Hierarchical video summarization based on context clustering

Science.gov (United States)

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.

Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

DEFF Research Database (Denmark)

Custer, Rocco

protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

Qualitative Content Analysis

OpenAIRE

Philipp Mayring

2000-01-01

The article describes an approach of systematic, rule guided qualitative text analysis, which tries to preserve some methodological strengths of quantitative content analysis and widen them to a concept of qualitative procedure. First the development of content analysis is delineated and the basic principles are explained (units of analysis, step models, working with categories, validity and reliability). Then the central procedures of qualitative content analysis, inductive development of ca...

Emergence of psychotic content in psychotherapy: An exploratory qualitative analysis of content, process, and therapist variables in a single case study.

Science.gov (United States)

Leonhardt, Bethany L; Kukla, Marina; Belanger, Elizabeth; Chaudoin-Patzoldt, Kelly A; Buck, Kelly D; Minor, Kyle S; Vohs, Jenifer L; Hamm, Jay A; Lysaker, Paul H

2018-03-01

Emerging integrative metacognitive therapies for schizophrenia seek to promote subjective aspects of recovery. Beyond symptom remission, they are concerned with shared meaning-making and intersubjective processes. It is unclear, however, how such therapies should understand and respond to psychotic content that threatens meaning-making in therapeutic contexts. Accordingly, we sought to understand what factors precede and potentially trigger psychotic content within psychotherapy and what aids in resolution and return to meaning-making. Forty-eight transcripts from a single psychotherapy case were analyzed with thematic analysis. Passages of delusional or disorganized content were identified and themes present prior to the emergence and resolution of such material were identified and coded. Themes that preceded the emergence of psychotic content varied across early, middle, and late phases of therapy. Material related to the patient's experience of inadequacy and potential vulnerability, therapist setting boundaries within the therapeutic relationship and making challenges appeared to trigger psychotic content, especially early in treatment. Psychotic content may emerge in session following identifiable antecedents which change over phases of therapy. Attending to psychotic content by assuming a non-hierarchical stance and not dismissing psychotic content may aid in maintaining intersubjectivity and support patient's movements toward recovery in integrative metacognitive therapies.

Qualitative Content Analysis

Directory of Open Access Journals (Sweden)

Satu Elo

2014-02-01

Full Text Available Qualitative content analysis is commonly used for analyzing qualitative data. However, few articles have examined the trustworthiness of its use in nursing science studies. The trustworthiness of qualitative content analysis is often presented by using terms such as credibility, dependability, conformability, transferability, and authenticity. This article focuses on trustworthiness based on a review of previous studies, our own experiences, and methodological textbooks. Trustworthiness was described for the main qualitative content analysis phases from data collection to reporting of the results. We concluded that it is important to scrutinize the trustworthiness of every phase of the analysis process, including the preparation, organization, and reporting of results. Together, these phases should give a reader a clear indication of the overall trustworthiness of the study. Based on our findings, we compiled a checklist for researchers attempting to improve the trustworthiness of a content analysis study. The discussion in this article helps to clarify how content analysis should be reported in a valid and understandable manner, which would be of particular benefit to reviewers of scientific articles. Furthermore, we discuss that it is often difficult to evaluate the trustworthiness of qualitative content analysis studies because of defective data collection method description and/or analysis description.

Generic Formal Framework for Compositional Analysis of Hierarchical Scheduling Systems

DEFF Research Database (Denmark)

Boudjadar, Jalil; Hyun Kim, Jin; Thi Xuan Phan, Linh

We present a compositional framework for the specification and analysis of hierarchical scheduling systems (HSS). Firstly we provide a generic formal model, which can be used to describe any type of scheduling system. The concept of Job automata is introduced in order to model job instantiation...

Hierarchical Discriminant Analysis

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Di Lu

2018-01-01

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

Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

Science.gov (United States)

Luo, Wen; Azen, Razia

2013-01-01

Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

A hierarchical cluster analysis of normal-tension glaucoma using spectral-domain optical coherence tomography parameters.

Science.gov (United States)

Bae, Hyoung Won; Ji, Yongwoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2015-01-01

Normal-tension glaucoma (NTG) is a heterogenous disease, and there is still controversy about subclassifications of this disorder. On the basis of spectral-domain optical coherence tomography (SD-OCT), we subdivided NTG with hierarchical cluster analysis using optic nerve head (ONH) parameters and retinal nerve fiber layer (RNFL) thicknesses. A total of 200 eyes of 200 NTG patients between March 2011 and June 2012 underwent SD-OCT scans to measure ONH parameters and RNFL thicknesses. We classified NTG into homogenous subgroups based on these variables using a hierarchical cluster analysis, and compared clusters to evaluate diverse NTG characteristics. Three clusters were found after hierarchical cluster analysis. Cluster 1 (62 eyes) had the thickest RNFL and widest rim area, and showed early glaucoma features. Cluster 2 (60 eyes) was characterized by the largest cup/disc ratio and cup volume, and showed advanced glaucomatous damage. Cluster 3 (78 eyes) had small disc areas in SD-OCT and were comprised of patients with significantly younger age, longer axial length, and greater myopia than the other 2 groups. A hierarchical cluster analysis of SD-OCT scans divided NTG patients into 3 groups based upon ONH parameters and RNFL thicknesses. It is anticipated that the small disc area group comprised of younger and more myopic patients may show unique features unlike the other 2 groups.

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

Science.gov (United States)

Kolekar, M. H.; Sengupta, S.

2005-07-01

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

Improved SIRAP analysis for synchronization in hierarchical scheduled real-time systems

NARCIS (Netherlands)

Behnam, M.; Bril, R.J.; Nolte, T.

2009-01-01

We present our ongoing work on synchronization in hierarchical scheduled real-time systems, where tasks are scheduled using fixed-priority pre-emptive scheduling. In this paper, we show that the original local schedulability analysis of the synchronization protocol SIRAP [4] is very pessimistic when

Determinants of falls in community-dwelling elderly: hierarchical analysis.

Science.gov (United States)

Brito, Thais Alves; Coqueiro, Raildo da Silva; Fernandes, Marcos Henrique; de Jesus, Cleber Souza

2014-01-01

To analyze the fall-related factors in community-dwelling elderly. Epidemiologic cross-sectional population-based household study with hierarchical interrelationships among the potential risk factors. The sample was made up of noninstitutionalized individuals over age 60, who were resident of a city in Brazil's Northeast Region. The dependent variable was fall occurrence in the last 12 months; independent variables were sociodemographic, behavioral, health, and functional status factors. Multivariate hierarchical Poisson regression analysis was used based on a proposed theoretic model. Three hundred and sixteen (89.0%) elderly participated of the survey, average age 74.2 years; the majority was female, with limited literacy and had low-medium family income. The fall prevalence was of 25.8%; occurrence was related to depression symptoms (PR = 1.55) and balance limitation (PR = 1.56). The high fall prevalence among elderly necessitates the identification of fall-related factors for action planning prevention programs with this group. © 2014 Wiley Periodicals, Inc.

Registered nurses views of caring in coronary care--a deductive and inductive content analysis.

Science.gov (United States)

Andersson, Ewa K; Sjöström-Strand, Annica; Willman, Ania; Borglin, Gunilla

2015-12-01

To extend nurses' descriptions of how they understood caring, as reflected in the findings of an earlier study (i.e. the hierarchical outcome space) and to gain additional understandings and perspectives of nurses' views of caring in relation to a coronary care patient case. Scientific literature from the 1970s-1990s contains descriptions of caring in nursing. In contrast, the contemporary literature on this topic--particularly in the context of coronary care--is very sparse, and the few studies that do contain descriptions rarely do so from the perspective of nurses. Qualitative descriptive study. Twenty-one nurses were interviewed using the stimulated recall interview technique. The data were analysed using deductive and inductive qualitative content analysis. The results of the iterative and integrated content analysis showed that the data mainly reproduced the content of the hierarchical outcome space describing how nurses could understand caring; however, in the outcome space, the relationship broke up (i.e. flipped). The nurses' views of caring could now also be understood as: person-centredness 'lurking' in the shadows; limited 'potential' for safeguarding patients' best interests; counselling as virtually the 'only' nursing intervention; and caring preceded by the 'almighty' context. Their views offered alternative and, at times, contrasting perspectives of caring, thereby adding to our understanding of it. Caring was described as operating somewhere between the nurses caring values and the contextual conditions in which caring occurred. This challenged their ability to sustain caring in accordance with their values and the patients' preferences. To ensure that the essentials of caring are met at all times, nurses need to plan and deliver caring in a systematic way. The use of systematic structures in caring, as the nursing process, can help nurses to work in a person-centred way, while sustaining their professional values. © 2015 John Wiley & Sons Ltd.

The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

Science.gov (United States)

Leung, S C; Fung, W K; Wong, K H

1999-01-01

The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

Science.gov (United States)

Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2014-04-29

To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Low temperature oxidative desulfurization with hierarchically mesoporous titaniumsilicate Ti-SBA-2 single crystals.

Science.gov (United States)

Shi, Chengxiang; Wang, Wenxuan; Liu, Ni; Xu, Xueyan; Wang, Danhong; Zhang, Minghui; Sun, Pingchuan; Chen, Tiehong

2015-07-21

Hierarchically porous Ti-SBA-2 with high framework Ti content (up to 5 wt%) was firstly synthesized by employing organic mesomorphous complexes of a cationic surfactant (CTAB) and an anionic polyelectrolyte (PAA) as templates. The material exhibited excellent performance in oxidative desulfurization of diesel fuel at low temperature (40 °C or 25 °C) due to the unique hierarchically porous structure and high framework Ti content.

State Space Analysis of Hierarchical Coloured Petri Nets

DEFF Research Database (Denmark)

Christensen, Søren; Kristensen, Lars Michael

2003-01-01

In this paper, we consider state space analysis of Coloured Petri Nets. It is well-known that almost all dynamic properties of the considered system can be verified when the state space is finite. However, state space analysis is more than just formulating a set of formal requirements and invokin...... supporting computation and storage of state spaces which exploi the hierarchical structure of the models....... in which formal verification, partial state spaces, and analysis by means of graphical feedback and simulation are integrated entities. The focus of the paper is twofold: the support for graphical feedback and the way it has been integrated with simulation, and the underlying algorithms and data-structures......In this paper, we consider state space analysis of Coloured Petri Nets. It is well-known that almost all dynamic properties of the considered system can be verified when the state space is finite. However, state space analysis is more than just formulating a set of formal requirements and invoking...

Qualitative Content Analysis

OpenAIRE

Satu Elo; Maria Kääriäinen; Outi Kanste; Tarja Pölkki; Kati Utriainen; Helvi Kyngäs

2014-01-01

Qualitative content analysis is commonly used for analyzing qualitative data. However, few articles have examined the trustworthiness of its use in nursing science studies. The trustworthiness of qualitative content analysis is often presented by using terms such as credibility, dependability, conformability, transferability, and authenticity. This article focuses on trustworthiness based on a review of previous studie...

Photocatalytic properties of hierarchical ZnO flowers synthesized by a sucrose-assisted hydrothermal method

Energy Technology Data Exchange (ETDEWEB)

Lv Wei [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China); Wei Bo [Center for Condensed Matter Science and Technology, Department of Physics, Harbin Institute of Technology, Harbin 150080 (China); Xu Lingling, E-mail: xulingling_hit@163.com [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China) and Center for Condensed Matter Science and Technology, Department of Physics, Harbin Institute of Technology, Harbin 150080 (China); Zhao Yan, E-mail: zhaoyan516@126.com [Department of Physics, Northeast Forestry University, Harbin 150040 (China); Gao Hong; Liu Jia [Key Laboratory of Photonic and Electric Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China)

2012-10-15

Highlights: Black-Right-Pointing-Pointer Hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. Black-Right-Pointing-Pointer The sucrose added ZnO flowers showed improved activity mainly due to the improved crystallinity. Black-Right-Pointing-Pointer The effect of sucrose content was studied and optimized. - Abstract: In this work, hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. The thermogravimetric analysis/differential thermal analysis (TGA-DTA) and Fourier transform infrared spectra (FTIR) showed that sucrose acted as a complexing agent in the synthesis process and assisted combustion during annealing. Photocatalytic activity was evaluated using the degradation of organic dye methyl orange. The sucrose added ZnO flowers showed improved activity, which was mainly attributed to the better crystallinity as confirmed by X-ray photoelectron spectroscopy (XPS) analysis. The effect of sucrose amount on photocatalytic activity was also studied.

Hierarchical analysis of dependency in metabolic networks.

Science.gov (United States)

Gagneur, Julien; Jackson, David B; Casari, Georg

2003-05-22

Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

Numerical analysis of a neural network with hierarchically organized patterns

International Nuclear Information System (INIS)

Bacci, Silvia; Wiecko, Cristina; Parga, Nestor

1988-01-01

A numerical analysis of the retrieval behaviour of an associative memory model where the memorized patterns are stored hierarchically is performed. It is found that the model is able to categorize errors. For a finite number of categories, these are retrieved correctly even when the stored patterns are not. Instead, when they are allowed to increase with the number of neurons, their retrieval quality deteriorates above a critical category capacity. (Author)

Automatic Hierarchical Color Image Classification

Directory of Open Access Journals (Sweden)

Jing Huang

2003-02-01

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

Hierarchical composites: Analysis of damage evolution based on fiber bundle model

DEFF Research Database (Denmark)

Mishnaevsky, Leon

2011-01-01

A computational model of multiscale composites is developed on the basis of the fiber bundle model with the hierarchical load sharing rule, and employed to study the effect of the microstructures of hierarchical composites on their damage resistance. Two types of hierarchical materials were consi...

Assessment of surface water quality using hierarchical cluster analysis

Directory of Open Access Journals (Sweden)

Dheeraj Kumar Dabgerwal

2016-02-01

Full Text Available This study was carried out to assess the physicochemical quality river Varuna inVaranasi,India. Water samples were collected from 10 sites during January-June 2015. Pearson correlation analysis was used to assess the direction and strength of relationship between physicochemical parameters. Hierarchical Cluster analysis was also performed to determine the sources of pollution in the river Varuna. The result showed quite high value of DO, Nitrate, BOD, COD and Total Alkalinity, above the BIS permissible limit. The results of correlation analysis identified key water parameters as pH, electrical conductivity, total alkalinity and nitrate, which influence the concentration of other water parameters. Cluster analysis identified three major clusters of sampling sites out of total 10 sites, according to the similarity in water quality. This study illustrated the usefulness of correlation and cluster analysis for getting better information about the river water quality.International Journal of Environment Vol. 5 (1 2016,  pp: 32-44

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

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

2017-01-01

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

Leadership styles across hierarchical levels in nursing departments.

Science.gov (United States)

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.

Functional annotation of hierarchical modularity.

Directory of Open Access Journals (Sweden)

Kanchana Padmanabhan

Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

Structure and dynamics of European sports science textual contents: Analysis of ECSS abstracts (1996-2014).

Science.gov (United States)

Hristovski, Robert; Aceski, Aleksandar; Balague, Natalia; Seifert, Ludovic; Tufekcievski, Aleksandar; Cecilia, Aguirre

2017-02-01

The article discusses general structure and dynamics of the sports science research content as obtained from the analysis of 21998 European College of Sport Science abstracts belonging to 12 science topics. The structural analysis showed intertwined multidisciplinary and unifying tendencies structured along horizontal (scope) and vertical (level) axes. Methodological (instrumental and mode of inquiry) integrative tendencies are dominant. Theoretical integrative tendencies are much less detectable along both horizontal and vertical axes. The dynamic analysis of written abstracts text content over the 19 years reveals the contextualizing and guiding role of thematic skeletons of each sports science topic in forming more detailed contingent research ideas and the role of the latter in stabilizing and procreating the former. This circular causality between both hierarchical levels and functioning on separate characteristic time scales is crucial for understanding how stable research traditions self-maintain and self-procreate through innovative contingencies. The structure of sports science continuously rebuilds itself through use and re-use of contingent research ideas. The thematic skeleton ensures its identity and the contingent conceptual sets its flexibility and adaptability to different research or applicative problems.

A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis

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Shaoning Li

2017-01-01

Full Text Available In the fields of geographic information systems (GIS and remote sensing (RS, the clustering algorithm has been widely used for image segmentation, pattern recognition, and cartographic generalization. Although clustering analysis plays a key role in geospatial modelling, traditional clustering methods are limited due to computational complexity, noise resistant ability and robustness. Furthermore, traditional methods are more focused on the adjacent spatial context, which makes it hard for the clustering methods to be applied to multi-density discrete objects. In this paper, a new method, cell-dividing hierarchical clustering (CDHC, is proposed based on convex hull retraction. The main steps are as follows. First, a convex hull structure is constructed to describe the global spatial context of geospatial objects. Then, the retracting structure of each borderline is established in sequence by setting the initial parameter. The objects are split into two clusters (i.e., “sub-clusters” if the retracting structure intersects with the borderlines. Finally, clusters are repeatedly split and the initial parameter is updated until the terminate condition is satisfied. The experimental results show that CDHC separates the multi-density objects from noise sufficiently and also reduces complexity compared to the traditional agglomerative hierarchical clustering algorithm.

Hierarchic Analysis Method to Evaluate Rock Burst Risk

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Ming Ji

2015-01-01

Full Text Available In order to reasonably evaluate the risk of rock bursts in mines, the factors impacting rock bursts and the existing grading criterion on the risk of rock bursts were studied. By building a model of hierarchic analysis method, the natural factors, technology factors, and management factors that influence rock bursts were analyzed and researched, which determined the degree of each factor’s influence (i.e., weight and comprehensive index. Then the grade of rock burst risk was assessed. The results showed that the assessment level generated by the model accurately reflected the actual risk degree of rock bursts in mines. The model improved the maneuverability and practicability of existing evaluation criteria and also enhanced the accuracy and science of rock burst risk assessment.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

Science.gov (United States)

Cressie, Noel; Calder, Catherine A; Clark, James S; Ver Hoef, Jay M; Wikle, Christopher K

2009-04-01

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Hierarchically Porous N-doped Carbon Derived from ZIF-8 Nanocomposites for Electrochemical Applications

International Nuclear Information System (INIS)

Jiang, Min; Cao, Xueping; Zhu, Dandan; Duan, Yongxin; Zhang, Jianming

2016-01-01

A core-shell structure composite, zeolitic imidazolate framework @ cetyltrimethylammonium bromide (ZIF-8@CTAB) was synthesized by CTAB micelle controlling the growth of ZIF-8 in aqueous systems. Direct carbonization of ZIF-8@CTAB at a high temperature produced the nitrogen-doped hierarchically porous carbon (named as PC1000@C). In comparison with the carbonization product of pure ZIF-8 (named as PC1000), PC1000@C possesses the higher specific surface area and two-times larger total pore volume. The results from elemental analysis shows the higher N content in PC1000 sample, while X-ray photoelectron spectroscopy curve-fitting shows the higher quaternary-N content in PC1000@C sample. The hierarchical microporous/mesoporous structure, high surface area and favorable N species in PC1000@C play an active role in catalyzing oxygen reduction reaction (ORR). The specific capacitance of porous carbon was calculated from the galvanostatic-discharge curve. PC1000@C exhibits a large specific capacitance of 225 F g"−"1 at a current density of 0.5 A g"−"1 and still retains 92% of initial capacitance after 1000 galvanostatic charge-discharge cycles.

Quantitative Analysis and Comparison of Four Major Flavonol Glycosides in the Leaves of Toona sinensis (A. Juss.) Roemer (Chinese Toon) from Various Origins by High-Performance Liquid Chromatography-Diode Array Detector and Hierarchical Clustering Analysis

Science.gov (United States)

Sun, Xiaoxiang; Zhang, Liting; Cao, Yaqi; Gu, Qinying; Yang, Huan; Tam, James P.

2016-01-01

Background: Toona sinensis (A. Juss.) Roemer is an endemic species of Toona genus native to Asian area. Its dried leaves are applied in the treatment of many diseases; however, few investigations have been reported for the quantitative analysis and comparison of major bioactive flavonol glycosides in the leaves harvested from various origins. Objective: To quantitatively analyze four major flavonol glycosides including rutinoside, quercetin-3-O-β-D-glucoside, quercetin-3-O-α-L-rhamnoside, and kaempferol-3-O-α-L-rhamnoside in the leaves from different production sites and classify them according to the content of these glycosides. Materials and Methods: A high-performance liquid chromatography-diode array detector (HPLC-DAD) method for their simultaneous determination was developed and validated for linearity, precision, accuracy, stability, and repeatability. Moreover, the method established was then employed to explore the difference in the content of these four glycosides in raw materials. Finally, a hierarchical clustering analysis was performed to classify 11 voucher specimens. Results: The separation was performed on a Waters XBridge Shield RP18 column (150 mm × 4.6 mm, 3.5 μm) kept at 35°C, and acetonitrile and H2O containing 0.30% trifluoroacetic acid as mobile phase was driven at 1.0 mL/min during the analysis. Ten microliters of solution were injected and 254 nm was selected to monitor the separation. A strong linear relationship between the peak area and concentration of four analytes was observed. And, the method was also validated to be repeatable, stable, precise, and accurate. Conclusion: An efficient and reliable HPLC-DAD method was established and applied in the assays for the samples from 11 origins successfully. Moreover, the content of those flavonol glycosides varied much among different batches, and the flavonoids could be considered as biomarkers to control the quality of Chinese Toon. SUMMARY Four major flavonol glycosides in the leaves

Adolescent judgment of sexual content on television: implications for future content analysis research.

Science.gov (United States)

Manganello, Jennifer A; Henderson, Vani R; Jordan, Amy; Trentacoste, Nicole; Martin, Suzanne; Hennessy, Michael; Fishbein, Martin

2010-07-01

Many studies of sexual messages in media utilize content analysis methods. At times, this research assumes that researchers and trained coders using content analysis methods and the intended audience view and interpret media content similarly. This article compares adolescents' perceptions of the presence or absence of sexual content on television to those of researchers using three different coding schemes. Results from this formative research study suggest that participants and researchers are most likely to agree with content categories assessing manifest content, and that differences exist among adolescents who view sexual messages on television. Researchers using content analysis methods to examine sexual content in media and media effects on sexual behavior should consider identifying how audience characteristics may affect interpretation of content and account for audience perspectives in content analysis study protocols when appropriate for study goals.

Category theoretic analysis of hierarchical protein materials and social networks.

Directory of Open Access Journals (Sweden)

David I Spivak

Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

Hierarchical structures of ZnO spherical particles synthesized solvothermally

Science.gov (United States)

Saito, Noriko; Haneda, Hajime

2011-12-01

We review the solvothermal synthesis, using a mixture of ethylene glycol (EG) and water as the solvent, of zinc oxide (ZnO) particles having spherical and flower-like shapes and hierarchical nanostructures. The preparation conditions of the ZnO particles and the microscopic characterization of the morphology are summarized. We found the following three effects of the ratio of EG to water on the formation of hierarchical structures: (i) EG restricts the growth of ZnO microcrystals, (ii) EG promotes the self-assembly of small crystallites into spheroidal particles and (iii) the high water content of EG results in hollow spheres.

Deliberate change without hierarchical influence?

DEFF Research Database (Denmark)

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

2017-01-01

reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

Science.gov (United States)

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Hierarchical control of electron-transfer

DEFF Research Database (Denmark)

Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis

1997-01-01

In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

Simultaneous determination of 19 flavonoids in commercial trollflowers by using high-performance liquid chromatography and classification of samples by hierarchical clustering analysis.

Science.gov (United States)

Song, Zhiling; Hashi, Yuki; Sun, Hongyang; Liang, Yi; Lan, Yuexiang; Wang, Hong; Chen, Shizhong

2013-12-01

The flowers of Trollius species, named Jin Lianhua in Chinese, are widely used traditional Chinese herbs with vital biological activity that has been used for several decades in China to treat upper respiratory infections, pharyngitis, tonsillitis, and bronchitis. We developed a rapid and reliable method for simultaneous quantitative analysis of 19 flavonoids in trollflowers by using high-performance liquid chromatography (HPLC). Chromatography was performed on Inertsil ODS-3 C18 column, with gradient elution methanol-acetonitrile-water with 0.02% (v/v) formic acid. Content determination was used to evaluate the quality of commercial trollflowers from different regions in China, while three Trollius species (Trollius chinensis Bunge, Trollius ledebouri Reichb, Trollius buddae Schipcz) were explicitly distinguished by using hierarchical clustering analysis. The linearity, precision, accuracy, limit of detection, and limit of quantification were validated for the quantification method, which proved sensitive, accurate and reproducible indicating that the proposed approach was applicable for the routine analysis and quality control of trollflowers. © 2013.

