = 0.029) whereas the percentage of healthy males was not associated with the standardized mean differences of cerebrospinal fluid α-synuclein levels (p = 0.920). In multiple system atrophy patients, α-synuclein levels were significantly lower in the cerebrospinal fluid and were positively associated with the male gender.
Hierarchical Context Modeling for Video Event Recognition.
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.
Hierarchical species distribution models
Hefley, Trevor J.; Hooten, Mevin B.
2016-01-01
Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
Zhao, Haixin; Cui, Shu; Yang, Lan; Li, Guodong; Li, Nan; Li, Xiaotian
2018-02-15
Photocatalysts with a hierarchically porous structure have attracted considerable attention owing to their wide pore size distribution and high surface area, which enhance the efficiency of transporting species to active sites. In this study, hierarchically meso-macroporous TiO 2 photocatalysts decorated with highly dispersed CdS nanoparticles were synthesized via hydrolysis, followed by a hydrothermal treatment. The textural mesopores and interconnected pore framework provided more accessible active sites and efficient mass transport for the photocatalytic process. The light collection efficiency was enhanced because of multiple scattering of incident light in the macropores. Moreover, the formation of a heterojunction between the CdS and TiO 2 nanoparticles extended the photoresponse of TiO 2 to the visible-light range and enhanced the charge separation efficiency. Therefore, the hierarchically meso-macroporous TiO 2 /CdS photocatalysts exhibited excellent photocatalytic activity for the degradation of rhodaming B under visible-light irradiation. Trapping experiments demonstrated that superoxide radicals (O 2 - ) and hydroxyl radicals (OH) were the main active species in photocatalysis. A reasonable photocatalytic mechanism of TiO 2 /CdS heterojunction photocatalysts was also presented. Copyright © 2017 Elsevier Inc. All rights reserved.
Using Hierarchical Folders and Tags for File Management
ERIC Educational Resources Information Center
Ma, Shanshan
2010-01-01
Hierarchical folders have been widely used for managing digital files. A well constructed hierarchical structure can keep files organized. A parent folder can have several subfolders and one subfolder can only reside in one parent folder. Files are stored in folders or subfolders. Files can be found by traversing a given path, going through…
Ren, Yudan; Nguyen, Vinh Thai; Guo, Lei; Guo, Christine Cong
2017-09-07
The brain is constantly monitoring and integrating both cues from the external world and signals generated intrinsically. These extrinsically and intrinsically-driven neural processes are thought to engage anatomically distinct regions, which are thought to constitute the extrinsic and intrinsic systems of the brain. While the specialization of extrinsic and intrinsic system is evident in primary and secondary sensory cortices, a systematic mapping of the whole brain remains elusive. Here, we characterized the extrinsic and intrinsic functional activities in the brain during naturalistic movie-viewing. Using a novel inter-subject functional correlation (ISFC) analysis, we found that the strength of ISFC shifts along the hierarchical organization of the brain. Primary sensory cortices appear to have strong inter-subject functional correlation, consistent with their role in processing exogenous information, while heteromodal regions that attend to endogenous processes have low inter-subject functional correlation. Those brain systems with higher intrinsic tendency show greater inter-individual variability, likely reflecting the aspects of brain connectivity architecture unique to individuals. Our study presents a novel framework for dissecting extrinsically- and intrinsically-driven processes, as well as examining individual differences in brain function during naturalistic stimulation.