Two-dimensional finite element neutron diffusion analysis using hierarchic shape functions

International Nuclear Information System (INIS)

Carpenter, D.C.

1997-01-01

Recent advances have been made in the use of p-type finite element method (FEM) for structural and fluid dynamics problems that hold promise for reactor physics problems. These advances include using hierarchic shape functions, element-by-element iterative solvers and more powerful mapping techniques. Use of the hierarchic shape functions allows greater flexibility and efficiency in implementing energy-dependent flux expansions and incorporating localized refinement of the solution space. The irregular matrices generated by the p-type FEM can be solved efficiently using element-by-element conjugate gradient iterative solvers. These solvers do not require storage of either the global or local stiffness matrices and can be highly vectorized. Mapping techniques based on blending function interpolation allow exact representation of curved boundaries using coarse element grids. These features were implemented in a developmental two-dimensional neutron diffusion program based on the use of hierarchic shape functions (FEM2DH). Several aspects in the effective use of p-type analysis were explored. Two choices of elemental preconditioning were examined--the proper selection of the polynomial shape functions and the proper number of functions to use. Of the five shape function polynomials tested, the integral Legendre functions were the most effective. The serendipity set of functions is preferable over the full tensor product set. Two global preconditioners were also examined--simple diagonal and incomplete Cholesky. The full effectiveness of the finite element methodology was demonstrated on a two-region, two-group cylindrical problem but solved in the x-y coordinate space, using a non-structured element grid. The exact, analytic eigenvalue solution was achieved with FEM2DH using various combinations of element grids and flux expansions

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

Directory of Open Access Journals (Sweden)

Woosang Lim

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

Imaging of lipids in atherosclerotic lesion in aorta from ApoE/LDLR-/- mice by FT-IR spectroscopy and Hierarchical Cluster Analysis.

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P Wrobel, Tomasz; Mateuszuk, Lukasz; Chlopicki, Stefan; Malek, Kamilla; Baranska, Malgorzata

2011-12-21

Spectroscopy-based approaches can provide an insight into the biochemical composition of a tissue sample. In the present work Fourier transform infrared (FT-IR) spectroscopy was used to develop a reliable methodology to study the content of free fatty acids, triglycerides, cholesteryl esters as well as cholesterol in aorta from mice with atherosclerosis (ApoE/LDLR(-/-) mice). In particular, distribution and concentration of palmitic, oleic and linoleic acid derivatives were analyzed. Spectral analysis of pure compounds allowed for clear discrimination between free fatty acids and other similar moieties based on the carbonyl band position (1699-1710 cm(-1) range). In order to distinguish cholesteryl esters from triglycerides a ratio of carbonyl band to signal at 1010 cm(-1) was used. Imaging of lipids in atherosclerotic aortic lesions in ApoE/LDLR(-/-) mice was followed by Hierarchical Cluster Analysis (HCA). The aorta from C57Bl/6J control mice (fed with chow diet) was used for comparison. The measurements were completed with an FT-IR spectrometer equipped with a 128 × 128 FPA detector. In cross-section of aorta from ApoE/LDLR(-/-) mice a region of atherosclerotic plaque was clearly identified by HCA, which was later divided into 2 sub-regions, one characterized by the higher content of cholesterol, while the other by higher contents of cholesteryl esters. HCA of tissues deposited on normal microscopic glass, hence limited to the 2200-3800 cm(-1) spectral range, also identified a region of atherosclerotic plaque. Importantly, this region correlates with the area stained by standard histological staining for atherosclerotic plaque (Oil Red O). In conclusion, the use of FT-IR and HCA may provide a novel tool for qualitative and quantitative analysis of contents and distribution of lipids in atherosclerotic plaque.

Hierarchical clustering using correlation metric and spatial continuity constraint

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Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Hierarchical Traces for Reduced NSM Memory Requirements

Science.gov (United States)

Dahl, Torbjørn S.

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

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

Science.gov (United States)

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

2014-05-01

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

Diagnostics for generalized linear hierarchical models in network meta-analysis.

Science.gov (United States)

Zhao, Hong; Hodges, James S; Carlin, Bradley P

2017-09-01

Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

DEFF Research Database (Denmark)

Pedersen, Thomas Lin

2017-01-01

of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https...

[Preliminarily application of content analysis to qualitative nursing data].

Science.gov (United States)

Liang, Shu-Yuan; Chuang, Yeu-Hui; Wu, Shu-Fang

2012-10-01

Content analysis is a methodology for objectively and systematically studying the content of communication in various formats. Content analysis in nursing research and nursing education is called qualitative content analysis. Qualitative content analysis is frequently applied to nursing research, as it allows researchers to determine categories inductively and deductively. This article examines qualitative content analysis in nursing research from theoretical and practical perspectives. We first describe how content analysis concepts such as unit of analysis, meaning unit, code, category, and theme are used. Next, we describe the basic steps involved in using content analysis, including data preparation, data familiarization, analysis unit identification, creating tentative coding categories, category refinement, and establishing category integrity. Finally, this paper introduces the concept of content analysis rigor, including dependability, confirmability, credibility, and transferability. This article elucidates the content analysis method in order to help professionals conduct systematic research that generates data that are informative and useful in practical application.

Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis.

Science.gov (United States)

Li, Ben; Li, Yunxiao; Qin, Zhaohui S

2017-06-01

Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package "adaptiveHM", which is freely available from https://github.com/benliemory/adaptiveHM.

Hierarchical materials: Background and perspectives

DEFF Research Database (Denmark)

2016-01-01

Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

Science.gov (United States)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

Predictors of Facebook User Engagement With Health-Related Content for Gay, Bisexual, and Other Men Who Have Sex With Men: Content Analysis

Science.gov (United States)

Lachowsky, Nathan; Hawkins, Blake W; Jollimore, Jody; Baharuddin, Fahmy; Hogg, Robert S

2018-01-01

Background Social media is used by community-based organizations (CBOs) to promote the well-being of gay and bisexual men (GBM). However, few studies have quantified which factors facilitate the diffusion of health content tailored for sexual minorities. Objective The aim of this study was to identify post characteristics that can be leveraged to optimize the health promotion efforts of CBOs on Facebook. Methods The Facebook application programming interface was used to collect 5 years’ of posts shared across 10 Facebook pages administered by Vancouver-based CBOs promoting GBM health. Network analysis assessed basic indicators of network structure. Content analyses were conducted using informatics-based approaches. Hierarchical negative binomial regression of post engagement data was used to identify meaningful covariates of engagement. Results In total, 14,071 posts were shared and 21,537 users engaged with these posts. Most users (n=13,315) engaged only once. There was moderate correlation between the number of posts and the number of CBOs users engaged with (r=.53, P<.001). Higher user engagement was positively associated with positive sentiment, sharing multimedia, and posting about pre-exposure prophylaxis, stigma, and mental health. Engagement was negatively associated with asking questions, posting about dating, and sharing posts during or after work (versus before). Conclusions Results highlight the existence of a core group of Facebook users who facilitate diffusion. Factors associated with greater user engagement present CBOs with a number of strategies for improving the diffusion of health content. PMID:29625953

Hierarchical emc analysis approach for power electronics applications

NARCIS (Netherlands)

Zhao, D.; Ferreira, B.; Roc'h, A.; Leferink, Frank Bernardus Johannes

2008-01-01

In this paper, a novel method for EMI (Electromagnetic Interference) level prediction is proposed. The method is based on the hierarchical structure of the generation of EMI. That is, the determination of EMI level can be divided into three levels, namely the functional level, the transient level

Analyzing security protocols in hierarchical networks

DEFF Research Database (Denmark)

Zhang, Ye; Nielson, Hanne Riis

2006-01-01

Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

Hierarchically structured exergetic and exergoeconomic analysis and evaluation of energy conversion processes

International Nuclear Information System (INIS)

Hebecker, Dietrich; Bittrich, Petra; Riedl, Karsten

2005-01-01

Evaluation of the efficiency and economic benefit of energy conversion processes and technologies requires a scientifically based analysis. The hierarchically structured exergetic analysis provides a detailed characterization of complex technical systems. By defining corresponding evaluation coefficients, the exergetic efficiency can be assessed for units within the whole system. Based on this exergetic analysis, a thermoeconomic evaluation method is developed. A cost function is defined for all units, subsystems and the total plant, so that the cost flow in the system can be calculated. Three dimensionless coefficients, the Pauer factor, the loss coefficient and the cost factor, enable pinpointing cost intensive process units, allocating cost in cases of co-production and gaining insight for future design improvements. The methodology is demonstrated by a biomass gasification plant producing electricity, heat and cold

TV content analysis techniques and applications

CERN Document Server

Kompatsiaris, Yiannis

2012-01-01

The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers. Leaving no stone unturned, TV Content Analysis: Techniques and Applications provides a detailed exploration of TV program analysis techniques. Leading researchers and academics from around the world supply scientifically sound treatment of recent developments across the related subject areas--including systems, architectures, algorithms,

Teaching Content Analysis through "Harry Potter"

Science.gov (United States)

Messinger, Adam M.

2012-01-01

Content analysis is a valuable research tool for social scientists that unfortunately can prove challenging to teach to undergraduate students. Published classroom exercises designed to teach content analysis have thus far been predominantly envisioned as lengthy projects for upper-level courses. A brief and engaging exercise may be more…

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

Science.gov (United States)

2012-01-22

Bungartz HJ, Rank E, Niggl A, Romberg R. Extending the p-Version of Finite Elements by an Octree-Based Hierarchy. In: Widlund OB, Keyes DE (eds...generalization to higher dimensions. We test hierarchical refinement of NURBS for some elementary fluid and structural analysis problems in two and three...with straightforward implementation in tree data structures and simple generalization to higher dimensions. We test hierarchical refinement of NURBS

Hierarchical capitalism in Latin America: Comparative analysis with other economies

Directory of Open Access Journals (Sweden)

Edgar J. Saucedo A.

2015-12-01

Full Text Available Purpose – The purpose of this paper is to compare the three largest economies in Latin America (Brazil, Mexico and Argentina with other economies that have another type of capitalism, in that way we can extract some effects of the hierarchical capitalism in Latin America Design/methodology/approach – The data were taken from World Economic Outlook (IMF, The Global Innovation Index (INSEADand the Democracy Index (The Economist. The selected countries are: Argentina, Brazil, Mexico, South Korea, Spain and Croatia. We establish a comparison among countries in the following dimensions: economic growth, innovation and democracy. Findings – The comparison shows that Argentina, Brazil and Mexico have lower level of economic growth, innovation performance and democracy level than South Korea, Spain and Croatia. The variety of capitalism in Latin America (hierarchical has lower performance than others kinds of capitalism in other regions of the world. Research limitations/implications – We have compared Latin American countries with countries from other regions of the world. However, a comparison may include more countries and results could vary. Originality/value – The results tend to support the idea that hierarchical capitalism has poor results in comparison with other varieties of capitalism.

Hierarchical modeling and its numerical implementation for layered thin elastic structures

Energy Technology Data Exchange (ETDEWEB)

Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

2017-05-15

Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

DEFF Research Database (Denmark)

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

2014-01-01

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

Hierarchically structured catalysts for cascade and selective steam reforming/hydrodeoxygenation reactions.

Science.gov (United States)

Sun, Junming; Karim, Ayman M; Li, Xiaohong Shari; Rainbolt, James; Kovarik, Libor; Shin, Yongsoon; Wang, Yong

2015-12-04

We report a hierarchically structured catalyst with steam reforming and hydrodeoxygenation functionalities being deposited in the micropores and macropores, respectively. The catalyst is highly efficient to upgrade the pyrolysis vapors of pine forest product residual, resulting in a dramatically decreased acid content and increased hydrocarbon yield without external H2 supply.

Design and measurement of fully digital ternary content addressable memory using ratioless static random access memory cells and hierarchical-AND matching comparator

Science.gov (United States)

Nishikata, Daisuke; Ali, Mohammad Alimudin Bin Mohd; Hosoda, Kento; Matsumoto, Hiroshi; Nakamura, Kazuyuki

2018-04-01

A 36-bit × 32-entry fully digital ternary content addressable memory (TCAM) using the ratioless static random access memory (RL-SRAM) technology and fully complementary hierarchical-AND matching comparators (HAMCs) was developed. Since its fully complementary and digital operation enables the effect of device variabilities to be avoided, it can operate with a quite low supply voltage. A test chip incorporating a conventional TCAM and a proposed 24-transistor ratioless TCAM (RL-TCAM) cells and HAMCs was developed using a 0.18 µm CMOS process. The minimum operating voltage of 0.25 V of the developed RL-TCAM, which is less than half of that of the conventional TCAM, was measured via the conventional CMOS push–pull output buffers with the level-shifting and flipping technique using optimized pull-up voltage and resistors.

Hierarchical Network Design

DEFF Research Database (Denmark)

Thomadsen, Tommy

2005-01-01

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

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

Science.gov (United States)

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

Hierarchical cellular designs for load-bearing biocomposite beams and plates

International Nuclear Information System (INIS)

Burgueno, Rigoberto; Quagliata, Mario J.; Mohanty, Amar K.; Mehta, Geeta; Drzal, Lawrence T.; Misra, Manjusri

2005-01-01

Scrutiny into the composition of natural, or biological materials convincingly reveals that high material and structural efficiency can be attained, even with moderate-quality constituents, by hierarchical topologies, i.e., successively organized material levels or layers. The present study demonstrates that biologically inspired hierarchical designs can help improve the moderate properties of natural fiber polymer composites or biocomposites and allow them to compete with conventional materials for load-bearing applications. An overview of the mechanics concepts that allow hierarchical designs to achieve higher performance is presented, followed by observation and results from flexural tests on periodic and hierarchical cellular beams and plates made from industrial hemp fibers and unsaturated polyester resin biocomposites. The experimental data is shown to agree well with performance indices predicted by mechanics models. A procedure for the multi-scale integrated material/structural analysis of hierarchical cellular biocomposite components is presented and its advantages and limitations are discussed

Ash content of lignites - radiometric analysis

International Nuclear Information System (INIS)

Leonhardt, J.; Thuemmel, H.W.

1986-01-01

The quality of lignites is governed by the ash content varying in dependence upon the geologic conditions. Setup and function of the radiometric devices being used for ash content analysis in the GDR are briefly described

Analysis of Scattering by Inhomogeneous Dielectric Objects Using Higher-Order Hierarchical MoM

DEFF Research Database (Denmark)

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

2003-01-01

An efficient technique for the analysis of electromagnetic scattering by arbitrary shaped inhomogeneous dielectric objects is presented. The technique is based on a higher-order method of moments (MoM) solution of the volume integral equation. This higher-order MoM solution comprises recently...... that the condition number of the resulting MoM matrix is reduced by several orders of magnitude in comparison to existing higher-order hierarchical basis functions and, consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement...

Predictors of Facebook User Engagement With Health-Related Content for Gay, Bisexual, and Other Men Who Have Sex With Men: Content Analysis.

Science.gov (United States)

Card, Kiffer George; Lachowsky, Nathan; Hawkins, Blake W; Jollimore, Jody; Baharuddin, Fahmy; Hogg, Robert S

2018-04-06

Social media is used by community-based organizations (CBOs) to promote the well-being of gay and bisexual men (GBM). However, few studies have quantified which factors facilitate the diffusion of health content tailored for sexual minorities. The aim of this study was to identify post characteristics that can be leveraged to optimize the health promotion efforts of CBOs on Facebook. The Facebook application programming interface was used to collect 5 years' of posts shared across 10 Facebook pages administered by Vancouver-based CBOs promoting GBM health. Network analysis assessed basic indicators of network structure. Content analyses were conducted using informatics-based approaches. Hierarchical negative binomial regression of post engagement data was used to identify meaningful covariates of engagement. In total, 14,071 posts were shared and 21,537 users engaged with these posts. Most users (n=13,315) engaged only once. There was moderate correlation between the number of posts and the number of CBOs users engaged with (r=.53, Puser engagement was positively associated with positive sentiment, sharing multimedia, and posting about pre-exposure prophylaxis, stigma, and mental health. Engagement was negatively associated with asking questions, posting about dating, and sharing posts during or after work (versus before). Results highlight the existence of a core group of Facebook users who facilitate diffusion. Factors associated with greater user engagement present CBOs with a number of strategies for improving the diffusion of health content. ©Kiffer George Card, Nathan Lachowsky, Blake W Hawkins, Jody Jollimore, Fahmy Baharuddin, Robert S Hogg. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 06.04.2018.

Detecting Hierarchical Structure in Networks

DEFF Research Database (Denmark)

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

2012-01-01

Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

Analysis of individual brain activation maps using hierarchical description and multiscale detection

International Nuclear Information System (INIS)

Poline, J.B.; Mazoyer, B.M.

1994-01-01

The authors propose a new method for the analysis of brain activation images that aims at detecting activated volumes rather than pixels. The method is based on Poisson process modeling, hierarchical description, and multiscale detection (MSD). Its performances have been assessed using both Monte Carlo simulated images and experimental PET brain activation data. As compared to other methods, the MSD approach shows enhanced sensitivity with a controlled overall type I error, and has the ability to provide an estimate of the spatial limits of the detected signals. It is applicable to any kind of difference image for which the spatial autocorrelation function can be approximated by a stationary Gaussian function

Hierarchical State Machines as Modular Horn Clauses

Directory of Open Access Journals (Sweden)

Pierre-Loïc Garoche

2016-07-01

Full Text Available In model based development, embedded systems are modeled using a mix of dataflow formalism, that capture the flow of computation, and hierarchical state machines, that capture the modal behavior of the system. For safety analysis, existing approaches rely on a compilation scheme that transform the original model (dataflow and state machines into a pure dataflow formalism. Such compilation often result in loss of important structural information that capture the modal behaviour of the system. In previous work we have developed a compilation technique from a dataflow formalism into modular Horn clauses. In this paper, we present a novel technique that faithfully compile hierarchical state machines into modular Horn clauses. Our compilation technique preserves the structural and modal behavior of the system, making the safety analysis of such models more tractable.

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

CERN Document Server

Qian, Dianwei

2015-01-01

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

A HIERARCHICAL SET OF MODELS FOR SPECIES RESPONSE ANALYSIS

NARCIS (Netherlands)

HUISMAN, J; OLFF, H; FRESCO, LFM

Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

A hierarchical set of models for species response analysis

NARCIS (Netherlands)

Huisman, J.; Olff, H.; Fresco, L.F.M.

1993-01-01

Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

Thermodynamic analysis on an anisotropically superhydrophobic surface with a hierarchical structure

Energy Technology Data Exchange (ETDEWEB)

Zhao, Jieliang [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China); Su, Zhengliang [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China); Department of Automotive Engineering, Tsinghua University, Beijing 100084 (China); Yan, Shaoze, E-mail: yansz@mail.tsinghua.edu.cn [Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Tsinghua University, Room 3407, Building 9003, 100084 Beijing (China)

2015-12-01

Graphical abstract: - Highlights: • We model the superhydrophobic surface with anisotropic and hierarchical structure. • Anisotropic wetting only shows in noncomposite state (not in composite state). • Transition from noncomposite to composite state on dual-scale structure is hard. • Droplets tend to roll in the particular direction. • Droplets tend to stably remain in one preferred thermodynamic state. - Abstract: Superhydrophobic surfaces, which refer to the surfaces with contact angle higher than 150° and hysteresis less than 10°, have been reported in various studies. However, studies on the superhydrophobicity of anisotropic, hierarchical surfaces are limited and the corresponding thermodynamic mechanisms could not be explained thoroughly. Here we propose a simplified surface model of anisotropic patterned surface with dual scale roughness. Based on the thermodynamic method, we calculate the equilibrium contact angle (ECA) and the contact angle hysteresis (CAH) on the given surface. We show here that the hierarchical structure has much better anisotropic wetting properties than the single-scale one, and the results shed light on the potential application in controllable micro-/nano-fluidic systems. Our studies can be potentially applied for the fabrication of anisotropically superhydrophobic surfaces.

Thermodynamic analysis on an anisotropically superhydrophobic surface with a hierarchical structure

International Nuclear Information System (INIS)

Zhao, Jieliang; Su, Zhengliang; Yan, Shaoze

2015-01-01

Graphical abstract: - Highlights: • We model the superhydrophobic surface with anisotropic and hierarchical structure. • Anisotropic wetting only shows in noncomposite state (not in composite state). • Transition from noncomposite to composite state on dual-scale structure is hard. • Droplets tend to roll in the particular direction. • Droplets tend to stably remain in one preferred thermodynamic state. - Abstract: Superhydrophobic surfaces, which refer to the surfaces with contact angle higher than 150° and hysteresis less than 10°, have been reported in various studies. However, studies on the superhydrophobicity of anisotropic, hierarchical surfaces are limited and the corresponding thermodynamic mechanisms could not be explained thoroughly. Here we propose a simplified surface model of anisotropic patterned surface with dual scale roughness. Based on the thermodynamic method, we calculate the equilibrium contact angle (ECA) and the contact angle hysteresis (CAH) on the given surface. We show here that the hierarchical structure has much better anisotropic wetting properties than the single-scale one, and the results shed light on the potential application in controllable micro-/nano-fluidic systems. Our studies can be potentially applied for the fabrication of anisotropically superhydrophobic surfaces.

Measuring populism: comparing two methods of content analysis

NARCIS (Netherlands)

Rooduijn, M.; Pauwels, T.

2011-01-01

The measurement of populism - particularly over time and space - has received only scarce attention. In this research note two different ways to measure populism are compared: a classical content analysis and a computer-based content analysis. An analysis of political parties in the United Kingdom,

Conceptual hierarchical modeling to describe wetland plant community organization

Science.gov (United States)

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.

Junk Food Marketing on Instagram: Content Analysis.

Science.gov (United States)

Vassallo, Amy Jo; Kelly, Bridget; Zhang, Lelin; Wang, Zhiyong; Young, Sarah; Freeman, Becky

2018-06-05

Omnipresent marketing of processed foods is a key driver of dietary choices and brand loyalty. Market data indicate a shift in food marketing expenditures to digital media, including social media. These platforms have greater potential to influence young people, given their unique peer-to-peer transmission and youths' susceptibility to social pressures. The aim of this study was to investigate the frequency of images and videos posted by the most popular, energy-dense, nutrient-poor food and beverage brands on Instagram and the marketing strategies used in these images, including any healthy choice claims. A content analysis of 15 accounts was conducted, using 12 months of Instagram posts from March 15, 2015, to March 15, 2016. A pre-established hierarchical coding guide was used to identify the primary marketing strategy of each post. Each brand used 6 to 11 different marketing strategies in their Instagram accounts; however, they often adhered to an overall theme such as athleticism or relatable consumers. There was a high level of branding, although not necessarily product information on all accounts, and there were very few health claims. Brands are using social media platforms such as Instagram to market their products to a growing number of consumers, using a high frequency of targeted and curated posts that manipulate consumer emotions rather than present information about their products. Policy action is needed that better reflects the current media environment. Public health bodies also need to engage with emerging media platforms and develop compelling social counter-marketing campaigns. ©Amy Jo Vassallo, Bridget Kelly, Lelin Zhang, Zhiyong Wang, Sarah Young, Becky Freeman. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 05.06.2018.

The analysis of thin walled composite laminated helicopter rotor with hierarchical warping functions and finite element method

Science.gov (United States)

Zhu, Dechao; Deng, Zhongmin; Wang, Xingwei

2001-08-01

In the present paper, a series of hierarchical warping functions is developed to analyze the static and dynamic problems of thin walled composite laminated helicopter rotors composed of several layers with single closed cell. This method is the development and extension of the traditional constrained warping theory of thin walled metallic beams, which had been proved very successful since 1940s. The warping distribution along the perimeter of each layer is expanded into a series of successively corrective warping functions with the traditional warping function caused by free torsion or free bending as the first term, and is assumed to be piecewise linear along the thickness direction of layers. The governing equations are derived based upon the variational principle of minimum potential energy for static analysis and Rayleigh Quotient for free vibration analysis. Then the hierarchical finite element method is introduced to form a numerical algorithm. Both static and natural vibration problems of sample box beams are analyzed with the present method to show the main mechanical behavior of the thin walled composite laminated helicopter rotor.

Hierarchical Cluster Analysis of Semicircular Canal and Otolith Deficits in Bilateral Vestibulopathy

Directory of Open Access Journals (Sweden)

Alexander A. Tarnutzer

2018-04-01

Full Text Available BackgroundGait imbalance and oscillopsia are frequent complaints of bilateral vestibular loss (BLV. Video-head-impulse testing (vHIT of all six semicircular canals (SCCs has demonstrated varying involvement of the different canals. Sparing of anterior-canal function has been linked to aminoglycoside-related vestibulopathy and Menière’s disease. We hypothesized that utricular and saccular impairment [assessed by vestibular-evoked myogenic potentials (VEMPs] may be disease-specific also, possibly facilitating the differential diagnosis.MethodsWe searched our vHIT database (n = 3,271 for patients with bilaterally impaired SCC function who also received ocular VEMPs (oVEMPs and cervical VEMPs (cVEMPs and identified 101 patients. oVEMP/cVEMP latencies above the 95th percentile and peak-to-peak amplitudes below the 5th percentile of normal were considered abnormal. Frequency of impairment of vestibular end organs (horizontal/anterior/posterior SCC, utriculus/sacculus was analyzed with hierarchical cluster analysis and correlated with the underlying etiology.ResultsRates of utricular and saccular loss of function were similar (87.1 vs. 78.2%, p = 0.136, Fisher’s exact test. oVEMP abnormalities were found more frequent in aminoglycoside-related bilateral vestibular loss (BVL compared with Menière’s disease (91.7 vs. 54.6%, p = 0.039. Hierarchical cluster analysis indicated distinct patterns of vestibular end-organ impairment, showing that the results for the same end-organs on both sides are more similar than to other end-organs. Relative sparing of anterior-canal function was reflected in late merging with the other end-organs, emphasizing their distinct state. An anatomically corresponding pattern of SCC/otolith hypofunction was present in 60.4% (oVEMPs vs. horizontal SCCs, 34.7% (oVEMPs vs. anterior SCCs, and 48.5% (cVEMPs vs. posterior SCCs of cases. Average (±1 SD number of damaged sensors was 6.8 ± 2.2 out of 10

A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

Science.gov (United States)

Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

2016-03-01

In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. © The Author 2015

Hierarchical sets: analyzing pangenome structure through scalable set visualizations

Science.gov (United States)

2017-01-01

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

Systematic comparative content analysis of 17 psychosocial work environment questionnaires using a new taxonomy.

Science.gov (United States)

Kop, Jean-Luc; Althaus, Virginie; Formet-Robert, Nadja; Grosjean, Vincent

2016-04-01

Many questionnaires have been developed to measure how psychosocial characteristics are perceived in a work environment. But the content validity of these questionnaires has rarely been questioned due to the absence of a reference taxonomy for characteristics of work environments. To propose an exhaustive taxonomy of work environment characteristics involved in psychosocial risks and to apply this taxonomy to questionnaires on workplace psychosocial factors. The taxonomy was developed by categorizing factors present in the main theoretical models of the field. Questionnaire items most frequently cited in scientific literature were retained for classification. The taxonomy was structured into four hierarchical levels and comprises 53 categories. The 17 questionnaires analyzed included 927 items: 59 from the "physical environment" category, 116 from the "social environment" category, 236 from the "work activity" category, 255 from the "activity management" category, and 174 from the "organizational context" category. There are major content differences among analyzed questionnaires. This study offers a means for selecting a scale on the basis of content.

Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study.

Science.gov (United States)

Vaismoradi, Mojtaba; Turunen, Hannele; Bondas, Terese

2013-09-01

Qualitative content analysis and thematic analysis are two commonly used approaches in data analysis of nursing research, but boundaries between the two have not been clearly specified. In other words, they are being used interchangeably and it seems difficult for the researcher to choose between them. In this respect, this paper describes and discusses the boundaries between qualitative content analysis and thematic analysis and presents implications to improve the consistency between the purpose of related studies and the method of data analyses. This is a discussion paper, comprising an analytical overview and discussion of the definitions, aims, philosophical background, data gathering, and analysis of content analysis and thematic analysis, and addressing their methodological subtleties. It is concluded that in spite of many similarities between the approaches, including cutting across data and searching for patterns and themes, their main difference lies in the opportunity for quantification of data. It means that measuring the frequency of different categories and themes is possible in content analysis with caution as a proxy for significance. © 2013 Wiley Publishing Asia Pty Ltd.

Catalysis with hierarchical zeolites

DEFF Research Database (Denmark)

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

2011-01-01

Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

Parallel hierarchical radiosity rendering

Energy Technology Data Exchange (ETDEWEB)

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

1993-07-01

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

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

Science.gov (United States)

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.

Analysis, Retrieval and Delivery of Multimedia Content

CERN Document Server

Cavallaro, Andrea; Leonardi, Riccardo; Migliorati, Pierangelo

2013-01-01

Covering some of the most cutting-edge research on the delivery and retrieval of interactive multimedia content, this volume of specially chosen contributions provides the most updated perspective on one of the hottest contemporary topics. The material represents extended versions of papers presented at the 11th International Workshop on Image Analysis for Multimedia Interactive Services, a vital international forum on this fast-moving field. Logically organized in discrete sections that approach the subject from its various angles, the content deals in turn with content analysis, motion and activity analysis, high-level descriptors and video retrieval, 3-D and multi-view, and multimedia delivery. The chapters cover the finest detail of emerging techniques such as the use of high-level audio information in improving scene segmentation and the use of subjective logic for forensic visual surveillance. On content delivery, the book examines both images and video, focusing on key subjects including an efficient p...

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

Science.gov (United States)

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

2017-07-01

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

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

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

Directory of Open Access Journals (Sweden)

Hossein Pourghassem

2010-10-01

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

Micromechanics of hierarchical materials

DEFF Research Database (Denmark)

Mishnaevsky, Leon, Jr.

2012-01-01

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

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

Energy Technology Data Exchange (ETDEWEB)

Price, Oliver R., E-mail: oliver.price@unilever.co [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Oliver, Margaret A. [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Walker, Allan [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); Wood, Martin [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom)

2009-05-15

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

International Nuclear Information System (INIS)

Price, Oliver R.; Oliver, Margaret A.; Walker, Allan; Wood, Martin

2009-01-01

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Methodological challenges in qualitative content analysis: A discussion paper.

Science.gov (United States)

Graneheim, Ulla H; Lindgren, Britt-Marie; Lundman, Berit

2017-09-01

This discussion paper is aimed to map content analysis in the qualitative paradigm and explore common methodological challenges. We discuss phenomenological descriptions of manifest content and hermeneutical interpretations of latent content. We demonstrate inductive, deductive, and abductive approaches to qualitative content analysis, and elaborate on the level of abstraction and degree of interpretation used in constructing categories, descriptive themes, and themes of meaning. With increased abstraction and interpretation comes an increased challenge to demonstrate the credibility and authenticity of the analysis. A key issue is to show the logic in how categories and themes are abstracted, interpreted, and connected to the aim and to each other. Qualitative content analysis is an autonomous method and can be used at varying levels of abstraction and interpretation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Networked Content Analysis: The case of climate change

NARCIS (Netherlands)

Niederer, S.M.C.

2016-01-01

Content Analysis has been developed within communication science as a technique to analyze bodies of text for features or (recurring) themes, in order to identify cultural indicators, societal trends and issues. And while Content Analysis has seen a tremendous uptake across scientific disciplines,

Proposing a Hierarchical Utility Package with Reference to Mobile Advertising

OpenAIRE

Shalini N. Tripathi; Masood H. Siddiqui

2011-01-01

Mobile advertising is a powerful tool for direct and interactive marketing. However effective marketing requires examining consumers’ psyche. This study proposes a hierarchical utility package (in the consumers’ perception) with reference to mobile advertising, thus enhancing its acceptance. Confirmatory factor analysis revealed four consolidated utility dimensions (with reference to mobile advertising). Binary logistic regression was used to create a hierarchical utility package with res...

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

Science.gov (United States)

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

How hierarchical is language use?

Science.gov (United States)

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

Analysis of the thematic content of review Nucleus

International Nuclear Information System (INIS)

Guerra Valdes, Ramiro

2007-01-01

A computer programme for performing standardized analysis of research areas and key concepts of nuclear science and technology under development at Cubaenergia is presented. Main components of the information processing system, as well as computational methods and modules for thematic content analysis of INIS Database record files are described. Results of thematic content analysis of review Nucleus from 1986 to 2005 are shown. Furthermore, results of demonstrative study Nucleus, Science, Technology and Society are also shown. The results provide new elements to asses the significance of the thematic content of review Nucleus in the context of innovation in interrelated multidisciplinary research areas

Leading processes of patient care and treatment in hierarchical healthcare organizations in Sweden--process managers' experiences.

Science.gov (United States)

Nilsson, Kerstin; Sandoff, Mette

2015-01-01

The purpose of this study is to gain better understanding of the roles and functions of process managers by describing Swedish process managers' experiences of leading processes involving patient care and treatment when working in a hierarchical health-care organization. This study is based on an explorative design. The data were gathered from interviews with 12 process managers at three Swedish hospitals. These data underwent qualitative and interpretative analysis with a modified editing style. The process managers' experiences of leading processes in a hierarchical health-care organization are described under three themes: having or not having a mandate, exposure to conflict situations and leading process development. The results indicate a need for clarity regarding process manager's responsibility and work content, which need to be communicated to all managers and staff involved in the patient care and treatment process, irrespective of department. There also needs to be an emphasis on realistic expectations and orientation of the goals that are an intrinsic part of the task of being a process manager. Generalizations from the results of the qualitative interview studies are limited, but a deeper understanding of the phenomenon was reached, which, in turn, can be transferred to similar settings. This study contributes qualitative descriptions of leading care and treatment processes in a functional, hierarchical health-care organization from process managers' experiences, a subject that has not been investigated earlier.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Science.gov (United States)

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

How Content Analysis may Complement and Extend the Insights of Discourse Analysis

Directory of Open Access Journals (Sweden)

Tracey Feltham-King

2016-02-01

Full Text Available Although discourse analysis is a well-established qualitative research methodology, little attention has been paid to how discourse analysis may be enhanced through careful supplementation with the quantification allowed in content analysis. In this article, we report on a research study that involved the use of both Foucauldian discourse analysis (FDA and directed content analysis based on social constructionist theory and our qualitative research findings. The research focused on the discourses deployed, and the ways in which women were discursively positioned, in relation to abortion in 300 newspaper articles, published in 25 national and regional South African newspapers over 28 years, from 1978 to 2005. While the FDA was able to illuminate the constitutive network of power relations constructing women as subjects of a particular kind, questions emerged that were beyond the scope of the FDA. These questions concerned understanding the relative weightings of various discourses and tracing historical changes in the deployment of these discourses. In this article, we show how the decision to combine FDA and content analysis affected our sampling methodology. Using specific examples, we illustrate the contribution of the FDA to the study. Then, we indicate how subject positioning formed the link between the FDA and the content analysis. Drawing on the same examples, we demonstrate how the content analysis supplemented the FDA through tracking changes over time and providing empirical evidence of the extent to which subject positionings were deployed.

Hierarchical architecture of active knits

International Nuclear Information System (INIS)

Abel, Julianna; Luntz, Jonathan; Brei, Diann

2013-01-01

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

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius

2017-07-03

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

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

2017-01-01

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

Analysis of Error Propagation Within Hierarchical Air Combat Models

Science.gov (United States)

2016-06-01

values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air...values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air engagement... PROPAGATION WITHIN HIERARCHICAL AIR COMBAT MODELS by Salih Ilaslan June 2016 Thesis Advisor: Thomas W. Lucas Second Reader: Jeffrey

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

Science.gov (United States)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

Phytochemical, Proximate and Metal Content Analysis of the Leaves ...

African Journals Online (AJOL)

Methods: The phytochemical analysis of Psidium guajava was carried out by using a standard procedure. Ash, fat, protein, carbohydrate and fibre contents were determined using proximate analysis while the metal contents were determined using Pearson's method. Results: The phytochemical analysis revealed the ...

Novel nitrogen-doped hierarchically porous coralloid carbon materials as host matrixes for lithium–sulfur batteries

International Nuclear Information System (INIS)

Yang, Jing; Wang, Shuyuan; Ma, Zhipeng; Du, Zhiling; Li, Chunying; Song, Jianjun; Wang, Guiling; Shao, Guangjie

2015-01-01

Highlights: • Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites were prepared • Nitrogen atoms were introduced to improve electrochemical properties • The intriguing structural features benefited discharge capacity and cycling stability - Abstract: Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites (N-HPCC/S) served as attractive cathode materials for lithium–sulfur (Li–S) batteries were fabricated for the first time. The nitrogen-doped hierarchically porous coralloid carbon (N-HPCC) with an appropriate nitrogen content (1.29 wt%) was synthesized via a facile hydrothermal approach, combined with subsequent carbonization–activation. The N-HPCC/S composites prepared by a simple melt–diffusion method displayed an excellent electrochemical performance. With a high sulfur content (58 wt%) in the total electrode weight, the N-HPCC/S cathode delivered a high initial discharge capacity of 1626.8 mA h g −1 and remained high up to 1086.3 mA h g −1 after 50 cycles at 100 mA g −1 , which is about 1.86 times as that of activated carbon. Particularly, the reversible discharge capacity still maintained 607.2 mA h g −1 after 200 cycles even at a higher rate of 800 mA g −1 . The enhanced electrochemical performance was attributed to the synergetic effect between the intriguing hierarchically porous coralloid structure and appropriate nitrogen doping, which could effectively trap polysulfides, alleviate the volume expansion, enhance the electronic conductivity and improve the surface interaction between the carbon matrix and polysulfides

A hierarchical SVG image abstraction layer for medical imaging

Science.gov (United States)

Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

2010-03-01

As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

Geographical Characterization of Tunisian Olive Tree Leaves (cv. Chemlali) Using HPLC-ESI-TOF and IT/MS Fingerprinting with Hierarchical Cluster Analysis

Science.gov (United States)

Arráez Román, David; Gómez Caravaca, Ana María; Zarrouk, Mokhtar

2018-01-01

The olive plant has been extensively studied for its nutritional value, whereas its leaves have been specifically recognized as a processing by-product. Leaves are considered by-products of olive farming, representing a significant material arriving to the olive mill. They have been considered for centuries as an important herbal remedy in Mediterranean countries. Their beneficial properties are generally attributed to the presence of a range of phytochemicals such as secoiridoids, triterpenes, lignans, and flavonoids. With the aim to study the impact of geographical location on the phenolic compounds, Olea europaea leaves were handpicked from the Tunisian cultivar “Chemlali” from nine regions in the north, center, and south of Tunisia. The ground leaves were then extracted with methanol : water 80% (v/v) and analyzed by using high-performance liquid chromatography coupled to electrospray time of flight and ion trap mass spectrometry analyzers. A total of 38 compounds could be identified. Their contents showed significant variation among samples from different regions. Hierarchical cluster analysis was applied to highlight similarities in the phytochemical composition observed between the samples of different regions. PMID:29725553

Hierarchical adaptive experimental design for Gaussian process emulators

International Nuclear Information System (INIS)

Busby, Daniel

2009-01-01

Large computer simulators have usually complex and nonlinear input output functions. This complicated input output relation can be analyzed by global sensitivity analysis; however, this usually requires massive Monte Carlo simulations. To effectively reduce the number of simulations, statistical techniques such as Gaussian process emulators can be adopted. The accuracy and reliability of these emulators strongly depend on the experimental design where suitable evaluation points are selected. In this paper a new sequential design strategy called hierarchical adaptive design is proposed to obtain an accurate emulator using the least possible number of simulations. The hierarchical design proposed in this paper is tested on various standard analytic functions and on a challenging reservoir forecasting application. Comparisons with standard one-stage designs such as maximin latin hypercube designs show that the hierarchical adaptive design produces a more accurate emulator with the same number of computer experiments. Moreover a stopping criterion is proposed that enables to perform the number of simulations necessary to obtain required approximation accuracy.

Hierarchical zeolites from class F coal fly ash

Science.gov (United States)

Chitta, Pallavi

Fly ash, a coal combustion byproduct is classified as types class C and class F. Class C fly ash is traditionally recycled for concrete applications and Class F fly ash often disposed in landfills. Class F poses an environmental hazard due to disposal and leaching of heavy metals into ground water and is important to be recycled in order to mitigate the environmental challenges. A major recycling option is to reuse the fly ash as a low-cost raw material for the production of crystalline zeolites, which serve as catalysts, detergents and adsorbents in the chemical industry. Most of the prior literature of fly ash conversion to zeolites does not focus on creating high zeolite surface area zeolites specifically with hierarchical pore structure, which are very important properties in developing a heterogeneous catalyst for catalysis applications. This research work aids in the development of an economical process for the synthesis of high surface area hierarchical zeolites from class F coal fly ash. In this work, synthesis of zeolites from fly ash using classic hydrothermal treatment approach and fusion pretreatment approach were examined. The fusion pretreatment method led to higher extent of dissolution of silica from quartz and mullite phases, which in turn led to higher surface area and pore size of the zeolite. A qualitative kinetic model developed here attributes the difference in silica content to Si/Al ratio of the beginning fraction of fly ash. At near ambient crystallization temperatures and longer crystallization times, the zeolite formed is a hierarchical faujasite with high surface area of at least 360 m2/g. This work enables the large scale recycling of class F coal fly ash to produce zeolites and mitigate environmental concerns. Design of experiments was used to predict surface area and pore sizes of zeolites - thus obviating the need for intense experimentation. The hierarchical zeolite catalyst supports tested for CO2 conversion, yielded hydrocarbons

Facile synthesis of Zn doped CuO hierarchical nanostructures: Structural, optical and antibacterial properties

Directory of Open Access Journals (Sweden)

Javed Iqbal

2015-12-01

Full Text Available ZnxCu1−xO (where x= 0, 0.01, 0.03, 0.05, 0.07 and 0.1 mol% hierarchical nanostructures have been prepared via soft chemical route. X-ray diffraction (XRD results of the synthesized samples reveal the monoclinic structure of CuO without any impurity related phases. The micro-structural parameters such as crystallite size and microstrain have been strongly influenced by Zn doping. Scanning electron microscope (SEM analyses depict the formation of hierarchical nanostructures having average particle size in the range of 26-43 nm. The surface area of CuO nanostructures has been reduced systematically with the increase in Zn content which is linked with the variations in particle size. An obvious decrease in the optical band gap energy of the synthesized CuO hierarchical nanostructures has been observed with Zn doping which is assigned to the formation of shallow levels in the band gap of CuO and combined transition from oxygen 2p states to d sates of Cu and Zn ions. The bactericidal potency of the CuO hierarchical nanostructures have been found to be enhanced remarkably with Zn doping.

Facile synthesis of Zn doped CuO hierarchical nanostructures: Structural, optical and antibacterial properties

Energy Technology Data Exchange (ETDEWEB)

Iqbal, Javed, E-mail: tariqjan84@gmail.com, E-mail: javed.suggau@iiu.edu.pk; Jan, Tariq, E-mail: tariqjan84@gmail.com, E-mail: javed.suggau@iiu.edu.pk; Ul-Hassan, Sibt; Umair Ali, M.; Abbas, Fazal [Laboratory of Nanoscience and Technology, Department of Physics, International Islamic University, H-10, Islamabad (Pakistan); Ahmed, Ishaq [Experimental Physics Labs, National Center for Physics, Islamabad (Pakistan); Mansoor, Qaisar; Ismail, Muhammad [Institute of Biomedical and Genetic Engineering (IBGE), Islamabad (Pakistan)

2015-12-15

Zn{sub x}Cu{sub 1−x}O (where x= 0, 0.01, 0.03, 0.05, 0.07 and 0.1 mol%) hierarchical nanostructures have been prepared via soft chemical route. X-ray diffraction (XRD) results of the synthesized samples reveal the monoclinic structure of CuO without any impurity related phases. The micro-structural parameters such as crystallite size and microstrain have been strongly influenced by Zn doping. Scanning electron microscope (SEM) analyses depict the formation of hierarchical nanostructures having average particle size in the range of 26-43 nm. The surface area of CuO nanostructures has been reduced systematically with the increase in Zn content which is linked with the variations in particle size. An obvious decrease in the optical band gap energy of the synthesized CuO hierarchical nanostructures has been observed with Zn doping which is assigned to the formation of shallow levels in the band gap of CuO and combined transition from oxygen 2p states to d sates of Cu and Zn ions. The bactericidal potency of the CuO hierarchical nanostructures have been found to be enhanced remarkably with Zn doping.

Renormalization group analysis of a simple hierarchical fermion model

International Nuclear Information System (INIS)

Dorlas, T.C.

1991-01-01

A simple hierarchical fermion model is constructed which gives rise to an exact renormalization transformation in a 2-dimensional parameter space. The behaviour of this transformation is studied. It has two hyperbolic fixed points for which the existence of a global critical line is proven. The asymptotic behaviour of the transformation is used to prove the existence of the thermodynamic limit in a certain domain in parameter space. Also the existence of a continuum limit for these theories is investigated using information about the asymptotic renormalization behaviour. It turns out that the 'trivial' fixed point gives rise to a two-parameter family of continuum limits corresponding to that part of parameter space where the renormalization trajectories originate at this fixed point. Although the model is not very realistic it serves as a simple example of the appliclation of the renormalization group to proving the existence of the thermodynamic limit and the continuum limit of lattice models. Moreover, it illustrates possible complications that can arise in global renormalization group behaviour, and that might also be present in other models where no global analysis of the renormalization transformation has yet been achieved. (orig.)

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

Science.gov (United States)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

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

Science.gov (United States)

Nitta, Tohru

2017-10-01

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

TYPE Ia SUPERNOVA LIGHT-CURVE INFERENCE: HIERARCHICAL BAYESIAN ANALYSIS IN THE NEAR-INFRARED

International Nuclear Information System (INIS)

Mandel, Kaisey S.; Friedman, Andrew S.; Kirshner, Robert P.; Wood-Vasey, W. Michael

2009-01-01

We present a comprehensive statistical analysis of the properties of Type Ia supernova (SN Ia) light curves in the near-infrared using recent data from Peters Automated InfraRed Imaging TELescope and the literature. We construct a hierarchical Bayesian framework, incorporating several uncertainties including photometric error, peculiar velocities, dust extinction, and intrinsic variations, for principled and coherent statistical inference. SN Ia light-curve inferences are drawn from the global posterior probability of parameters describing both individual supernovae and the population conditioned on the entire SN Ia NIR data set. The logical structure of the hierarchical model is represented by a directed acyclic graph. Fully Bayesian analysis of the model and data is enabled by an efficient Markov Chain Monte Carlo algorithm exploiting the conditional probabilistic structure using Gibbs sampling. We apply this framework to the JHK s SN Ia light-curve data. A new light-curve model captures the observed J-band light-curve shape variations. The marginal intrinsic variances in peak absolute magnitudes are σ(M J ) = 0.17 ± 0.03, σ(M H ) = 0.11 ± 0.03, and σ(M Ks ) = 0.19 ± 0.04. We describe the first quantitative evidence for correlations between the NIR absolute magnitudes and J-band light-curve shapes, and demonstrate their utility for distance estimation. The average residual in the Hubble diagram for the training set SNe at cz > 2000kms -1 is 0.10 mag. The new application of bootstrap cross-validation to SN Ia light-curve inference tests the sensitivity of the statistical model fit to the finite sample and estimates the prediction error at 0.15 mag. These results demonstrate that SN Ia NIR light curves are as effective as corrected optical light curves, and, because they are less vulnerable to dust absorption, they have great potential as precise and accurate cosmological distance indicators.

An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

Science.gov (United States)

Atas, Dogu; Karadag, Özge

2017-01-01

In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

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

Science.gov (United States)

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.

COMPOSITE METHOD OF RELIABILITY RESEARCH FOR HIERARCHICAL MULTILAYER ROUTING SYSTEMS

Directory of Open Access Journals (Sweden)

R. B. Tregubov

2016-09-01

Full Text Available The paper deals with the idea of a research method for hierarchical multilayer routing systems. The method represents a composition of methods of graph theories, reliability, probabilities, etc. These methods are applied to the solution of different private analysis and optimization tasks and are systemically connected and coordinated with each other through uniform set-theoretic representation of the object of research. The hierarchical multilayer routing systems are considered as infrastructure facilities (gas and oil pipelines, automobile and railway networks, systems of power supply and communication with distribution of material resources, energy or information with the use of hierarchically nested functions of routing. For descriptive reasons theoretical constructions are considered on the example of task solution of probability determination for up state of specific infocommunication system. The author showed the possibility of constructive combination of graph representation of structure of the object of research and a logic probable analysis method of its reliability indices through uniform set-theoretic representation of its elements and processes proceeding in them.

Video content analysis of surgical procedures.

Science.gov (United States)

Loukas, Constantinos

2018-02-01

In addition to its therapeutic benefits, minimally invasive surgery offers the potential for video recording of the operation. The videos may be archived and used later for reasons such as cognitive training, skills assessment, and workflow analysis. Methods from the major field of video content analysis and representation are increasingly applied in the surgical domain. In this paper, we review recent developments and analyze future directions in the field of content-based video analysis of surgical operations. The review was obtained from PubMed and Google Scholar search on combinations of the following keywords: 'surgery', 'video', 'phase', 'task', 'skills', 'event', 'shot', 'analysis', 'retrieval', 'detection', 'classification', and 'recognition'. The collected articles were categorized and reviewed based on the technical goal sought, type of surgery performed, and structure of the operation. A total of 81 articles were included. The publication activity is constantly increasing; more than 50% of these articles were published in the last 3 years. Significant research has been performed for video task detection and retrieval in eye surgery. In endoscopic surgery, the research activity is more diverse: gesture/task classification, skills assessment, tool type recognition, shot/event detection and retrieval. Recent works employ deep neural networks for phase and tool recognition as well as shot detection. Content-based video analysis of surgical operations is a rapidly expanding field. Several future prospects for research exist including, inter alia, shot boundary detection, keyframe extraction, video summarization, pattern discovery, and video annotation. The development of publicly available benchmark datasets to evaluate and compare task-specific algorithms is essential.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

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I. Crawford

2015-11-01

Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

ESPRIT-Tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time.

Science.gov (United States)

Cai, Yunpeng; Sun, Yijun

2011-08-01

Taxonomy-independent analysis plays an essential role in microbial community analysis. Hierarchical clustering is one of the most widely employed approaches to finding operational taxonomic units, the basis for many downstream analyses. Most existing algorithms have quadratic space and computational complexities, and thus can be used only for small or medium-scale problems. We propose a new online learning-based algorithm that simultaneously addresses the space and computational issues of prior work. The basic idea is to partition a sequence space into a set of subspaces using a partition tree constructed using a pseudometric, then recursively refine a clustering structure in these subspaces. The technique relies on new methods for fast closest-pair searching and efficient dynamic insertion and deletion of tree nodes. To avoid exhaustive computation of pairwise distances between clusters, we represent each cluster of sequences as a probabilistic sequence, and define a set of operations to align these probabilistic sequences and compute genetic distances between them. We present analyses of space and computational complexity, and demonstrate the effectiveness of our new algorithm using a human gut microbiota data set with over one million sequences. The new algorithm exhibits a quasilinear time and space complexity comparable to greedy heuristic clustering algorithms, while achieving a similar accuracy to the standard hierarchical clustering algorithm.

Heavy Sexual Content Versus Safer Sex Content: A Content Analysis of the Entertainment Education Drama Shuga.

Science.gov (United States)

Booker, Nancy Achieng'; Miller, Ann Neville; Ngure, Peter

2016-12-01

Extremely popular with Kenyan youth, the entertainment-education drama Shuga was designed with specific goals of promoting condom use, single versus multiple sexual partners, and destigmatization of HIV. Almost as soon as it aired, however, it generated controversy due to its extensive sexual themes and relatively explicit portrayal of sexual issues. To determine how safer sex, antistigma messages, and overall sexual content were integrated into Shuga, we conducted a content analysis. Results indicated that condom use and HIV destigmatization messages were frequently and clearly communicated. Negative consequences for risky sexual behavior were communicated over the course of the entire series. Messages about multiple concurrent partnerships were not evident. In addition, in terms of scenes per hour of programming, Shuga had 10.3 times the amount of sexual content overall, 8.2 times the amount of sexual talk, 17.8 times the amount of sexual behavior, and 9.4 times the amount of sexual intercourse as found in previous analysis of U.S. entertainment programming. Research is needed to determine how these factors may interact to influence adolescent viewers of entertainment education dramas.

Band-gap analysis of a novel lattice with a hierarchical periodicity using the spectral element method

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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.

A Hierarchical Approach to Persistent Scatterer Network Construction and Deformation Time Series Estimation

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Rui Zhang

2014-12-01

Full Text Available This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data.

Neutrosophic Hierarchical Clustering Algoritms

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Rıdvan Şahin

2014-03-01

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

The Hierarchical Perspective

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Daniel Sofron

2015-05-01

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

Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

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Bin Ahmad Fawzan Mohammed Ridha

2018-01-01

Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

Hierarchical porous ZnO microflowers with ultra-high ethanol gas-sensing at low concentration

Science.gov (United States)

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).

Manganese contents of soils as determined by activation analysis

International Nuclear Information System (INIS)

El-Kholi, A.F.; Hamdy, A.A.; Al Metwally, A.I.; El-Damaty, A.H.

1976-01-01

The object of this investigation is to determine total manganese by means of neutron activation analysis and evaluate this technique in comparison with the corresponding data obtained by conventional chemical analysis. Data obtained revealed that the values of total manganese in calcareous soils obtained by both chemical analysis and that by neutron activation analysis were similar. Therefore, activation analysis could be recommended as a quick laboratory, less tedious, and time consuming method for the determination of Mn content in both soils and plants than the conventional chemical techniques due to its great specificity, sensitivity and simplicity. Statistical analysis showed that there is a significant correlation at 5% probability level between manganese content in Soybean plant and total manganese determined by activation and chemical analysis giving the evidence that in the case of those highly calcareous soils of low total manganese content this fraction has to be considered as far as available soil manganese is concerned

Adaptive hierarchical multi-agent organizations

NARCIS (Netherlands)

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

2010-01-01

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

Hierarchical Organization of Auditory and Motor Representations in Speech Perception: Evidence from Searchlight Similarity Analysis.

Science.gov (United States)

Evans, Samuel; Davis, Matthew H

2015-12-01

How humans extract the identity of speech sounds from highly variable acoustic signals remains unclear. Here, we use searchlight representational similarity analysis (RSA) to localize and characterize neural representations of syllables at different levels of the hierarchically organized temporo-frontal pathways for speech perception. We asked participants to listen to spoken syllables that differed considerably in their surface acoustic form by changing speaker and degrading surface acoustics using noise-vocoding and sine wave synthesis while we recorded neural responses with functional magnetic resonance imaging. We found evidence for a graded hierarchy of abstraction across the brain. At the peak of the hierarchy, neural representations in somatomotor cortex encoded syllable identity but not surface acoustic form, at the base of the hierarchy, primary auditory cortex showed the reverse. In contrast, bilateral temporal cortex exhibited an intermediate response, encoding both syllable identity and the surface acoustic form of speech. Regions of somatomotor cortex associated with encoding syllable identity in perception were also engaged when producing the same syllables in a separate session. These findings are consistent with a hierarchical account of how variable acoustic signals are transformed into abstract representations of the identity of speech sounds. © The Author 2015. Published by Oxford University Press.

Synthesis and Characterization of Wooden Magnetic Activated Carbon Fibers with Hierarchical Pore Structures

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Dongna Li

2018-04-01

Full Text Available Wooden magnetic activated carbon fibers (WMACFs with hierarchical pore structures were obtained by adding magnetic iron oxide (Fe3O4 nanoparticles into the liquefied wood. The structures and properties of WMACFs were analyzed by scanning electronmicroscopy (SEM, X-ray diffraction (XRD, Fourier transform infrared spectroscopy (FTIR, N2 adsorption, and vibrating sample magnetometer (VSM. The results showed that WMACFs had high Brunauer-Emmett-Teller (BET surface area (1578 m2/g and total pore volume (0.929 cm3/g, of which 45% was the contribution of small mesopores of 2–3 nm. It is believed that Fe3O4 nanoparticles play an important role in the formation of hierarchical pores. With the Fe3O4 content increasing, the yield rate of WMACFs decreased, and the Fe3O4 crystal plane diffraction peaks and characteristic adsorption peaks were obviously observed. At the same time, it was also found that WMACFs had favorable magnetic properties when the Fe3O4 content was above 1.5%. As a result, WMACFs could be a promising candidate for high efficiency, low cost, and convenient separation for the magnetic field.

Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

Science.gov (United States)

Rupa, Chandra; Mujumdar, Pradeep

2016-04-01

In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings

Communication Base Station Log Analysis Based on Hierarchical Clustering

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Zhang Shao-Hua

2017-01-01

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

Competitiveness of personality as a psychological phenomenon: The content of the construct and its typology

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Klyueva, Olga A.

2016-06-01

Full Text Available Human activity (professional and production-related occurs within the context of explicit or implicit competition and proves to be more or less productive and creative. Operationalization and measurement of the competitiveness of personality without due regard for personal and situational interactions reduces the content of the notion. Competitiveness requires a high degree of personal energy, flexibility, intelligence, and creativity in regulating activity. However, enlarging the domain of psychological studies has necessitated the study of personality in the context of the natural social situations in which it functions. This structural and functional analysis allows expansion of the description of the phenomenology of the competitiveness of personality as well as classification of the strategies of competitive behavior. In this study competitive-behavior strategies (1,064 critical incidents in professional activities were analyzed using the Critical Incident Technique and thematic content analysis. To classify the data set, I used two-step cluster analysis as an exploratory method and analyzed the cross-tables of several categorical variables using the log-linear method of model selection. I applied the Solution Tree method for categorical variables to build a dependent-variable hierarchical model with the relevant predictor values. Through analysis of the results of the cluster analysis, the hierarchical model, and the functional and situational analysis of the context, it is possible to single out and validate three types of competitiveness strategies: the dependent, irrational, destructive, short-term strategy (quasi-competitiveness; the dependent, rational, constructive, short-term strategy; and the free, rational, constructive, long-term strategy. Study of the nature of competition and a subject’s competitive-behavior strategies is required to analyze, predict, and correct destructive strategies for enhancing performance.

Road network safety evaluation using Bayesian hierarchical joint model.

Science.gov (United States)

Wang, Jie; Huang, Helai

2016-05-01

Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Preliminary results from the hierarchical glitch pipeline

International Nuclear Information System (INIS)

Mukherjee, Soma

2007-01-01

This paper reports on the preliminary results obtained from the hierarchical glitch classification pipeline on LIGO data. The pipeline that has been under construction for the past year is now complete and end-to-end tested. It is ready to generate analysis results on a daily basis. The details of the pipeline, the classification algorithms employed and the results obtained with one days analysis on the gravitational wave and several auxiliary and environmental channels from all three LIGO detectors are discussed

The CODESRIA Bulletin: A Content Analysis

African Journals Online (AJOL)

Prof

the major question that guides this essay is the following: What do articles in the. CODESRIA ... A qualitative and quantitative analysis of the contents of the articles can ..... and elections, child and youth, race, gender, and academic freedom.

Searching for continuous gravitational wave signals. The hierarchical Hough transform algorithm

International Nuclear Information System (INIS)

Papa, M.; Schutz, B.F.; Sintes, A.M.

2001-01-01

It is well known that matched filtering techniques cannot be applied for searching extensive parameter space volumes for continuous gravitational wave signals. This is the reason why alternative strategies are being pursued. Hierarchical strategies are best at investigating a large parameter space when there exist computational power constraints. Algorithms of this kind are being implemented by all the groups that are developing software for analyzing the data of the gravitational wave detectors that will come online in the next years. In this talk I will report about the hierarchical Hough transform method that the GEO 600 data analysis team at the Albert Einstein Institute is developing. The three step hierarchical algorithm has been described elsewhere [8]. In this talk I will focus on some of the implementational aspects we are currently concerned with. (author)

Understanding to Hierarchical Microstructures of Crab (Chinese hairy) Shell as a Natural Architecture

Energy Technology Data Exchange (ETDEWEB)

Chuanqiang, Zhou [Testing Center, Yangzhou University, No. 48 Wenhui East Road, Yangzhou (China); Xiangxiang, Gong [Testing Center, Yangzhou University, No. 48 Wenhui East Road, Yangzhou (China); School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou (China); Jie, Han [School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou (China)

2016-03-07

This work was done to better understand the microstructures, composition and mechanical properties of Chinese hairy crab shell. For fully revealing its hierarchical microstructure, the crab shell was observed with electron microscope under different magnifications from different facets. XRD, EDS, FTIR and TGA techniques have been used to characterize the untreated and chemically-treated crab shells, which provided enough information to determine the species and relative content of components in this biomaterial. Combined the microstructures with constituents analysis, the structural principles of crab shell was detailedly realized from different structural levels beyond former reports. To explore the relationship between structure and function, the mechanical properties of shell have been measured through performing tensile tests. The contributions of organics and minerals in shell to the mechanical properties were also discussed by measuring the tensile strength of de-calcification samples treated with HCl solution.

Understanding to Hierarchical Microstructures of Crab (Chinese hairy) Shell as a Natural Architecture

International Nuclear Information System (INIS)

Chuanqiang, Zhou; Xiangxiang, Gong; Jie, Han

2016-01-01

This work was done to better understand the microstructures, composition and mechanical properties of Chinese hairy crab shell. For fully revealing its hierarchical microstructure, the crab shell was observed with electron microscope under different magnifications from different facets. XRD, EDS, FTIR and TGA techniques have been used to characterize the untreated and chemically-treated crab shells, which provided enough information to determine the species and relative content of components in this biomaterial. Combined the microstructures with constituents analysis, the structural principles of crab shell was detailedly realized from different structural levels beyond former reports. To explore the relationship between structure and function, the mechanical properties of shell have been measured through performing tensile tests. The contributions of organics and minerals in shell to the mechanical properties were also discussed by measuring the tensile strength of de-calcification samples treated with HCl solution

On the hierarchical lattices approximation of Bravais lattices: Specific heat and correlation length

International Nuclear Information System (INIS)

Tsallis, C.

1984-01-01

Certain types of real-space renormalization groups (which essentially approximate Bravais lattices through hierarchical ones) do not preserve standard thermodynamic convexity properties. It is pointed out that this serious defect is not intrinsic to any real-space renormalization. It can be avoided if form-invariance (under uniform translation of the energy scale) of the equation connecting the Bravais lattice (which is intended to study) to the hierarchical one (which approximates it) is demanded. In addition to that expressions for the critical exponentes ν and α corresponding to hierarchical lattices are analysed; these are consistent with Melrose recent analysis of the fractal intrinsic dimensionality. (Author) [pt

Evaluating Hierarchical Structure in Music Annotations.

Science.gov (United States)

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

2017-01-01

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

Evaluating Hierarchical Structure in Music Annotations

Directory of Open Access Journals (Sweden)

Brian McFee

2017-08-01

Full Text Available 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.

Growth, characterization and electrochemical properties of hierarchical CuO nanostructures for supercapacitor applications

Energy Technology Data Exchange (ETDEWEB)

Krishnamoorthy, Karthikeyan [Nanomaterials and System Laboratory, Department of Mechanical Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of); Kim, Sang-Jae, E-mail: kimsangj@jejunu.ac.kr [Nanomaterials and System Laboratory, Department of Mechanical Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of); Department of Mechatronics Engineering, Jeju National University, Jeju 690 756 (Korea, Republic of)

2013-09-01

Graphical abstract: - Highlights: • Hierarchical CuO nanostructures were grown on Cu foil. • Monoclinic phase of CuO was grown. • XPS analysis revealed the presence of Cu(2p{sub 3/2}) and Cu(2p{sub 1/2}) on the surfaces. • Specific capacitance of 94 F/g was achieved for the CuO using cyclic voltammetry. • Impedance spectra show their pseudo capacitor applications. - Abstract: In this paper, we have investigated the electrochemical properties of hierarchical CuO nanostructures for pseudo-supercapacitor device applications. Moreover, the CuO nanostructures were formed on Cu substrate by in situ crystallization process. The as-grown CuO nanostructures were characterized using X-ray diffraction (XRD), Fourier transform-infra red spectroscopy (FT-IR), X-ray photoelectron spectroscopy and field emission-scanning electron microscope (FE-SEM) analysis. The XRD and FT-IR analysis confirm the formation of monoclinic CuO nanostructures. FE-SEM analysis shows the formation of leave like hierarchical structures of CuO with high uniformity and controlled density. The electrochemical analysis such as cyclic voltammetry and electrochemical impedance spectroscopy studies confirms the pseudo-capacitive behavior of the CuO nanostructures. Our experimental results suggest that CuO nanostructures will create promising applications of CuO toward pseudo-supercapacitors.

Growth, characterization and electrochemical properties of hierarchical CuO nanostructures for supercapacitor applications

International Nuclear Information System (INIS)

Krishnamoorthy, Karthikeyan; Kim, Sang-Jae

2013-01-01

Graphical abstract: - Highlights: • Hierarchical CuO nanostructures were grown on Cu foil. • Monoclinic phase of CuO was grown. • XPS analysis revealed the presence of Cu(2p 3/2 ) and Cu(2p 1/2 ) on the surfaces. • Specific capacitance of 94 F/g was achieved for the CuO using cyclic voltammetry. • Impedance spectra show their pseudo capacitor applications. - Abstract: In this paper, we have investigated the electrochemical properties of hierarchical CuO nanostructures for pseudo-supercapacitor device applications. Moreover, the CuO nanostructures were formed on Cu substrate by in situ crystallization process. The as-grown CuO nanostructures were characterized using X-ray diffraction (XRD), Fourier transform-infra red spectroscopy (FT-IR), X-ray photoelectron spectroscopy and field emission-scanning electron microscope (FE-SEM) analysis. The XRD and FT-IR analysis confirm the formation of monoclinic CuO nanostructures. FE-SEM analysis shows the formation of leave like hierarchical structures of CuO with high uniformity and controlled density. The electrochemical analysis such as cyclic voltammetry and electrochemical impedance spectroscopy studies confirms the pseudo-capacitive behavior of the CuO nanostructures. Our experimental results suggest that CuO nanostructures will create promising applications of CuO toward pseudo-supercapacitors

Computational content analysis of European Central Bank statements

NARCIS (Netherlands)

Milea, D.V.; Almeida, R.J.; Sharef, N.M.; Kaymak, U.; Frasincar, F.

2012-01-01

In this paper we present a framework for the computational content analysis of European Central Bank (ECB) statements. Based on this framework, we provide two approaches that can be used in a practical context. Both approaches use the content of ECB statements to predict upward and downward movement

A System for the Semantic Multimodal Analysis of News Audio-Visual Content

Directory of Open Access Journals (Sweden)

Michael G. Strintzis

2010-01-01

Full Text Available News-related content is nowadays among the most popular types of content for users in everyday applications. Although the generation and distribution of news content has become commonplace, due to the availability of inexpensive media capturing devices and the development of media sharing services targeting both professional and user-generated news content, the automatic analysis and annotation that is required for supporting intelligent search and delivery of this content remains an open issue. In this paper, a complete architecture for knowledge-assisted multimodal analysis of news-related multimedia content is presented, along with its constituent components. The proposed analysis architecture employs state-of-the-art methods for the analysis of each individual modality (visual, audio, text separately and proposes a novel fusion technique based on the particular characteristics of news-related content for the combination of the individual modality analysis results. Experimental results on news broadcast video illustrate the usefulness of the proposed techniques in the automatic generation of semantic annotations.

Hierarchical spatial point process analysis for a plant community with high biodiversity

DEFF Research Database (Denmark)

Illian, Janine B.; Møller, Jesper; Waagepetersen, Rasmus

2009-01-01

A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maxim...

Three-dimensional hierarchical porous flower-like nickel-cobalt oxide/multi-walled carbon nanotubes nanocomposite for high-capacity supercapacitors

Energy Technology Data Exchange (ETDEWEB)

Liu, Peipei; Hu, Zhonghua, E-mail: huzh@tongji.edu.cn; Liu, Yafei; Yao, Mingming; Zhang, Qiang

2015-02-15

Highlights: • 3D hierarchical porous flower-like Ni-Co oxide/MWCNTs was synthesized. • The electrode shows a large specific surface area and desirable mesoporosity. • High specific capacitances and outstanding stability were obtained. • The content of MWCNTs affects the electrochemical properties of the electrode. - Abstract: Three-dimensional (3D) hierarchical porous flower-like nickel-cobalt oxide/multi-walled carbon nanotubes (Ni-Co oxide/MWCNTs) nanocomposites were fabricated by a facile and template-free hydrothermal method as electrodes for high-capacity supercapacitors. The samples were characterized by energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), nitrogen adsorption-desorption and thermal gravimetric analysis (TGA). The electrochemical performance was investigated by cyclic voltammetry (CV), galvanostatic charge-discharge, and cycle life. It was found that Ni-Co oxide/MWCNTs nanocomposites displayed a high specific capacitance (1703 F g{sup −1} at a discharge current density of 1 A g{sup −1}) and, additionally, an excellent cycling performance, retaining 97% of the maximum capacitance after 2000 cycles at 10 A g{sup −1}. Even at a high current density (20 A g{sup −1}), the specific capacitance was still up to 1309 F g{sup −1}. This outstanding capacitive performance may be attributed to the ideal composition of the material and to its unique 3D hierarchical porous flower-like architecture.

Three-dimensional hierarchical porous flower-like nickel-cobalt oxide/multi-walled carbon nanotubes nanocomposite for high-capacity supercapacitors

International Nuclear Information System (INIS)

Liu, Peipei; Hu, Zhonghua; Liu, Yafei; Yao, Mingming; Zhang, Qiang

2015-01-01

Highlights: • 3D hierarchical porous flower-like Ni-Co oxide/MWCNTs was synthesized. • The electrode shows a large specific surface area and desirable mesoporosity. • High specific capacitances and outstanding stability were obtained. • The content of MWCNTs affects the electrochemical properties of the electrode. - Abstract: Three-dimensional (3D) hierarchical porous flower-like nickel-cobalt oxide/multi-walled carbon nanotubes (Ni-Co oxide/MWCNTs) nanocomposites were fabricated by a facile and template-free hydrothermal method as electrodes for high-capacity supercapacitors. The samples were characterized by energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), nitrogen adsorption-desorption and thermal gravimetric analysis (TGA). The electrochemical performance was investigated by cyclic voltammetry (CV), galvanostatic charge-discharge, and cycle life. It was found that Ni-Co oxide/MWCNTs nanocomposites displayed a high specific capacitance (1703 F g −1 at a discharge current density of 1 A g −1 ) and, additionally, an excellent cycling performance, retaining 97% of the maximum capacitance after 2000 cycles at 10 A g −1 . Even at a high current density (20 A g −1 ), the specific capacitance was still up to 1309 F g −1 . This outstanding capacitive performance may be attributed to the ideal composition of the material and to its unique 3D hierarchical porous flower-like architecture

Comparing hierarchical models via the marginalized deviance information criterion.

Science.gov (United States)

Quintero, Adrian; Lesaffre, Emmanuel

2018-07-20

Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent variables, there are several versions of this statistic: the conditional DIC (cDIC) that incorporates the latent variables in the focus of the analysis and the marginalized DIC (mDIC) that integrates them out. Regardless of the asymptotic and coherency difficulties of cDIC, this alternative is usually used in Markov chain Monte Carlo (MCMC) methods for hierarchical models because of practical convenience. The mDIC criterion is more appropriate in most cases but requires integration of the likelihood, which is computationally demanding and not implemented in Bayesian software. Therefore, we consider a method to compute mDIC by generating replicate samples of the latent variables that need to be integrated out. This alternative can be easily conducted from the MCMC output of Bayesian packages and is widely applicable to hierarchical models in general. Additionally, we propose some approximations in order to reduce the computational complexity for large-sample situations. The method is illustrated with simulated data sets and 2 medical studies, evidencing that cDIC may be misleading whilst mDIC appears pertinent. Copyright © 2018 John Wiley & Sons, Ltd.

A Bayesian hierarchical model for demand curve analysis.

Science.gov (United States)

Ho, Yen-Yi; Nhu Vo, Tien; Chu, Haitao; Luo, Xianghua; Le, Chap T

2018-07-01

Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine. The conventional approach popularly used to analyze the demand curve data is individual-specific non-linear least square regression. The non-linear least square approach sets out to minimize the residual sum of squares for each subject in the dataset; however, this one-subject-at-a-time approach does not allow for the estimation of between- and within-subject variability in a unified model framework. In this paper, we review the existing approaches to analyze the demand curve data, non-linear least square regression, and the mixed effects regression and propose a new Bayesian hierarchical model. We conduct simulation analyses to compare the performance of these three approaches and illustrate the proposed approaches in a case study of nicotine self-administration in rats. We present simulation results and discuss the benefits of using the proposed approaches.

Applying Hierarchical Task Analysis Method to Discovery Layer Evaluation

Directory of Open Access Journals (Sweden)

Marlen Promann

2015-03-01

Full Text Available Libraries are implementing discovery layers to offer better user experiences. While usability tests have been helpful in evaluating the success or failure of implementing discovery layers in the library context, the focus has remained on its relative interface benefits over the traditional federated search. The informal site- and context specific usability tests have offered little to test the rigor of the discovery layers against the user goals, motivations and workflow they have been designed to support. This study proposes hierarchical task analysis (HTA as an important complementary evaluation method to usability testing of discovery layers. Relevant literature is reviewed for the discovery layers and the HTA method. As no previous application of HTA to the evaluation of discovery layers was found, this paper presents the application of HTA as an expert based and workflow centered (e.g. retrieving a relevant book or a journal article method to evaluating discovery layers. Purdue University’s Primo by Ex Libris was used to map eleven use cases as HTA charts. Nielsen’s Goal Composition theory was used as an analytical framework to evaluate the goal carts from two perspectives: a users’ physical interactions (i.e. clicks, and b user’s cognitive steps (i.e. decision points for what to do next. A brief comparison of HTA and usability test findings is offered as a way of conclusion.

Pro-eating disorder communities on social networking sites: a content analysis.

Science.gov (United States)

Juarascio, Adrienne S; Shoaib, Amber; Timko, C Alix

2010-01-01

The purpose of this study was to assess the number of pro-ana groups on social networking sites and to analyze their content. A general inductive approach was used to analyze the content. Two main themes emerged from the content analysis: social support and eating disorder specific content. Themes were similar across all groups; however, a linguistic analysis indicated differences between groups on the two different networking sites. There was an absence of content typically found on Internet sites. Pro-ana groups on social networking sites are focused on social interactions, and lack eating disorder specific content found on Internet sites.

Hierarchically Nanostructured Materials for Sustainable Environmental Applications

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Zheng eRen

2013-11-01

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

Genomic analysis of the hierarchical structure of regulatory networks

Science.gov (United States)

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

International Nuclear Information System (INIS)

Sanders, N. E.; Soderberg, A. M.; Betancourt, M.

2015-01-01

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

Energy Technology Data Exchange (ETDEWEB)

Sanders, N. E.; Soderberg, A. M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Betancourt, M., E-mail: nsanders@cfa.harvard.edu [Department of Statistics, University of Warwick, Coventry CV4 7AL (United Kingdom)

2015-02-10

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST.

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong; Wu, Tao

2017-01-01

The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced

Web Content Management Systems: An Analysis of Forensic Investigatory Challenges.

Science.gov (United States)

Horsman, Graeme

2018-02-26

With an increase in the creation and maintenance of personal websites, web content management systems are now frequently utilized. Such systems offer a low cost and simple solution for those seeking to develop an online presence, and subsequently, a platform from which reported defamatory content, abuse, and copyright infringement has been witnessed. This article provides an introductory forensic analysis of the three current most popular web content management systems available, WordPress, Drupal, and Joomla! Test platforms have been created, and their site structures have been examined to provide guidance for forensic practitioners facing investigations of this type. Result's document available metadata for establishing site ownership, user interactions, and stored content following analysis of artifacts including Wordpress's wp_users, and wp_comments tables, Drupal's "watchdog" records, and Joomla!'s _users, and _content tables. Finally, investigatory limitations documenting the difficulties of investigating WCMS usage are noted, and analysis recommendations are offered. © 2018 American Academy of Forensic Sciences.

Hierarchically organized layout for visualization of biochemical pathways.

Science.gov (United States)

Tsay, Jyh-Jong; Wu, Bo-Liang; Jeng, Yu-Sen

2010-01-01

Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

The CODESRIA Bulletin: a content analysis | Bangura | African ...

African Journals Online (AJOL)

African Research Review ... A qualitative and quantitative analysis of the contents of the articles can serve many useful purposes. At the most basic level, a simple tabulation can identify trends and changes in the works' contents. ... Browse By Country · List All Titles · Free To Read Titles This Journal is Open Access.

Automation of control and analysis of execution of official duties and instructions in the hierarchical organization

Directory of Open Access Journals (Sweden)

Demchenko A.I.

2017-01-01

Full Text Available The article considers the problem of monitoring over execution of official duties of employees. This problem is characteristic of the enterprises having a hierarchical management structure. The functions and the modes of monitoring are defined, the types of analysis of the staff activities are provided. The description of the program complex allowing distributing functions and instructions for between the employees is given. The developed computer program allows tracking the performance, creating reports. The computer program has a demarcation of access rights and provides the can be operated in both local, and a large-scale network.

Hierarchical screening for multiple mental disorders.

Science.gov (United States)

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

2013-10-01

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

Statistical modelling of railway track geometry degradation using Hierarchical Bayesian models

International Nuclear Information System (INIS)

Andrade, A.R.; Teixeira, P.F.

2015-01-01

Railway maintenance planners require a predictive model that can assess the railway track geometry degradation. The present paper uses a Hierarchical Bayesian model as a tool to model the main two quality indicators related to railway track geometry degradation: the standard deviation of longitudinal level defects and the standard deviation of horizontal alignment defects. Hierarchical Bayesian Models (HBM) are flexible statistical models that allow specifying different spatially correlated components between consecutive track sections, namely for the deterioration rates and the initial qualities parameters. HBM are developed for both quality indicators, conducting an extensive comparison between candidate models and a sensitivity analysis on prior distributions. HBM is applied to provide an overall assessment of the degradation of railway track geometry, for the main Portuguese railway line Lisbon–Oporto. - Highlights: • Rail track geometry degradation is analysed using Hierarchical Bayesian models. • A Gibbs sampling strategy is put forward to estimate the HBM. • Model comparison and sensitivity analysis find the most suitable model. • We applied the most suitable model to all the segments of the main Portuguese line. • Tackling spatial correlations using CAR structures lead to a better model fit

Self-assembled biomimetic superhydrophobic hierarchical arrays.

Science.gov (United States)

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

2013-09-01

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

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

Directory of Open Access Journals (Sweden)

Guo Junqiao

2008-09-01

Full Text Available Abstract Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations.

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

Science.gov (United States)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

Hierarchically structured, nitrogen-doped carbon membranes

KAUST Repository

Wang, Hong

2017-08-03

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

Hierarchical Rhetorical Sentence Categorization for Scientific Papers

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

2015-01-01

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

Predictive Ability of Pender's Health Promotion Model for Physical Activity and Exercise in People with Spinal Cord Injuries: A Hierarchical Regression Analysis

Science.gov (United States)

Keegan, John P.; Chan, Fong; Ditchman, Nicole; Chiu, Chung-Yi

2012-01-01

The main objective of this study was to validate Pender's Health Promotion Model (HPM) as a motivational model for exercise/physical activity self-management for people with spinal cord injuries (SCIs). Quantitative descriptive research design using hierarchical regression analysis (HRA) was used. A total of 126 individuals with SCI were recruited…

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

Directory of Open Access Journals (Sweden)

Xiaowei Li

2017-01-01

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

An Improved 6LoWPAN Hierarchical Routing Protocol

Directory of Open Access Journals (Sweden)

Xue Li

2015-10-01

Full Text Available IETF 6LoWPAN working group is engaged in the IPv6 protocol stack research work based on IEEE802.15.4 standard. In this working group, the routing protocol is one of the important research contents. In the 6LoWPAN, HiLow is a well-known layered routing protocol. This paper puts forward an improved hierarchical routing protocol GHiLow by improving HiLow parent node selection and path restoration strategy. GHiLow improves the parent node selection by increasing the choice of parameters. Simutaneously, it also improves path recovery by analysing different situations to recovery path. Therefore, GHiLow contributes to the ehancement of network performance and the decrease of network energy consumption.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

Science.gov (United States)

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

Content Analysis as a Best Practice in Technical Communication Research

Science.gov (United States)

Thayer, Alexander; Evans, Mary; McBride, Alicia; Queen, Matt; Spyridakis, Jan

2007-01-01

Content analysis is a powerful empirical method for analyzing text, a method that technical communicators can use on the job and in their research. Content analysis can expose hidden connections among concepts, reveal relationships among ideas that initially seem unconnected, and inform the decision-making processes associated with many technical…

Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal.

Science.gov (United States)

Namazi, Hamidreza; Khosrowabadi, Reza; Hussaini, Jamal; Habibi, Shaghayegh; Farid, Ali Akhavan; Kulish, Vladimir V

2016-08-30

One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.

Hierarchical Bayesian Analysis of Biased Beliefs and Distributional Other-Regarding Preferences

Directory of Open Access Journals (Sweden)

Jeroen Weesie

2013-02-01

Full Text Available This study investigates the relationship between an actor’s beliefs about others’ other-regarding (social preferences and her own other-regarding preferences, using an “avant-garde” hierarchical Bayesian method. We estimate two distributional other-regarding preference parameters, α and β, of actors using incentivized choice data in binary Dictator Games. Simultaneously, we estimate the distribution of actors’ beliefs about others α and β, conditional on actors’ own α and β, with incentivized belief elicitation. We demonstrate the benefits of the Bayesian method compared to it’s hierarchical frequentist counterparts. Results show a positive association between an actor’s own (α; β and her beliefs about average(α; β in the population. The association between own preferences and the variance in beliefs about others’ preferences in the population, however, is curvilinear for α and insignificant for β. These results are partially consistent with the cone effect [1,2] which is described in detail below. Because in the Bayesian-Nash equilibrium concept, beliefs and own preferences are assumed to be independent, these results cast doubt on the application of the Bayesian-Nash equilibrium concept to experimental data.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

Science.gov (United States)

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.

Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

Science.gov (United States)

Fesharaki, Nooshin Jafari; Pourghassem, Hossein

2013-07-01

Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

Zeolitic materials with hierarchical porous structures.

Science.gov (United States)

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

2011-06-17

During the past several years, different kinds of hierarchical structured zeolitic materials have been synthesized due to their highly attractive properties, such as superior mass/heat transfer characteristics, lower restriction of the diffusion of reactants in the mesopores, and low pressure drop. Our contribution provides general information regarding types and preparation methods of hierarchical zeolitic materials and their relative advantages and disadvantages. Thereafter, recent advances in the preparation and characterization of hierarchical zeolitic structures within the crystallites by post-synthetic treatment methods, such as dealumination or desilication; and structured devices by in situ and ex situ zeolite coatings on open-cellular ceramic foams as (non-reactive as well as reactive) supports are highlighted. Specific advantages of using hierarchical zeolitic catalysts/structures in selected catalytic reactions, such as benzene to phenol (BTOP) and methanol to olefins (MTO) are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Processing of hierarchical syntactic structure in music.

Science.gov (United States)

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.

"Analyzing the Longitudinal K-12 Grading Histories of Entire Cohorts of Students: Grades, Data Driven Decision Making, Dropping out and Hierarchical Cluster Analysis"

Directory of Open Access Journals (Sweden)

Alex J. Bowers

2010-05-01

Full Text Available School personnel currently lack an effective method to pattern and visually interpret disaggregated achievement data collected on students as a means to help inform decision making. This study, through the examination of longitudinal K-12 teacher assigned grading histories for entire cohorts of students from a school district (n=188, demonstrates a novel application of hierarchical cluster analysis and pattern visualization in which all data points collected on every student in a cohort can be patterned, visualized and interpreted to aid in data driven decision making by teachers and administrators. Additionally, as a proof-of-concept study, overall schooling outcomes, such as student dropout or taking a college entrance exam, are identified from the data patterns and compared to past methods of dropout identification as one example of the usefulness of the method. Hierarchical cluster analysis correctly identified over 80% of the students who dropped out using the entire student grade history patterns from either K-12 or K-8.

Hierarchical Nanoceramics for Industrial Process Sensors

Energy Technology Data Exchange (ETDEWEB)

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

2011-07-15

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

Hierarchically structured distributed microprocessor network for control

International Nuclear Information System (INIS)

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

1979-01-01

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

The Case for a Hierarchical Cosmology

Science.gov (United States)

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)

Classification using Hierarchical Naive Bayes models

DEFF Research Database (Denmark)

Langseth, Helge; Dyhre Nielsen, Thomas

2006-01-01

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

Effect of Job Autonomy Upon Organizational Commitment of Employees at Different Hierarchical Level

Directory of Open Access Journals (Sweden)

Shalini Sisodia

2013-10-01

Full Text Available The main aim of the present study was to examine the effect of job autonomy upon organizational commitment of employees at different hierarchical level. A study was made on randomly selected 100 male employees who work in different organizations in Agra, who were administered Organizational Commitment Scale (by Allen & Meyer, 1990 and Job Autonomy Scale (by Das, Arora, & Singhal, 2000. On the basis of median of the job autonomy scores, the sample was divided into two groups (1 high job autonomy group and (2 low job autonomy group and on the basis of hierarchical level, the employees were divided into two groups (1 50 high hierarchical level employees’ including managers, etc. and (2 50 low hierarchical level employees, e.g. clerical staff, etc. The 2x2 factorial design was formed for this purpose and four groups of employees were formed (1 high hierarchy, high autonomy group (2 high hierarchy, low autonomy group(3 low hierarchy, high autonomy group and (4 low hierarchy, low autonomy group. A two-way analysis of variance was employed to compare the level of organizational commitment of each of the four groups. There is a significant difference found between job commitment of employees with high and low job autonomy (F = 4.670, p < .05. There is a significant difference found between job commitment of employees of high hierarchical group and those of low hierarchical group (F = 40.691, p < .01 and significant interaction effect found between job autonomy and hierarchical level upon organizational commitment of employees (F = 6.114, p < .05.

Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

Science.gov (United States)

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.

Nondestructive analysis of sugar content on watermelon using MRI device

International Nuclear Information System (INIS)

Miki, Takashi; Saito, Kazuyoshi; Hayashi, Seiji

1996-01-01

So far, the use of superconducting magnets has been limited to chemical analysis and medical inspection. To develop a new use, we have tried to apply common MRI devices as nondestructive sugar content detector of watermelon. To estimate the sugar content, a new technique using multiple regression analysis of two NMR relaxation times was developed. It was found that the coefficient of multiple regression at the center of the watermelon exceeded 0.9 and the standard error of prediction was around 0.5, and that the over-ripened part of flesh called 'nieka' in watermelon could be distinguished because its T 2 was much longer than that of the ordinary part. An evaluation rate of sugar content could be below 6s per watermelon. It is concluded that multiple analysis of T 1 and T 2 on intact watermelon can be applied as a noninvasive, nondestructive indicator of sugar content. (author)

Multimedia content analysis

CERN Document Server

Ohm, Jens

2016-01-01

This textbook covers the theoretical backgrounds and practical aspects of image, video and audio feature expression, e.g., color, texture, edge, shape, salient point and area, motion, 3D structure, audio/sound in time, frequency and cepstral domains, structure and melody. Up-to-date algorithms for estimation, search, classification and compact expression of feature data are described in detail. Concepts of signal decomposition (such as segmentation, source tracking and separation), as well as composition, mixing, effects, and rendering, are discussed. Numerous figures and examples help to illustrate the aspects covered. The book was developed on the basis of a graduate-level university course, and most chapters are supplemented by problem-solving exercises. The book is also a self-contained introduction both for researchers and developers of multimedia content analysis systems in industry. .

Surface Water Quality Assessment and Prioritize the Factors Pollute This Water Using Topsis Fuzzy Hierarchical Analysis

Directory of Open Access Journals (Sweden)

Mehdi Komasi

2017-03-01

Full Text Available Background & Objective: Nowadays, according to growth of industry and increasing population, water resources are seriousely shortened. This lack of water resources will require special management to be considered in industry and agriculture. Among the various sources of water, surface waters are more susceptible to infection. The most important of these sources of pollution are industrial pollution, detergent, pesticides, radioactive materials, heat and salt concentration.  Materials & methods: In this article, at first the importance of each pollutant will be evaluated base on the effects and its results and then quality evaluation of surface water will be studied. In order to assess the relative importance of these pollutants primarily using TOPSIS software, prioritize these factors as one of the hierarchical analysis and then is modeled with decision tree method using Weka software, the importance of each factor is evaluated and if it does not meet the minimal importance of the decision tree will be removed. Results: The results obtained from the Topsis fuzzy analysis indicate that surface water and groundwater are exposed to pollution about 74% and 26% respectively among the six pollutants examined in this study. In addition, results obtaned from the hierarchical tree in software Weka has shown that the heat factor, soluble salts and industrial pollutants give impac factor or purity about 0.1338, 0.0523 and 1.2694 respectively. Conclusion: Surface water is at greater risk of being polluted compared with groundwater. The heat factor and low concentration of dissolved salts have the low impact and industrial pollutants are considered as the most influential factors in surface water pollution.

Nuclear physical express analysis of solid fuel sulphur content

International Nuclear Information System (INIS)

Pak, Yu.; Ponomaryova, M

2005-01-01

Full text: Sulphur content is an important qualitative coal parameter. The problem of coal sulphur content determining remains one of the most important both in Kazakhstan and in other coal-mining countries. The traditional method of sampling, the final stage of which is chemical analysis of coal for sulphur, is characterized by high labour intensity and low productivity. That's why it is ineffective for mass express analytical quality control and technological schemes of coal processing control. In this connection it is very urgent to develop a method of coal sulphur content on the base of a series nuclear-geophysical equipment with an isotope source of primary radiation, allowing to increase analysis representativity and maximally take into account coal real composition inconstancy. To solve the problem set it is necessary to study the main laws of X-ray-radiometric method applied to the coal quality analysis for working out instrumental methods of speed determining of coal sulphur content with satisfactory accuracy for technological tasks, to determine laws of changing the flows of characteristic X-ray and scattered radiation from coal sulphur content of various real composition and to optimize methodical and hardware parameters, providing minimal error of sulphur content control. On the base of studying laws of real composition coal components and their interconnections with sulphur content there has been substantiated the expediency of using hardware functions of calcium and iron to control coal sulphur contents; there has been suggested a model to estimate the methodical error of coal sulphur content determining on the base of the data about sensitivity to sulphur and effecting factors using ultimate methods of coal components substitution methods allowing to optimize sulphur control parameters; there has been worked out an algorithm of X-ray-radiometric control of sulphur content based on the sequential radiating the analyzed coal with gamma-radiation of

Multidisciplinary cognitive content of nanoscience and nanotechnology

International Nuclear Information System (INIS)

Milojević, Staša

2012-01-01

This article examines the cognitive evolution and disciplinary diversity of nanoscience/nanotechnology (nano research) as expressed through the terminology used in titles of nano journal articles. The analysis is based on the NanoBank bibliographic database of 287,106 nano articles published between 1981 and 2004. We perform multifaceted analyses of title words, focusing on 100 most frequent words or phrases (terms). Hierarchical clustering of title terms reveals three distinct time periods of cognitive development of nano research: formative (1981–1990), early (from 1991 to 1998), and current (after 1998). Early period is characterized by the introduction of thin film deposition techniques, while the current period is characterized by the increased focus on carbon nanotube and nanoparticle research. We introduce a method to identify disciplinary components of nanotechnology. It shows that the nano research is being carried out in a number of diverse parent disciplines. Currently, only 5% of articles are published in dedicated nano-only journals. We find that some 85% of nano research today is multidisciplinary. The case study of the diffusion of several nano-specific terms (e.g., “carbon nanotube”) shows that concepts spread from the initially few disciplinary components to the majority of them in a time span of around a decade. Hierarchical clustering of disciplinary components reveals that the cognitive content of current nanoscience can be divided into nine clusters. Some clusters account for a large fraction of nano research and are identified with such parent disciplines as the condensed matter and applied physics, materials science, and analytical chemistry. Other clusters represent much smaller parts of nano research, but are as cognitively distinct. In the decreasing order of size, these fields are: polymer science, biotechnology, general chemistry, surface science, and pharmacology. Cognitive content of research published in nano-only journals is

Addictions Content Published in Counseling Journals: A 10-Year Content Analysis to Inform Research and Practice

Science.gov (United States)

Wahesh, Edward; Likis-Werle, S. Elizabeth; Moro, Regina R.

2017-01-01

This content analysis includes 210 articles that focused on addictions topics published between January 2005 and December 2014 in the journals of the National Board for Certified Counselors (NBCC), Chi Sigma Iota (CSI), the American Counseling Association (ACA), and ACA member divisions. Results include the types of addictions content and…

A local adaptive algorithm for emerging scale-free hierarchical networks

International Nuclear Information System (INIS)

Gomez Portillo, I J; Gleiser, P M

2010-01-01

In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

A Hierarchical Agency Model of Deposit Insurance

OpenAIRE

Jonathan Carroll; Shino Takayama

2010-01-01

This paper develops a hierarchical agency model of deposit insurance. The main purpose is to undertake a game theoretic analysis of the consequences of deposit insurance schemes and their effects on monitoring incentives for banks. Using this simple framework, we analyze both risk- independent and risk-dependent premium schemes along with reserve requirement constraints. The results provide policymakers with not only a better understanding of the effects of deposit insurance on welfare and th...

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

Analysis of intra-genomic GC content homogeneity within prokaryotes

DEFF Research Database (Denmark)

Bohlin, J; Snipen, L; Hardy, S.P.

2010-01-01

the GC content varies within microbial genomes to assess whether this property can be associated with certain biological functions related to the organism's environment and phylogeny. We utilize a new quantity GCVAR, the intra-genomic GC content variability with respect to the average GC content......Bacterial genomes possess varying GC content (total guanines (Gs) and cytosines (Cs) per total of the four bases within the genome) but within a given genome, GC content can vary locally along the chromosome, with some regions significantly more or less GC rich than on average. We have examined how...... both aerobic and facultative microbes. Although an association has previously been found between mean genomic GC content and oxygen requirement, our analysis suggests that no such association exits when phylogenetic bias is accounted for. A significant association between GCVAR and mean GC content...

Metabolite Profiling of Peppers of Various Colors Reveals Relationships Between Tocopherol, Carotenoid, and Phytosterol Content.

Science.gov (United States)

Kim, Tae Jin; Choi, Jaehyuk; Kim, Kil Won; Ahn, Soon Kil; Ha, Sun-Hwa; Choi, Yongsoo; Park, Nam Il; Kim, Jae Kwang

2017-12-01

Peppers are widely consumed in Korea; the varietal development of peppers with increased content of beneficial plant metabolites is, therefore, of considerable interest. This requires a comprehensive understanding of the metabolic profile of pepper plants and the factors affecting this profile. To this end, we determined the content of various metabolites, such as hydrophilic and lipophilic compounds, phenolic acids, carotenoids, and capsaicinoids in peppers of various colors (green, red, pale green, and violet peppers) and in a high-pungency (green) pepper. We also performed principal component analysis (PCA), Pearson's correlation analysis, and hierarchical clustering analysis (HCA) to determine the relationships among these metabolites in peppers. PCA results indicated no significant variances among the 3 sample replicates. The HCA showed correlations between the metabolites resulting from common or closely linked biosynthesis pathways. Our results showed that carotenoids correlated positively with tocopherols and negatively with phytosterols; our findings also indicated a close relationship between the methylerythritol 4-phosphate and mevalonic acid biosynthesis pathways, providing evidence in favor of an earlier hypothesis regarding crosstalk across the chloroplast membrane. We, thus, demonstrate that metabolic profiling combined with multivariate analysis is a useful tool for analyzing metabolic networks. A total of 71 metabolites were measured in 5 peppers of different colors. The metabolic profiling with multivariate analysis revealed that tocopherol content had a positive correlation with the carotenoid content and a negative correlation with the phytosterol content. The results of this study may help in breeding programs to produce new germplasm with enhanced nutritional quality. © 2017 Institute of Food Technologists®.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

Science.gov (United States)

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Location optimization of solar plants by an integrated hierarchical DEA PCA approach

International Nuclear Information System (INIS)

Azadeh, A.; Ghaderi, S.F.; Maghsoudi, A.

2008-01-01

Unique features of renewable energies such as solar energy has caused increasing demands for such resources. In order to use solar energy as a natural resource, environmental circumstances and geographical location related to solar intensity must be considered. Different factors may affect on the selection of a suitable location for solar plants. These factors must be considered concurrently for optimum location identification of solar plants. This article presents an integrated hierarchical approach for location of solar plants by data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT). Furthermore, an integrated hierarchical DEA approach incorporating the most relevant parameters of solar plants is introduced. Moreover, 2 multivariable methods namely, PCA and NT are used to validate the results of DEA model. The prescribed approach is tested for 25 different cities in Iran with 6 different regions within each city. This is the first study that considers an integrated hierarchical DEA approach for geographical location optimization of solar plants. Implementation of the proposed approach would enable the energy policy makers to select the best-possible location for construction of a solar power plant with lowest possible costs

One-pot pseudomorphic crystallization of mesoporous porous silica to hierarchical porous zeolites

Energy Technology Data Exchange (ETDEWEB)

Xing, Jun-Ling; Jiang, Shu-Hua; Pang, Jun-Ling; Yuan, En-Hui; Ma, Xiao-Jing [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China); Lam, Koon-Fung [Department of Chemical Engineering, University College London, Torrington Place, London (United Kingdom); Xue, Qing-Song, E-mail: qsxue@chem.ecnu.edu.cn [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China); Zhang, Kun, E-mail: kzhang@chem.ecnu.edu.cn [Shanghai Key Laboratory of Green Chemistry and Chemical Processes, College of Chemistry and Molecular Engineering, East China Normal University, No. 3663 Zhongshan North Road, 200062 Shanghai (China)

2015-09-15

Hierarchically porous silica with mesopore and zeolitic micropore was synthesized via pseudomorphic crystallization under high-temperature hydrothermal treatment in the presence of cetyltrimethylammonium tosylate and tetrapropylammonium ions. A combined characterization using small-angle X-ray diffraction (XRD), nitrogen adsorption, high-resolution transmission electron microscopy (TEM), thermogravimetric analysis (TG), and elemental analysis showed that dual templates, CTA{sup +} and TPA{sup +} molecules, can work in a cooperative manner to synthesize mesoporous zeolite in a one-pot system by precisely tuning the reaction conditions, such as reaction time and temperature, and type and amount of heterometal atoms. It is found that the presence of Ti precursor is critical to the successful synthesis of such nanostructure. It not only retards the nucleation and growth of crystalline MFI domains, but also acts as nano-binder or nano-glue to favor the assembly of zeolite nanoblocks. - Graphical abstract: Display Omitted - Highlights: • A facile method to synthesize mesoporous zeolites with hierarchical porosity was presented. • It gives a new insight into keeping the balance between mesoscopic and molecular ordering in hierarchical porous materials. • A new understanding on the solid–solid transformation mechanism for the synthesis of titanosilicate zeolites was proposed.

Content and Style of Advice in Iran and Canada

Science.gov (United States)

Tavakoli, Mahin

2013-01-01

The content and nature of nonprofessional advice in Iran, a hierarchical and collectivist culture, was compared to the same type of advice in Canada, an egalitarian and individualist culture. A researcher developed a questionnaire that consisted of 10 letters, each describing a writer's problem and asking for advice. The responses of participants…

Analysis of Contents of Tanzanian University Library Websites | Sife ...

African Journals Online (AJOL)

A study was carried out between January and February 2013 to analyze the contents of 16 university and university college library websites in Tanzania using content analysis method. The consolidated data were analyzed using Microsoft Excel and presented in tabular form. The study findings revealed that although many ...

Content analysis: What are they talking about?

NARCIS (Netherlands)

Strijbos, J.W.; Martens, R.L.; Prins, F.J.; Jochems, W.M.G.

2006-01-01

Quantitative content analysis is increasingly used to surpass surface level analyses in computer-supported collaborative learning (e.g., counting messages), but critical reflection on accepted practice has generally not been reported. A review of CSCL conference proceedings revealed a general

Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness.

Science.gov (United States)

Graneheim, U H; Lundman, B

2004-02-01

Qualitative content analysis as described in published literature shows conflicting opinions and unsolved issues regarding meaning and use of concepts, procedures and interpretation. This paper provides an overview of important concepts (manifest and latent content, unit of analysis, meaning unit, condensation, abstraction, content area, code, category and theme) related to qualitative content analysis; illustrates the use of concepts related to the research procedure; and proposes measures to achieve trustworthiness (credibility, dependability and transferability) throughout the steps of the research procedure. Interpretation in qualitative content analysis is discussed in light of Watzlawick et al.'s [Pragmatics of Human Communication. A Study of Interactional Patterns, Pathologies and Paradoxes. W.W. Norton & Company, New York, London] theory of communication.

Content analysis of Student's short messages; Tehran's universities

Directory of Open Access Journals (Sweden)

Masoud Kowsari

2008-07-01

Full Text Available Recently, cell phone, as an unlimited media, in comparison with others, has deeply changed the modes of interpersonal connections. Accessibility, and inexpensiveness, in addition to the transcendence of normal face to face relation restrictions, could be taken for granted as most fascinating features of SMS. Therefore, content analysis of the SMS could help to clarify the communicative subjectivities in interpersonal communications. This study tends to analyze the content of 2651 short messages exchanged among 80 students both genders, in various universities in Tehran. This paper attempts to answer the following questions: Who are the main senders of the messages? In what time are the SMS s frequently s sent or received? What are the most frequent contents? Is there any relationship between the gender of recipients/senders and the content of the messages? Whether the contents are related to the marital statue of the receiver and sender or not?

Predicting the decision to pursue mediation in civil disputes: a hierarchical classes analysis.

Science.gov (United States)

Reich, Warren A; Kressel, Kenneth; Scanlon, Kathleen M; Weiner, Gary A

2007-11-01

Clients (N = 185) involved in civil court cases completed the CPR Institute's Mediation Screen, which is designed to assist in making a decision about pursuing mediation. The authors modeled data using hierarchical classes analysis (HICLAS), a clustering algorithm that places clients into 1 set of classes and CPRMS items into another set of classes. HICLAS then links the sets of classes so that any class of clients can be identified in terms of the classes of items they endorsed. HICLAS-derived item classes reflected 2 underlying themes: (a) suitability of the dispute for a problem-solving process and (b) potential benefits of mediation. All clients who perceived that mediation would be beneficial also believed that the context of their conflict was favorable to mediation; however, not all clients who saw a favorable context believed they would benefit from mediation. The majority of clients who agreed to pursue mediation endorsed items reflecting both contextual suitability and perceived benefits of mediation.

Virtual timers in hierarchical real-time systems

NARCIS (Netherlands)

Heuvel, van den M.M.H.P.; Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.; Zhu, D.

2009-01-01

Hierarchical scheduling frameworks (HSFs) provide means for composing complex real-time systems from welldefined subsystems. This paper describes an approach to provide hierarchically scheduled real-time applications with virtual event timers, motivated by the need for integrating priority

Assessment of genetic divergence in tomato through agglomerative hierarchical clustering and principal component analysis

International Nuclear Information System (INIS)

Iqbal, Q.; Saleem, M.Y.; Hameed, A.; Asghar, M.

2014-01-01

For the improvement of qualitative and quantitative traits, existence of variability has prime importance in plant breeding. Data on different morphological and reproductive traits of 47 tomato genotypes were analyzed for correlation,agglomerative hierarchical clustering and principal component analysis (PCA) to select genotypes and traits for future breeding program. Correlation analysis revealed significant positive association between yield and yield components like fruit diameter, single fruit weight and number of fruits plant-1. Principal component (PC) analysis depicted first three PCs with Eigen-value higher than 1 contributing 81.72% of total variability for different traits. The PC-I showed positive factor loadings for all the traits except number of fruits plant-1. The contribution of single fruit weight and fruit diameter was highest in PC-1. Cluster analysis grouped all genotypes into five divergent clusters. The genotypes in cluster-II and cluster-V exhibited uniform maturity and higher yield. The D2 statistics confirmed highest distance between cluster- III and cluster-V while maximum similarity was observed in cluster-II and cluster-III. It is therefore suggested that crosses between genotypes of cluster-II and cluster-V with those of cluster-I and cluster-III may exhibit heterosis in F1 for hybrid breeding and for selection of superior genotypes in succeeding generations for cross breeding programme. (author)

Information-theoretical analysis of private content identification

NARCIS (Netherlands)

Voloshynovskiy, S.; Koval, O.; Beekhof, F.; Farhadzadeh, F.; Holotyak, T.

2010-01-01

In recent years, content identification based on digital fingerprinting attracts a lot of attention in different emerging applications. At the same time, the theoretical analysis of digital fingerprinting systems for finite length case remains an open issue. Additionally, privacy leaks caused by

Hierarchical modelling of line commutated power systems used in particle accelerators using Saber

International Nuclear Information System (INIS)

Reimund, J.A.

1993-01-01

This paper discusses the use of hierarchical simulation models using the program Saber trademark for the prediction of magnet ripple currents generated by the power supply/output filter combination. Modeling of an entire power system connected to output filters and particle accelerator ring magnets will be presented. Special emphasis is made on the modeling of power source imbalances caused by transformer impedance imbalances and utility variances. The affect that these imbalances have on the harmonic content of ripple current is also investigated

Content-based TV sports video retrieval using multimodal analysis

Science.gov (United States)

Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

2003-09-01

In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

Hierarchical Layered WS2 /Graphene-Modified CdS Nanorods for Efficient Photocatalytic Hydrogen Evolution.

Science.gov (United States)

Xiang, Quanjun; Cheng, Feiyue; Lang, Di

2016-05-10

Graphene-based ternary composite photocatalysts with genuine heterostructure constituents have attracted extensive attention in photocatalytic hydrogen evolution. Here we report a new graphene-based ternary composite consisting of CdS nanorods grown on hierarchical layered WS2 /graphene hybrid (WG) as a high-performance photocatalyst for hydrogen evolution under visible light irradiation. The optimal content of layered WG as a co-catalyst in the ternary CdS/WS2 /graphene composites was found to be 4.2 wt %, giving a visible light photocatalytic H2 -production rate of 1842 μmol h(-1)  g(-1) with an apparent quantum efficiency of 21.2 % at 420 nm. This high photocatalytic H2 -production activity is due to the deposition of CdS nanorods on layered WS2 /graphene sheets, which can efficiently suppress charge recombination, improve interfacial charge transfer, and provide reduction active sites. The proposed mechanism for the enhanced photocatalytic activity of CdS nanorods modified with hierarchical layered WG was further confirmed by transient photocurrent response. This work shows that a noble-metal-free hierarchical layered WS2 /graphene nanosheets hybrid can be used as an effective co-catalyst for photocatalytic water splitting. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The use of content analysis in the assessment of medical controversies.

Science.gov (United States)

de Villiers, F P

1991-12-01

Medicine is fraught with controversies, and several strategies have been developed in order to reach rational conclusions. Examples are using more subjects or an improved research design, developing consensus statements or using meta-analysis. An additional strategy is described in this paper. The language content of scientific papers is examined to establish whether the authors use factual (informational) language or emotional appeals (directive language) to convince the reader. This type of content analysis is then applied to a sample controversy. The paper shows that directive language content analysis can be applied effectively to scientific publications to clarify the basis of and reasoning behind some controversies.

Ontology-based content analysis of US patent applications from 2001-2010.

Science.gov (United States)

Weber, Lutz; Böhme, Timo; Irmer, Matthias

2013-01-01

Ontology-based semantic text analysis methods allow to automatically extract knowledge relationships and data from text documents. In this review, we have applied these technologies for the systematic analysis of pharmaceutical patents. Hierarchical concepts from the knowledge domains of chemical compounds, diseases and proteins were used to annotate full-text US patent applications that deal with pharmacological activities of chemical compounds and filed in the years 2001-2010. Compounds claimed in these applications have been classified into their respective compound classes to review the distribution of scaffold types or general compound classes such as natural products in a time-dependent manner. Similarly, the target proteins and claimed utility of the compounds have been classified and the most relevant were extracted. The method presented allows the discovery of the main areas of innovation as well as emerging fields of patenting activities - providing a broad statistical basis for competitor analysis and decision-making efforts.

Investigating the provenance of iron artifacts of the Royal Iron Factory of Sao Joao de Ipanema by hierarchical cluster analysis of EDS microanalyses of slag inclusions

Energy Technology Data Exchange (ETDEWEB)

Mamani-Calcina, Elmer Antonio; Landgraf, Fernando Jose Gomes; Azevedo, Cesar Roberto de Farias, E-mail: c.azevedo@usp.br [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Escola Politecnica. Departmento de Engenharia Metalurgica e de Materiais

2017-01-15

Microstructural characterization techniques, including EDX (Energy Dispersive X-ray Analysis) microanalyses, were used to investigate the slag inclusions in the microstructure of ferrous artifacts of the Royal Iron Factory of Sao Joao de Ipanema (first steel plant of Brazil, XIX century), the D. Pedro II Bridge (located in Bahia, assembled in XIX century and produced in Scotland) and the archaeological sites of Sao Miguel de Missoes (Rio Grande do Sul, Brazil, production site of iron artifacts, the XVIII century) and Afonso Sardinha (Sao Paulo, Brazil production site of iron artifacts, XVI century). The microanalyses results of the main micro constituents of the microstructure of the slag inclusions were investigated by hierarchical cluster analysis and the dendrogram with the microanalyses results of the wüstite phase (using as critical variables the contents of MnO, MgO, Al{sub 2}O{sub 3}, V{sub 2}O{sub 5} and TiO{sub 2}) allowed the identification of four clusters, which successfully represented the samples of the four investigated sites (Ipanema, Sardinha, Missoes and Bahia). Finally, the comparatively low volumetric fraction of slag inclusions in the samples of Ipanema (∼1%) suggested the existence of technological expertise at the iron making processing in the Royal Iron Factory of Sao Joao de Ipanema. (author)

Hierarchical organization versus self-organization

OpenAIRE

Busseniers, Evo

2014-01-01

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

Topology of the correlation networks among major currencies using hierarchical structure methods

Science.gov (United States)

Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

2011-02-01

We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

Discrete hierarchical organization of social group sizes.

Science.gov (United States)

Zhou, W-X; Sornette, D; Hill, R A; Dunbar, R I M

2005-02-22

The 'social brain hypothesis' for the evolution of large brains in primates has led to evidence for the coevolution of neocortical size and social group sizes, suggesting that there is a cognitive constraint on group size that depends, in some way, on the volume of neural material available for processing and synthesizing information on social relationships. More recently, work on both human and non-human primates has suggested that social groups are often hierarchically structured. We combine data on human grouping patterns in a comprehensive and systematic study. Using fractal analysis, we identify, with high statistical confidence, a discrete hierarchy of group sizes with a preferred scaling ratio close to three: rather than a single or a continuous spectrum of group sizes, humans spontaneously form groups of preferred sizes organized in a geometrical series approximating 3-5, 9-15, 30-45, etc. Such discrete scale invariance could be related to that identified in signatures of herding behaviour in financial markets and might reflect a hierarchical processing of social nearness by human brains.

Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

Science.gov (United States)

Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

2012-11-01

This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

Science.gov (United States)

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Deep learning, audio adversaries, and music content analysis

DEFF Research Database (Denmark)

Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

2015-01-01

We present the concept of adversarial audio in the context of deep neural networks (DNNs) for music content analysis. An adversary is an algorithm that makes minor perturbations to an input that cause major repercussions to the system response. In particular, we design an adversary for a DNN...... that takes as input short-time spectral magnitudes of recorded music and outputs a high-level music descriptor. We demonstrate how this adversary can make the DNN behave in any way with only extremely minor changes to the music recording signal. We show that the adversary cannot be neutralised by a simple...... filtering of the input. Finally, we discuss adversaries in the broader context of the evaluation of music content analysis systems....

Au functionalized ZnO rose-like hierarchical structures and their enhanced NO2 sensing performance

Science.gov (United States)

Shingange, K.; Swart, H. C.; Mhlongo, G. H.

2018-04-01

Herein, we present ZnO rose-like hierarchical nanostructures employed as support to Au nanoparticles to produce Au functionalized three dimensional (3D) ZnO hierarchical nanostructures (Au/ZnO) for NO2 detection using a microwave-assisted method. Comparative analysis of NO2 sensing performance between the pristine ZnO and Au/ZnO rose-like structures at 300 °C revealed improved NO2 response and rapid response-recovery times with Au incorporation owing to a combination of high surface accessibility induced by hierarchical nanostructure design and catalytic activity of the small Au nanoparticles. Structural and optical analyses acquired from X-ray diffraction, scanning electron microscopy, transmission electron microscope and photoluminescence spectroscopy were also performed.

Independent component analysis for understanding multimedia content

DEFF Research Database (Denmark)

Kolenda, Thomas; Hansen, Lars Kai; Larsen, Jan

2002-01-01

Independent component analysis of combined text and image data from Web pages has potential for search and retrieval applications by providing more meaningful and context dependent content. It is demonstrated that ICA of combined text and image features has a synergistic effect, i.e., the retrieval...

Qualitative content analysis of complementary topical therapies ...

African Journals Online (AJOL)

In order to alleviate diabetic foot problems, patients sometimes seek complementary therapies outside the professional context. This paper describes the use of complementary remedies as a topical treatment for diabetic foot ulcers among Jordanians. Qualitative content analysis was used to analyse written responses of 68 ...

Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

Science.gov (United States)

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.

Multiparty hierarchical quantum-information splitting

International Nuclear Information System (INIS)

Wang Xinwen; Zhang Dengyu; Tang Shiqing; Xie Lijun

2011-01-01

We propose a scheme for multiparty hierarchical quantum-information splitting (QIS) with a multipartite entangled state, where a boss distributes a secret quantum state to two grades of agents asymmetrically. The agents who belong to different grades have different authorities for recovering the boss's secret. Except for the boss's Bell-state measurement, no nonlocal operation is involved. The presented scheme is also shown to be secure against eavesdropping. Such a hierarchical QIS is expected to find useful applications in the field of modern multipartite quantum cryptography.

Biased trapping issue on weighted hierarchical networks

Indian Academy of Sciences (India)

archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

CTAB-Assisted Hydrothermal Synthesis of WO3 Hierarchical Porous Structures and Investigation of Their Sensing Properties

Directory of Open Access Journals (Sweden)

Dan Meng

2015-01-01

Full Text Available WO3 hierarchical porous structures were successfully synthesized via cetyltrimethylammonium bromide- (CTAB- assisted hydrothermal method. The structure and morphology were investigated using scanning electron microscope, X-ray diffractometer, transmission electron microscopy, X-ray photoelectron spectra, Brunauer-Emmett-Teller nitrogen adsorption-desorption, and thermogravimetry and differential thermal analysis. The result demonstrated that WO3 hierarchical porous structures with an orthorhombic structure were constructed by a number of nanoparticles about 50–100 nm in diameters. The H2 gas sensing measurements showed that well-defined WO3 hierarchical porous structures with a large specific surface area exhibited the higher sensitivity compared with products without CTAB at all operating temperatures. Moreover, the reversible and fast response to H2 gas and good selectivity were obtained. The results indicated that the WO3 hierarchical porous structures are promising materials for gas sensors.

From text to codings: intercoder reliability assessment in qualitative content analysis.

Science.gov (United States)

Burla, Laila; Knierim, Birte; Barth, Jurgen; Liewald, Katharina; Duetz, Margreet; Abel, Thomas

2008-01-01

High intercoder reliability (ICR) is required in qualitative content analysis for assuring quality when more than one coder is involved in data analysis. The literature is short of standardized procedures for ICR procedures in qualitative content analysis. To illustrate how ICR assessment can be used to improve codings in qualitative content analysis. Key steps of the procedure are presented, drawing on data from a qualitative study on patients' perspectives on low back pain. First, a coding scheme was developed using a comprehensive inductive and deductive approach. Second, 10 transcripts were coded independently by two researchers, and ICR was calculated. A resulting kappa value of .67 can be regarded as satisfactory to solid. Moreover, varying agreement rates helped to identify problems in the coding scheme. Low agreement rates, for instance, indicated that respective codes were defined too broadly and would need clarification. In a third step, the results of the analysis were used to improve the coding scheme, leading to consistent and high-quality results. The quantitative approach of ICR assessment is a viable instrument for quality assurance in qualitative content analysis. Kappa values and close inspection of agreement rates help to estimate and increase quality of codings. This approach facilitates good practice in coding and enhances credibility of analysis, especially when large samples are interviewed, different coders are involved, and quantitative results are presented.

Language Learning of Gifted Individuals: A Content Analysis Study

Directory of Open Access Journals (Sweden)

Beria Gokaydin

2017-11-01

Full Text Available This study aims to carry out a content analysis of the studies on language learning of gifted individuals and determine the trends in this field. Articles on language learning of gifted individuals published in the Scopus database were examined based on certain criteria including type of publication, year of publication, language, research discipline, countries of research, institutions of authors, key words, and resources. Data were analyzed with the content analysis method. Results showed that the number of studies on language learning of gifted individuals has increased throughout the years. Recommendations for further research and practices are provided.

Statistical mixture design selective extraction of compounds with antioxidant activity and total polyphenol content from Trichilia catigua.

Science.gov (United States)

Lonni, Audrey Alesandra Stinghen Garcia; Longhini, Renata; Lopes, Gisely Cristiny; de Mello, João Carlos Palazzo; Scarminio, Ieda Spacino

2012-03-16

Statistical design mixtures of water, methanol, acetone and ethanol were used to extract material from Trichilia catigua (Meliaceae) barks to study the effects of different solvents and their mixtures on its yield, total polyphenol content and antioxidant activity. The experimental results and their response surface models showed that quaternary mixtures with approximately equal proportions of all four solvents provided the highest yields, total polyphenol contents and antioxidant activities of the crude extracts followed by ternary design mixtures. Principal component and hierarchical clustering analysis of the HPLC-DAD spectra of the chromatographic peaks of 1:1:1:1 water-methanol-acetone-ethanol mixture extracts indicate the presence of cinchonains, gallic acid derivatives, natural polyphenols, flavanoids, catechins, and epicatechins. Copyright © 2011 Elsevier B.V. All rights reserved.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Enoki, Motohiro [Faculty of Business Administration, Tokyo Keizai University, Kokubunji, Tokyo 185-8502 (Japan); Ishiyama, Tomoaki [Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Kobayashi, Masakazu A. R. [Research Center for Space and Cosmic Evolution, Ehime University, Matsuyama, Ehime 790-8577 (Japan); Nagashima, Masahiro, E-mail: enokimt@tku.ac.jp [Faculty of Education, Nagasaki University, Nagasaki, Nagasaki 852-8521 (Japan)

2014-10-10

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

Analyzing Public Discourse: Using Media Content Analysis to Understand the Policy Process

Science.gov (United States)

Saraisky, Nancy Green

2016-01-01

One of the most basic and obvious sources of data for education policy analysis is text. This article discusses content analysis as an important part of the methodological toolbox for elucidating patterns and trends about education policy. Focusing specifically on media, I show how media content analysis can produce nuanced insights about the ways…

Mobile Apps for Self-Injury: A Content Analysis.

Science.gov (United States)

Vieira, Aaron M; Lewis, Stephen P

2018-05-01

A growing body of research points to the salience of the Internet and mobile material among individuals who self-injure. However, to date, no research has investigated the mobile apps related to nonsuicidal self-injury (NSSI). Such information would clarify which apps may be useful for those who self-injure while highlighting whether app-related content warrants improvement. The current study examined the content and usability of NSSI apps available on the two largest app-related platforms (Google Play and iTunes). Using content analysis, apps were examined regarding their content (e.g., presence of NSSI myths and types of coping strategies) as well as usability (e.g., app performance). Results indicate that NSSI apps have varied content, with few developed by, or affiliated with, a trusted source (e.g., university). NSSI apps tend to not propagate NSSI myths that vary with respect to the quality of coping strategies offered. They also tend to be rated favorably in terms of their usability. Overall, the present findings add to the NSSI literature and highlight several implications and avenues for future work, which are discussed.

Hierarchical structure of the energy landscape of proteins revisited by time series analysis. II. Investigation of explicit solvent effects

Science.gov (United States)

Alakent, Burak; Camurdan, Mehmet C.; Doruker, Pemra

2005-10-01

Time series analysis tools are employed on the principal modes obtained from the Cα trajectories from two independent molecular-dynamics simulations of α-amylase inhibitor (tendamistat). Fluctuations inside an energy minimum (intraminimum motions), transitions between minima (interminimum motions), and relaxations in different hierarchical energy levels are investigated and compared with those encountered in vacuum by using different sampling window sizes and intervals. The low-frequency low-indexed mode relationship, established in vacuum, is also encountered in water, which shows the reliability of the important dynamics information offered by principal components analysis in water. It has been shown that examining a short data collection period (100ps) may result in a high population of overdamped modes, while some of the low-frequency oscillations (memory: future conformations are less dependent on previous conformations due to the lowering of energy barriers in hierarchical levels of the energy landscape. In short-time dynamics (sight contradicts. However, this comes about because water enhances the transitions between minima and forces the protein to reduce its already inherent inability to maintain oscillations observed in vacuum. Some of the frequencies lower than 10cm-1 are found to be overdamped, while those higher than 20cm-1 are slightly increased. As for the long-time dynamics in water, it is found that random-walk motion is maintained for approximately 200ps (about five times of that in vacuum) in the low-indexed modes, showing the lowering of energy barriers between the higher-level minima.

Discovering hierarchical structure in normal relational data

DEFF Research Database (Denmark)

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

2014-01-01

-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

Energy flow in plate assembles by hierarchical version of finite element method

DEFF Research Database (Denmark)

Wachulec, Marcin; Kirkegaard, Poul Henning

method has been proposed. In this paper a modified hierarchical version of finite element method is used for modelling of energy flow in plate assembles. The formulation includes description of in-plane forces so that planes lying in different planes can be modelled. Two examples considered are: L......The dynamic analysis of structures in medium and high frequencies are usually focused on frequency and spatial averages of energy of components, and not the displacement/velocity fields. This is especially true for structure-borne noise modelling. For the analysis of complicated structures...... the finite element method has been used to study the energy flow. The finite element method proved its usefulness despite the computational expense. Therefore studies have been conducted in order to simplify and reduce the computations required. Among others, the use of hierarchical version of finite element...

Fanpage metrics analysis. "Study on content engagement"

Science.gov (United States)

Rahman, Zoha; Suberamanian, Kumaran; Zanuddin, Hasmah Binti; Moghavvemi, Sedigheh; Nasir, Mohd Hairul Nizam Bin Md

2016-08-01

Social Media is now determined as an excellent communicative tool to connect directly with consumers. One of the most significant ways to connect with the consumers through these Social Networking Sites (SNS) is to create a facebook fanpage with brand contents and to place different posts periodically on these fanpages. In measuring social networking sites' effectiveness, corporate houses are now analyzing metrics in terms of calculating engagement rate, number of comments/share and likings in fanpages. So now, it is very important for the marketers to know the effectiveness of different contents or posts of fanpages in order to increase the fan responsiveness and engagement rate in the fan pages. In the study the authors have analyzed total 1834 brand posts from 17 international brands of Electronics companies. Data of 9 months (From December 2014 to August 2015) have been collected for analyses, which were available online in the Brand' fan pages. An econometrics analysis is conducted using Eviews 9, to determine the impact of different contents on fanpage engagement. The study picked the four most frequently posted content to determine their impact on PTA (people Talking About) metrics and Fanpage engagement activities.

Road Network Selection Based on Road Hierarchical Structure Control

Directory of Open Access Journals (Sweden)

HE Haiwei

2015-04-01

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

A study of undue pain and surfing: using hierarchical criteria to assess website quality.

Science.gov (United States)

Lorence, Daniel; Abraham, Joanna

2008-09-01

In studies of web-based consumer health information, scant attention has been paid to the selective development of differential methodologies for website quality evaluation, or to selective grouping and analysis of specific ;domains of uncertainty' in healthcare. Our objective is to introduce a more refined model for website evaluation, and illustrate its application using assessment of websites within an area of ongoing medical uncertainty, back pain. In this exploratory technology assessment, we suggest a model for assessing these ;domains of uncertainty' within healthcare, using qualitative assessment of websites and hierarchical concepts. Using such a hierarchy of quality criteria, we review medical information provided by the most frequently accessed websites related to back pain. Websites are evaluated using standardized criteria, with results rated from the viewpoint of the consumer. Results show that standardization of quality rating across subjective content, and between commercial and niche search results, can provide a consumer-friendly dimension to health information.

Hierarchically Structured Electrospun Fibers

Directory of Open Access Journals (Sweden)

Nicole E. Zander

2013-01-01

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

Analysis of Content Shared in Online Cancer Communities: Systematic Review.

Science.gov (United States)

van Eenbergen, Mies C; van de Poll-Franse, Lonneke V; Krahmer, Emiel; Verberne, Suzan; Mols, Floortje

2018-04-03

The content that cancer patients and their relatives (ie, posters) share in online cancer communities has been researched in various ways. In the past decade, researchers have used automated analysis methods in addition to manual coding methods. Patients, providers, researchers, and health care professionals can learn from experienced patients, provided that their experience is findable. The aim of this study was to systematically review all relevant literature that analyzes user-generated content shared within online cancer communities. We reviewed the quality of available research and the kind of content that posters share with each other on the internet. A computerized literature search was performed via PubMed (MEDLINE), PsycINFO (5 and 4 stars), Cochrane Central Register of Controlled Trials, and ScienceDirect. The last search was conducted in July 2017. Papers were selected if they included the following terms: (cancer patient) and (support group or health communities) and (online or internet). We selected 27 papers and then subjected them to a 14-item quality checklist independently scored by 2 investigators. The methodological quality of the selected studies varied: 16 were of high quality and 11 were of adequate quality. Of those 27 studies, 15 were manually coded, 7 automated, and 5 used a combination of methods. The best results can be seen in the papers that combined both analytical methods. The number of analyzed posts ranged from 200 to 1,500,000; the number of analyzed posters ranged from 75 to 90,000. The studies analyzing large numbers of posts mainly related to breast cancer, whereas those analyzing small numbers were related to other types of cancers. A total of 12 studies involved some or entirely automatic analysis of the user-generated content. All the authors referred to two main content categories: informational support and emotional support. In all, 15 studies reported only on the content, 6 studies explicitly reported on content and social

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

Hierarchical Neural Regression Models for Customer Churn Prediction

Directory of Open Access Journals (Sweden)

Golshan Mohammadi

2013-01-01

Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

Hierarchical clustering analysis of blood plasma lipidomics profiles from mono- and dizygotic twin families

NARCIS (Netherlands)

Draisma, H.H.; Reijmers, T.H.; Meulman, J.J.; Greef, J. van der; Hankemeier, T.; Boomsma, D.I.

2013-01-01

Twin and family studies are typically used to elucidate the relative contribution of genetic and environmental variation to phenotypic variation. Here, we apply a quantitative genetic method based on hierarchical clustering, to blood plasma lipidomics data obtained in a healthy cohort consisting of

Application of summative content analysis to a postal questionnaire.

Science.gov (United States)

Griffiths, Thomas Howard

2016-01-01

Content analysis of replies to closed questions in questionnaires can be undertaken to understand remarks that may explain the responses, provide illustrative examples of issues raised in the questionnaire, define new issues or issues of importance that were not covered in the questionnaire and inform the design of new questions in future surveys. To discuss the usefulness of summative content analysis to free text in postal questionnaires. Content analysis provides useful comparative insights between two respondent groups in the case example provided. Five themes emerged: poor understanding of the concept of 'patient lateral transfer work technique' and the direct instrument nursing observation (DINO) instrument's key directions; outcomes of patient transfer; positive responses; manual handling risk; and poor translation into English of DINO. Respondents need an opportunity to clarify their responses to questionnaires using free text, to provide insight into their understanding of the question being asked, understanding of the concept or construct being discussed, and data triangulation through the confirmation of item responses and free-text comments. Responses to questions in a postal questionnaire and the opportunity for free-text commentary by respondents enable the identification of hidden meanings behind tickbox responses to questions.

Content Analysis as a Foundation for Programmatic Research in Communication

OpenAIRE

Slater, Michael D.

2013-01-01

Previous arguments that content analyses provide the descriptive foundation for media effects research (McLeod & Reeves, 1980) are extended to include that content analyses can provide a sound and useful foundation for programmatic research by individual communication scientists. I discuss examples from my own work and from that of colleagues in communication and related disciplines. Use of messages sampled and coded in a content analysis in combination with survey data sets or as stimuli in ...

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2018-04-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2017-08-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Nitrogen-enriched hierarchically porous carbons prepared from polybenzoxazine for high-performance supercapacitors.

Science.gov (United States)

Wan, Liu; Wang, Jianlong; Xie, Lijing; Sun, Yahui; Li, Kaixi

2014-09-10

Nitrogen-enriched hierarchically porous carbons (HPCs) were synthesized from a novel nitrile-functionalized benzoxazine based on benzoxazine chemistry using a soft-templating method and a potassium hydroxide (KOH) chemical activation method and used as electrode materials for supercapacitors. The textural and chemical properties could be easily tuned by adding a soft template and changing the activation temperature. The introduction of the soft-templating agent (surfactant F127) resulted in the formation of mesopores, which facilitated fast ionic diffusion and reduced the internal resistance. The micropores of HPCs were extensively developed by KOH activation to provide large electrochemical double-layer capacitance. As the activation temperature increased from 600 to 800 °C, the specific surface area of nitrogen-enriched carbons increased dramatically, micropores were enlarged, and more meso/macropores were developed, but the nitrogen and oxygen content decreased, which affected the electrochemical performance. The sample HPC-800 activated at 800 °C possesses a high specific surface area (1555.4 m(2) g(-1)), high oxygen (10.61 wt %) and nitrogen (3.64 wt %) contents, a hierarchical pore structure, a high graphitization degree, and good electrical conductivity. It shows great pseudocapacitance and the largest specific capacitance of 641.6 F g(-1) at a current density of 1 A g(-1) in a 6 mol L(-1) KOH aqueous electrolyte when measured in a three-electrode system. Furthermore, the HPC-800 electrode exhibits excellent rate capability (443.0 F g(-1) remained at 40 A g(-1)) and good cycling stability (94.3% capacitance retention over 5000 cycles).

Bayesian hierarchical model for large-scale covariance matrix estimation.

Science.gov (United States)

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

Genetic Analysis of Reduced γ-Tocopherol Content in Ethiopian Mustard Seeds.

Science.gov (United States)

García-Navarro, Elena; Fernández-Martínez, José M; Pérez-Vich, Begoña; Velasco, Leonardo

2016-01-01

Ethiopian mustard (Brassica carinata A. Braun) line BCT-6, with reduced γ-tocopherol content in the seeds, has been previously developed. The objective of this research was to conduct a genetic analysis of seed tocopherols in this line. BCT-6 was crossed with the conventional line C-101 and the F1, F2, and BC plant generations were analyzed. Generation mean analysis using individual scaling tests indicated that reduced γ-tocopherol content fitted an additive-dominant genetic model with predominance of additive effects and absence of epistatic interactions. This was confirmed through a joint scaling test and additional testing of the goodness of fit of the model. Conversely, epistatic interactions were identified for total tocopherol content. Estimation of the minimum number of genes suggested that both γ- and total tocopherol content may be controlled by two genes. A positive correlation between total tocopherol content and the proportion of γ-tocopherol was identified in the F2 generation. Additional research on the feasibility of developing germplasm with high tocopherol content and reduced concentration of γ-tocopherol is required.

Genetic Analysis of Reduced γ-Tocopherol Content in Ethiopian Mustard Seeds

Directory of Open Access Journals (Sweden)

Elena García-Navarro

2016-01-01

Full Text Available Ethiopian mustard (Brassica carinata A. Braun line BCT-6, with reduced γ-tocopherol content in the seeds, has been previously developed. The objective of this research was to conduct a genetic analysis of seed tocopherols in this line. BCT-6 was crossed with the conventional line C-101 and the F1, F2, and BC plant generations were analyzed. Generation mean analysis using individual scaling tests indicated that reduced γ-tocopherol content fitted an additive-dominant genetic model with predominance of additive effects and absence of epistatic interactions. This was confirmed through a joint scaling test and additional testing of the goodness of fit of the model. Conversely, epistatic interactions were identified for total tocopherol content. Estimation of the minimum number of genes suggested that both γ- and total tocopherol content may be controlled by two genes. A positive correlation between total tocopherol content and the proportion of γ-tocopherol was identified in the F2 generation. Additional research on the feasibility of developing germplasm with high tocopherol content and reduced concentration of γ-tocopherol is required.

Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

DEFF Research Database (Denmark)

He, W.; Min, D.D.; Zhang, X.D.

2014-01-01

Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...... and products of catalytic reactions can freely diffuse through open mesopores (2–40 nm). The formation mechanism of hierarchically structured porous bioactive glasses, the immobilization mechanism of enzyme and the catalysis mechanism of immobilized enzyme are then discussed. The novel nanostructure...

Hierarchical modelling for the environmental sciences statistical methods and applications

CERN Document Server

Clark, James S

2006-01-01

New statistical tools are changing the way in which scientists analyze and interpret data and models. Hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide a consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complicated, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences.

On the use of mesophase pitch for the preparation of hierarchical porous carbon monoliths by nanocasting

Directory of Open Access Journals (Sweden)

Philipp Adelhelm, Karin Cabrera and Bernd M Smarsly

2012-01-01

Full Text Available A detailed study is given on the synthesis of a hierarchical porous carbon, possessing both meso- and macropores, using a mesophase pitch (MP as the carbon precursor. This carbon material is prepared by the nanocasting approach involving the replication of a porous silica monolith (hard templating. While this carbon material has already been tested in energy storage applications, various detailed aspects of its formation and structure are addressed in this study. Scanning electron microscopy (SEM, Hg porosimetry and N2 physisorption are used to characterize the morphology and porosity of the carbon replica. A novel approach for the detailed analysis of wide-angle x-ray scattering (WAXS from non-graphitic carbons is applied to quantitatively compare the graphene microstructures of carbons prepared using MP and furfuryl alcohol (FA. This WAXS analysis underlines the importance of the carbon precursor in the synthesis of templated porous carbon materials via the nanocasting route. Our study demonstrates that a mesophase pitch is a superior precursor whenever a high-purity, low-micropore-content and well-developed graphene structure is desired.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

Science.gov (United States)

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Three Ways to Link Merge with Hierarchical Concept-Combination

Directory of Open Access Journals (Sweden)

Chris Thornton

2016-11-01

Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

TechTrends 2010-2015: A Content Analysis

Science.gov (United States)

Stauffer, Eric

2017-01-01

This study is a content analysis of articles published within the journal "TechTrends" from 2000 to 2015. The study reveals that the publication "TechTrends" has increased the overall number of peer reviewed original papers over the last 6 years. The author describes the proportion of these original papers per volume and…

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling.

Science.gov (United States)

Yu, Jiyang; Silva, Jose; Califano, Andrea

2016-01-15

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives. Indeed, rigorous statistical analysis of high-throughput FG screening data remains challenging, particularly when integrative analyses are used to combine multiple sh/sgRNAs targeting the same gene in the library. We use large RNAi and CRISPR repositories that are publicly available to evaluate a novel meta-analysis approach for FG screens via Bayesian hierarchical modeling, Screening Bayesian Evaluation and Analysis Method (ScreenBEAM). Results from our analysis show that the proposed strategy, which seamlessly combines all available data, robustly outperforms classical algorithms developed for microarray data sets as well as recent approaches designed for next generation sequencing technologies. Remarkably, the ScreenBEAM algorithm works well even when the quality of FG screens is relatively low, which accounts for about 80-95% of the public datasets. R package and source code are available at: https://github.com/jyyu/ScreenBEAM. ac2248@columbia.edu, jose.silva@mssm.edu, yujiyang@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Learning Hierarchical User Interest Models from Web Pages

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuum. In some sense, specific interests correspond to short-term interests, while general interests correspond to long-term interests. So this representation more really reflects the users' interests. The algorithm can automatically model a user's multiple interest domains, dynamically generate the interest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.

Hierarchical surfaces for enhanced self-cleaning applications

Science.gov (United States)

Fernández, Ariadna; Francone, Achille; Thamdrup, Lasse H.; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus; Sotomayor Torres, Clivia M.; Kehagias, Nikolaos

2017-04-01

In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets.

Inclusion of Aging in Rehabilitation Counseling Journals 2000-2012: A Content Analysis

Science.gov (United States)

Kettaneh, Amani A.; Kinyanjui, Benson; Slevin, John R.; Slevin, Barbara; Harley, Debra A.

2015-01-01

Purpose: To conduct a content analysis of the rehabilitation counseling literature to identify articles published on aging. Method: To determine the number of articles that were published on aging in rehabilitation counseling journals, a content analysis of articles from 2000 through 2012 was performed. For purposes of this review, only…

20 Years of the MENC Biennial Conference: A Content Analysis

Science.gov (United States)

Palkki, Joshua; Albert, Daniel J.; Hill, Stuart Chapman; Shaw, Ryan D.

2016-01-01

The purpose of this study was to investigate the content and intended audiences for educational sessions offered at MENC biennial conferences in order to illuminate trends and topics in professional development. The researchers performed a content analysis of each session (N?= 2,593) using program booklets from conferences between 1988 and 2008,…

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

Science.gov (United States)

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Ash contents of foodstuff samples in environmental radioactivity analysis

International Nuclear Information System (INIS)

Oikawa, Shinji; Ohta, Hiroshi; Hayano, Kazuhiko; Nonaka, Nobuhiro

2004-01-01

Statistical data of the ash content in various environmental samples obtained from an environmental radioactivity survey project commissioned by the Japanese government of Science and Technology Agency (at present Ministry of Education, Culture, Sports, Sciences and Technology) during the past 10 years are expressed for establishing a standard of ash content in environmental samples based on radioactivity analysis. The ash content for some kinds of environmental samples such as dietary food, milk, Japanese radish, spinach, fish, green tea and potato was reviewed in the light of statistical and stochastic viewpoints. For all of the samples reviewed in this paper, the coefficient of variation varied from 4.7% for milk to 36.3% for cabbage. Dietary food and milk samples were reviewed more than 1900 and 1400 samples, respectively. Especially, ash content of dietary food depended mainly on the dietary culture reflected on the period. However it showed an almost invariant distribution within 18.7% of coefficient of variation during the past 10 years. Pretreatment of environmental samples especially ashing processes are important from the viewpoint on environmental radioactivity analysis, which is one of the especial fields in analytical chemistry. Statistical reviewed data obtained in this paper may be useful for sample preparation. (author)

iSBatch: a batch-processing platform for data analysis and exploration of live-cell single-molecule microscopy images and other hierarchical datasets.

Science.gov (United States)

Caldas, Victor E A; Punter, Christiaan M; Ghodke, Harshad; Robinson, Andrew; van Oijen, Antoine M

2015-10-01

Recent technical advances have made it possible to visualize single molecules inside live cells. Microscopes with single-molecule sensitivity enable the imaging of low-abundance proteins, allowing for a quantitative characterization of molecular properties. Such data sets contain information on a wide spectrum of important molecular properties, with different aspects highlighted in different imaging strategies. The time-lapsed acquisition of images provides information on protein dynamics over long time scales, giving insight into expression dynamics and localization properties. Rapid burst imaging reveals properties of individual molecules in real-time, informing on their diffusion characteristics, binding dynamics and stoichiometries within complexes. This richness of information, however, adds significant complexity to analysis protocols. In general, large datasets of images must be collected and processed in order to produce statistically robust results and identify rare events. More importantly, as live-cell single-molecule measurements remain on the cutting edge of imaging, few protocols for analysis have been established and thus analysis strategies often need to be explored for each individual scenario. Existing analysis packages are geared towards either single-cell imaging data or in vitro single-molecule data and typically operate with highly specific algorithms developed for particular situations. Our tool, iSBatch, instead allows users to exploit the inherent flexibility of the popular open-source package ImageJ, providing a hierarchical framework in which existing plugins or custom macros may be executed over entire datasets or portions thereof. This strategy affords users freedom to explore new analysis protocols within large imaging datasets, while maintaining hierarchical relationships between experiments, samples, fields of view, cells, and individual molecules.

Hierarchical Micro-Nano Coatings by Painting

Science.gov (United States)

Kirveslahti, Anna; Korhonen, Tuulia; Suvanto, Mika; Pakkanen, Tapani A.

2016-03-01

In this paper, the wettability properties of coatings with hierarchical surface structures and low surface energy were studied. Hierarchically structured coatings were produced by using hydrophobic fumed silica nanoparticles and polytetrafluoroethylene (PTFE) microparticles as additives in polyester (PES) and polyvinyldifluoride (PVDF). These particles created hierarchical micro-nano structures on the paint surfaces and lowered or supported the already low surface energy of the paint. Two standard application techniques for paint application were employed and the presented coatings are suitable for mass production and use in large surface areas. By regulating the particle concentrations, it was possible to modify wettability properties gradually. Highly hydrophobic surfaces were achieved with the highest contact angle of 165∘. Dynamic contact angle measurements were carried out for a set of selected samples and low hysteresis was obtained. Produced coatings possessed long lasting durability in the air and in underwater conditions.

Hierarchical virtual screening approaches in small molecule drug discovery.

Science.gov (United States)

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.

Computer content analysis of schizophrenic speech: a preliminary report.

Science.gov (United States)

Tucker, G J; Rosenberg, S D

1975-06-01

Computer analysis significantly differtiated the thermatic content of the free speech of 10 schizophrenic patients from that of 10 nonschizophrenic patients and from the content of transcripts of dream material from 10 normal subjects. Schizophrenic patients used the thematic categories in factor 1 (the "schizophrenic factor") 3 times more frequently than the nonschizophrenics and 10 times more frequently than the normal subjects (p smaller than 01). In general, the language content of the schizophrenic patient mirrored an almost agitated attempt to locate oneself in time and space and to defend against internal discomfort and confusion. The authors discuss the implications of this study for future research.

A new approach for global synchronization in hierarchical scheduled real-time systems

NARCIS (Netherlands)

Behnam, M.; Nolte, T.; Bril, R.J.

2009-01-01

We present our ongoing work to improve an existing synchronization protocol SIRAP for hierarchically scheduled real-time systems. A less pessimistic schedulability analysis is presented which can make the SIRAP protocol more efficient in terms of calculated CPU resource needs. In addition and for

Content Analysis of the "Professional School Counseling" Journal: The First Ten Years

Science.gov (United States)

Falco, Lia D.; Bauman, Sheri; Sumnicht, Zachary; Engelstad, Alicia

2011-01-01

The authors conducted a content analysis of the articles published in the first 10 volumes of the "Professional School Counseling" (PSC) journal, beginning in October 1997 when "The School Counselor" merged with "Elementary School Counseling and Guidance". The analysis coded a total of 571 articles into 20 content categories. Findings address the…

Climate Change Discourse in Mass Media: Application of Computer-Assisted Content Analysis

Science.gov (United States)

Kirilenko, Andrei P.; Stepchenkova, Svetlana O.

2012-01-01

Content analysis of mass media publications has become a major scientific method used to analyze public discourse on climate change. We propose a computer-assisted content analysis method to extract prevalent themes and analyze discourse changes over an extended period in an objective and quantifiable manner. The method includes the following: (1)…

Content Analysis of a Computer-Based Faculty Activity Repository

Science.gov (United States)

Baker-Eveleth, Lori; Stone, Robert W.

2013-01-01

The research presents an analysis of faculty opinions regarding the introduction of a new computer-based faculty activity repository (FAR) in a university setting. The qualitative study employs content analysis to better understand the phenomenon underlying these faculty opinions and to augment the findings from a quantitative study. A web-based…

Hierarchically interconnected porous scaffolds for phase change materials with improved thermal conductivity and efficient solar-to-electric energy conversion.

Science.gov (United States)

Yang, Jie; Yu, Peng; Tang, Li-Sheng; Bao, Rui-Ying; Liu, Zheng-Ying; Yang, Ming-Bo; Yang, Wei

2017-11-23

An ice-templating self-assembly strategy and a vacuum impregnation method were used to fabricate polyethylene glycol (PEG)/hierarchical porous scaffold composite phase change materials (PCMs). Hierarchically interconnected porous scaffolds of boron nitride (BN), with the aid of a small amount of graphene oxide (GO), endow the composite PCMs with high thermal conductivity, excellent shape-stability and efficient solar-to-electric energy conversion. The formation of a three-dimensional (3D) thermally conductive pathway in the composites contributes to improving the thermal conductivity up to 2.36 W m -1 K -1 at a relatively low content of BN (ca. 23 wt%). This work provides a route for thermally conductive and shape-stabilized composite PCMs used as energy storage materials.

CONTENT ANALYSIS OF HOTEL WEBSITES: CASE STUDY OF CROATIA

OpenAIRE

Suzana Markovic; Sanja Raspor; Tomislav Car; Jelena Komsic

2012-01-01

In the competitive hotel industry the content of hotel websites has an important role in achieving and maintaining business success and profitability. The purpose of this study is to analyze the websites of a selected group of hotels (three, four and five star) by applying content analysis by six dimensions (contact information, information about facilities, reservations and the surrounding area, as well as communication with customers and web-site functionality) and 22 characteristics. The a...

Sight-Singing Pedagogy: A Content Analysis of Choral Methods Textbooks

Science.gov (United States)

Floyd, Eva G.; Haning, Marshall A.

2015-01-01

The purpose of this study was to examine the sight-singing pedagogy content of choral methods textbooks, with the intent of determining what elements of sight-singing pedagogy are most commonly included in these resources. A content analysis was conducted to analyze information related to sight-singing pedagogy in 10 textbooks that are commonly…

Multistep Hybrid Extragradient Method for Triple Hierarchical Variational Inequalities

Directory of Open Access Journals (Sweden)

Zhao-Rong Kong

2013-01-01

Full Text Available We consider a triple hierarchical variational inequality problem (THVIP, that is, a variational inequality problem defined over the set of solutions of another variational inequality problem which is defined over the intersection of the fixed point set of a strict pseudocontractive mapping and the solution set of the classical variational inequality problem. Moreover, we propose a multistep hybrid extragradient method to compute the approximate solutions of the THVIP and present the convergence analysis of the sequence generated by the proposed method. We also derive a solution method for solving a system of hierarchical variational inequalities (SHVI, that is, a system of variational inequalities defined over the intersection of the fixed point set of a strict pseudocontractive mapping and the solution set of the classical variational inequality problem. Under very mild conditions, it is proven that the sequence generated by the proposed method converges strongly to a unique solution of the SHVI.

Delineating the structure of normal and abnormal personality: an integrative hierarchical approach.

Science.gov (United States)

Markon, Kristian E; Krueger, Robert F; Watson, David

2005-01-01

Increasing evidence indicates that normal and abnormal personality can be treated within a single structural framework. However, identification of a single integrated structure of normal and abnormal personality has remained elusive. Here, a constructive replication approach was used to delineate an integrative hierarchical account of the structure of normal and abnormal personality. This hierarchical structure, which integrates many Big Trait models proposed in the literature, replicated across a meta-analysis as well as an empirical study, and across samples of participants as well as measures. The proposed structure resembles previously suggested accounts of personality hierarchy and provides insight into the nature of personality hierarchy more generally. Potential directions for future research on personality and psychopathology are discussed.

Delineating the Structure of Normal and Abnormal Personality: An Integrative Hierarchical Approach

Science.gov (United States)

Markon, Kristian E.; Krueger, Robert F.; Watson, David

2008-01-01

Increasing evidence indicates that normal and abnormal personality can be treated within a single structural framework. However, identification of a single integrated structure of normal and abnormal personality has remained elusive. Here, a constructive replication approach was used to delineate an integrative hierarchical account of the structure of normal and abnormal personality. This hierarchical structure, which integrates many Big Trait models proposed in the literature, replicated across a meta-analysis as well as an empirical study, and across samples of participants as well as measures. The proposed structure resembles previously suggested accounts of personality hierarchy and provides insight into the nature of personality hierarchy more generally. Potential directions for future research on personality and psychopathology are discussed. PMID:15631580

Multivariate analysis of the effects of soil parameters and environmental factors on the flavonoid content of leaves of Passiflora incarnata L., Passifloraceae

Directory of Open Access Journals (Sweden)

Maria Célia H. Reimberg

Full Text Available The aim of the present study was to evaluate the effect of soil characteristics (pH, macro- and micro-nutrients, environmental factors (temperature, humidity, period of the year and time of day of collection and meteorological conditions (rain, sun, cloud and cloud/rain on the flavonoid content of leaves of Passiflora incarnata L., Passifloraceae. The total flavonoid contents of leaf samples harvested from plants cultivated or collected under different conditions were quantified by high-performance liquid chromatography with ultraviolet detection (HPLC-UV/PAD. Chemometric treatment of the data by principal component (PCA and hierarchic cluster analyses (HCA showed that the samples did not present a specific classification in relation to the environmental and soil variables studied, and that the environmental variables were not significant in describing the data set. However, the levels of the elements Fe, B and Cu present in the soil showed an inverse correlation with the total flavonoid contents of the leaves of P. incarnata.

[Analysis of spectral features based on water content of desert vegetation].

Science.gov (United States)

Zhao, Zhao; Li, Xia; Yin, Ye-biao; Tang, Jin; Zhou, Sheng-bin

2010-09-01

By using HR-768 field-portable spectroradiometer made by the Spectra Vista Corporation (SVC) of America, the hyper-spectral data of nine types of desert plants were measured, and the water content of corresponding vegetation was determined by roasting in lab. The continuum of measured hyperspectral data was removed by using ENVI, and the relationship between the water content of vegetation and the reflectance spectrum was analyzed by using correlation coefficient method. The result shows that the correlation between the bands from 978 to 1030 nm and water content of vegetation is weak while it is better for the bands from 1133 to 1266 nm. The bands from 1374 to 1534 nm are the characteristic bands because of the correlation between them and water content is the best. By using cluster analysis and according to the water content, the vegetation could be marked off into three grades: high (>70%), medium (50%-70%) and low (<50%). The research reveals the relationship between water content of desert vegetation and hyperspectral data, and provides basis for the analysis of area in desert and the monitoring of desert vegetation by using remote sensing data.

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-01-01

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

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-12-05

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

Non-Hierarchical Clustering as a method to analyse an open-ended ...

African Journals Online (AJOL)

We show that the use of non-hierarchical analysis allows us to interpret the reasoning of students solving different mathematical problems using Algebra, and to separate them into different groups, that can be recognised and characterised by common traits in their answers, without any prior knowledge on the part of the ...

Hierarchical surfaces for enhanced self-cleaning applications

International Nuclear Information System (INIS)

Fernández, Ariadna; Francone, Achille; Sotomayor Torres, Clivia M; Kehagias, Nikolaos; Thamdrup, Lasse H; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus

2017-01-01

In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets. (paper)

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

Directory of Open Access Journals (Sweden)

Hyeon-Ae eJeon

2014-11-01

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

Profiling Chilean Suicide Note-Writers through Content Analysis

Directory of Open Access Journals (Sweden)

Francisco Ceballos-Espinoza

2016-09-01

Full Text Available Suicides account for 2000 deaths in Chile each year. With a suicide rate of 11.3, it is classified as a country with high suicide risk. Aims: to identify personality and cognitive characteristics of the group of Chilean suicides that left suicide notes, through a content analysis. Methods: descriptive field study with an ex post facto design. All suicides registered between 2010 and 2012 by the Investigations Police of Chile were analyzed, obtaining 203 suicide notes from 96 cases. The Darbonne categories for content analysis were used with the inter-judge method. Results: The mean age of the suicides was 44.2 (SD = 18.53. Most of the notes were addressed to family members (51.7%. The most expressed reasons were marital- or interpersonal-related (24.6%; another 23.6% expressed a lack of purpose or hopelessness (including depression, wish to die, low self-esteem. The most frequent content expressed were instructions (about money, children, and funeral. All of the notes showed logical thinking and were written with coherence and clarity. Notably 42% of the notes were marked by affections of fondness, love or dependence of others. Regarding attitudes, the most common were of escape or farewell (42.4%, followed by fatalism, hopelessness, frustration or tiredness (40%. 24 statistically significant differences were found throughout the categories of analysis, according to cohorts of age, marital status and sex. Conclusions: the findings contribute to the profiling of Chilean suicides and to the implementation of suicide prevention programs

Hierarchical Ag mesostructures for single particle SERS substrate

Energy Technology Data Exchange (ETDEWEB)

Xu, Minwei, E-mail: xuminwei@xjtu.edu.cn; Zhang, Yin

2017-01-30

Highlights: • Hierarchical Ag mesostructures with the size of 250, 360 and 500 nm are synthesized via a seed-mediated approach. • The Ag mesostructures present the tailorable size and highly roughened surfaces. • The average enhancement factors for individual Ag mesostructures were estimated to be as high as 10{sup 6}. - Abstract: Hierarchical Ag mesostructures with highly rough surface morphology have been synthesized at room temperature through a simple seed-mediated approach. Electron microscopy characterizations indicate that the obtained Ag mesostructures exhibit a textured surface morphology with the flower-like architecture. Moreover, the particle size can be tailored easily in the range of 250–500 nm. For the growth process of the hierarchical Ag mesostructures, it is believed that the self-assembly mechanism is more reasonable rather than the epitaxial overgrowth of Ag seed. The oriented attachment of nanoparticles is revealed during the formation of Ag mesostructures. Single particle surface enhanced Raman spectra (sp-SERS) of crystal violet adsorbed on the hierarchical Ag mesostructures were measured. Results reveal that the hierarchical Ag mesostructures can be highly sensitive sp-SERS substrates with good reproducibility. The average enhancement factors for individual Ag mesostructures are estimated to be about 10{sup 6}.

A hierarchical fuzzy rule-based approach to aphasia diagnosis.

Science.gov (United States)

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

2007-10-01

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

Visual hierarchical processing and lateralization of cognitive functions through domestic chicks' eyes.

Directory of Open Access Journals (Sweden)

Cinzia Chiandetti

Full Text Available Hierarchical stimuli have proven effective for investigating principles of visual organization in humans. A large body of evidence suggests that the analysis of the global forms precedes the analysis of the local forms in our species. Studies on lateralization also indicate that analytic and holistic encoding strategies are separated between the two hemispheres of the brain. This raises the question of whether precedence effects may reflect the activation of lateralized functions within the brain. Non-human animals have perceptual organization and functional lateralization that are comparable to that of humans. Here we trained the domestic chick in a concurrent discrimination task involving hierarchical stimuli. Then, we evaluated the animals for analytic and holistic encoding strategies in a series of transformational tests by relying on a monocular occlusion technique. A local precedence emerged in both the left and the right hemisphere, adding further evidence in favour of analytic processing in non-human animals.

An analysis of infiltration with moisture content distribution in a two-dimensional discretized water content domain

KAUST Repository

Yu, Han; Douglas, Craig C.

2014-01-01

On the basis of unsaturated Darcy's law, the Talbot-Ogden method provides a fast unconditional mass conservative algorithm to simulate groundwater infiltration in various unsaturated soil textures. Unlike advanced reservoir modelling methods that compute unsaturated flow in space, it only discretizes the moisture content domain into a suitable number of bins so that the vertical water movement is estimated piecewise in each bin. The dimensionality of the moisture content domain is extended from one dimensional to two dimensional in this study, which allows us to distinguish pore shapes within the same moisture content range. The vertical movement of water in the extended model imitates the infiltration phase in the Talbot-Ogden method. However, the difference in this extension is the directional redistribution, which represents the horizontal inter-bin flow and causes the water content distribution to have an effect on infiltration. Using this extension, we mathematically analyse the general relationship between infiltration and the moisture content distribution associated with wetting front depths in different bins. We show that a more negatively skewed moisture content distribution can produce a longer ponding time, whereas a higher overall flux cannot be guaranteed in this situation. It is proven on the basis of the water content probability distribution independent of soil textures. To illustrate this analysis, we also present numerical examples for both fine and coarse soil textures.

An analysis of infiltration with moisture content distribution in a two-dimensional discretized water content domain

KAUST Repository

Yu, Han

2014-06-11

On the basis of unsaturated Darcy\\'s law, the Talbot-Ogden method provides a fast unconditional mass conservative algorithm to simulate groundwater infiltration in various unsaturated soil textures. Unlike advanced reservoir modelling methods that compute unsaturated flow in space, it only discretizes the moisture content domain into a suitable number of bins so that the vertical water movement is estimated piecewise in each bin. The dimensionality of the moisture content domain is extended from one dimensional to two dimensional in this study, which allows us to distinguish pore shapes within the same moisture content range. The vertical movement of water in the extended model imitates the infiltration phase in the Talbot-Ogden method. However, the difference in this extension is the directional redistribution, which represents the horizontal inter-bin flow and causes the water content distribution to have an effect on infiltration. Using this extension, we mathematically analyse the general relationship between infiltration and the moisture content distribution associated with wetting front depths in different bins. We show that a more negatively skewed moisture content distribution can produce a longer ponding time, whereas a higher overall flux cannot be guaranteed in this situation. It is proven on the basis of the water content probability distribution independent of soil textures. To illustrate this analysis, we also present numerical examples for both fine and coarse soil textures.

Lithium battery using sulfur infiltrated in three-dimensional flower-like hierarchical porous carbon electrode

Energy Technology Data Exchange (ETDEWEB)

Moreno, Noelia; Caballero, Alvaro [Dpto.Química Inorgánica, Instituto Universitario de Investigación en Química Fina y Nanoquímica, Universidad de Córdoba, Campus de Rabanales (Spain); Morales, Julián, E-mail: iq1mopaj@uco.es [Dpto.Química Inorgánica, Instituto Universitario de Investigación en Química Fina y Nanoquímica, Universidad de Córdoba, Campus de Rabanales (Spain); Agostini, Marco [Department of Chemistry, SapienzaUniversity, P.zzale Aldo Moro 5, 00185, Rome (Italy); Hassoun, Jusef, E-mail: jusef.hassoun@unife.it [Università di Ferrara, Dipartimento di Scienze Chimiche e Farmaceutiche, Via Fossato di Mortara 17, Ferrara (Italy)

2016-09-01

Three dimensional, flower-like hierarchical porous carbon (FPC) and its CO{sub 2}-activation (AFPC) are reported as sulfur-hosting matrixes in Li/S battery. The composites are characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), nitrogen adsorption-desorption isotherms as well as by galvanostatic cycling and electrochemical impedance spectroscopy (EIS) in lithium-cell. Both samples show well defined micrometric morphology and a sulfur content as high as 66% expected to reflect into rather high practical energy density of the electrode in lithium-sulfur battery. The lithium sulfur cell using the FPC-S composite exhibits at 25 °C a moderate cycling stability with delivered capacity ranging from 1000 to about 610 mAh g{sup −1} upon 50 cycles at 100 mA g{sup −1}. The AFPC-S composite reveals increased cycling stability and delivers a capacity ranging from 1000 to 680 mAh g{sup −1}. Improved capacity is achieved by slightly increasing the temperature, as demonstrated by cycling the FPC-S at 35 °C using a current as high as 500 mA g{sup −1}. The excellent rate capability of the electrode is associated to the carbon texture and morphology that significantly lower the cell resistance, as indeed demonstrated by EIS measurement upon cycling. - Highlights: • Sulfur electrode basing on activated, flower-like hierarchical porous carbon is reported. • Defined micrometric morphology and a sulfur content as high as 66% are obtained. • Lithium sulfur cell using the composite exhibits remarkable performances. • A specific capacity of about 1000 mAh g{sup −1} is obtained at high current rate. • The resulting Li/S battery has relevant energy content.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

Science.gov (United States)

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

Hierarchical effects on target detection and conflict monitoring

Science.gov (United States)

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

Programming with Hierarchical Maps

DEFF Research Database (Denmark)

Ørbæk, Peter

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

Hierarchical remote data possession checking method based on massive cloud files

Directory of Open Access Journals (Sweden)

Ma Haifeng

2017-06-01

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

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

Energy Technology Data Exchange (ETDEWEB)

Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

Science.gov (United States)

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Hierarchical Porous Structures

Energy Technology Data Exchange (ETDEWEB)

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

2016-06-07

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

Synthesis and Characterization of Hierarchical Structured TiO2 Nanotubes and Their Photocatalytic Performance on Methyl Orange

Directory of Open Access Journals (Sweden)

Kai Liu

2015-01-01

Full Text Available Hierarchical structured TiO2 nanotubes were prepared by mechanical ball milling of highly ordered TiO2 nanotube arrays grown by electrochemical anodization of titanium foil. Scanning electron microscopy, transmission electron microscopy, X-ray diffraction, specific surface area analysis, UV-visible absorption spectroscopy, photocurrent measurement, photoluminescence spectra, electrochemical impedance spectra, and photocatalytic degradation test were applied to characterize the nanocomposites. Surface area increased as the milling time extended. After 5 h ball milling, TiO2 hierarchical nanotubes exhibited a corn-like shape and exhibited enhanced photoelectrochemical activity in comparison to commercial P25. The superior photocatalytic activity is suggested to be due to the combined advantages of high surface area of nanoparticles and rapid electron transfer as well as collection of the nanotubes in the hierarchical structure. The hierarchical structured TiO2 nanotubes could be applied into flexible applications on solar cells, sensors, and other photoelectrochemical devices.

QUALITATIVE ANALYSIS METHOD OF DETECTION OF WAX CONTENT IN GORENGAN USING SMARTPHONE

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Yulia Yulia

2018-05-01

Full Text Available Wax is one of the compounds that can be misused to be added to Gorengan, Indonesian fritter, to keep them crispy. Gorengan containing wax is difficult to identify visually, so a quick and easy method of detecting wax content is required. The purpose of this research is to develop and evaluate the analytical performance of detecting wax content in gorengan using smartphone. Gorengan sample was dissolved with hexane and then added reagent that will give discoloration followed by analysis using smartphone. Some analysis performance parameters were evaluated in terms of linearity and detection limit, qualitative analysis capability, precision, and selectivity test. The developed method was also applied in some gorengan samples. The result shows that the detection of wax content in gorengan can be conducted by using reagent consisting of NaOH, Schift, and curcumin (1 : 2 : 2. Performance analysis shows that the linearity measurement at concentration between 10% and 25% has correlation coefficient (r of 0.9537 with detection limit at concentration of 2% and precision (%RSD less than 3%. The developed method can be applied for the detection of wax content in gorengan in the market.

Design Issues and Information Contents of the Provincial Government Websites of Indonesia: A Content Analysis on Visual Messages

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Achmad Syarief

2009-07-01

Full Text Available A website is not just merely act as an object of displaying information, but it also represents a contextual medium of communication through visuals and contents. The interplay of website design elements builds up meanings that affect users beyond what previous communication practices have uncovered. Previous research acknowledges that visuals and contents have significant effects in attracting users’ attention and trust. Thus, the ability of a website to provide credible information through visuals and contents to target users is therefore plays great importance in the success of a website. However, although a considerable number of researches on website design have been performed, study in understanding the characteristics of site’s visual appearances and information contents for the purpose of promoting local investment in Indonesia has been very limited. This paper addresses visual design issues and information contents of eighteen provincial government websites of Indonesia. Through content analysis, the paper comparatively examines visual appearances, information contents, and functions of each website, in order to determine visual characteristics and contents that suit the purpose of promoting local potencies. The paper focuses on commonality, discrepancy, and pattern of contents, provide suggestions to improve the use of provincial government website design of Indonesia.

Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

Science.gov (United States)

Hou, Fujun

2016-01-01

This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

Mining Sequential Update Summarization with Hierarchical Text Analysis

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Chunyun Zhang

2016-01-01

Full Text Available The outbreak of unexpected news events such as large human accident or natural disaster brings about a new information access problem where traditional approaches fail. Mostly, news of these events shows characteristics that are early sparse and later redundant. Hence, it is very important to get updates and provide individuals with timely and important information of these incidents during their development, especially when being applied in wireless and mobile Internet of Things (IoT. In this paper, we define the problem of sequential update summarization extraction and present a new hierarchical update mining system which can broadcast with useful, new, and timely sentence-length updates about a developing event. The new system proposes a novel method, which incorporates techniques from topic-level and sentence-level summarization. To evaluate the performance of the proposed system, we apply it to the task of sequential update summarization of temporal summarization (TS track at Text Retrieval Conference (TREC 2013 to compute four measurements of the update mining system: the expected gain, expected latency gain, comprehensiveness, and latency comprehensiveness. Experimental results show that our proposed method has good performance.

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

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Kai Wang

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

Hierarchical layered and semantic-based image segmentation using ergodicity map

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Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

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

Fabrication of Superhydrophobic Surface with Controlled Wetting Property by Hierarchical Particles.

Science.gov (United States)

Xu, Jianxiong; Liu, Weiwei; Du, Jingjing; Tang, Zengmin; Xu, Lijian; Li, Na

2015-04-01

Hierarchical particles were prepared by synthetically joining appropriately functionalized polystyrene spheres of poly[styrene-co-(3-(4-vinylphenyl)pentane-2,4-dione)] (PS-co-PVPD) nanoparticles and poly(styrene-co-chloromethylstyrene) (PS-co-PCMS) microparticles. The coupling reaction of nucleophilic substitution of pendent β-diketone groups with benzyl chloride was used to form the hierarchical particles. Since the polymeric nanoparticles and microparticles were synthesized by dispersion polymerization and emulsion polymerization, respectively, both the core microparticles and the surface nanoparticles can be different size and chemical composition. By means of changing the size of the PS-co-PVPD surface nanoparticles, a series of hierarchical particles with different scale ratio of the micro/nano surface structure were successfully prepared. Moreover, by employing the PS-co-PVPD microparticles and PS-co-PCMS nanoparticles as building blocks, hierarchical particles with surface nanoaprticles of different composition were made. These as-prepared hierarchical particles were subsequently assembled on glass substrates to form particulate films. Contact angle measurement shows that superhydrophobic surfaces can be obtained and the contact angle of water on the hierarchically structured surface can be adjusted by the scale ratio of the micro/nano surface structure and surface chemical component of hierarchical particles.

Discursive Hierarchical Patterning in Law and Management Cases

Science.gov (United States)

Lung, Jane

2008-01-01

This paper investigates the differences in the discursive patterning of cases in Law and Management. It examines a corpus of 271 Law and Management cases and discusses the kind of information that these two disciplines call for and how discourses are constructed in discursive hierarchical patterns. A discursive hierarchical pattern is a model…

Hierarchical modularity in human brain functional networks

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David Meunier

2009-10-01

Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

Science.gov (United States)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

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

Bayesian nonparametric hierarchical modeling.

Science.gov (United States)

Dunson, David B

2009-04-01

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

Hierarchical species distribution models

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

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

Hierarchical silica particles by dynamic multicomponent assembly

DEFF Research Database (Denmark)

Wu, Z. W.; Hu, Q. Y.; Pang, J. B.

2005-01-01

Abstract: Aerosol-assisted assembly of mesoporous silica particles with hierarchically controllable pore structure has been prepared using cetyltrimethylammonium bromide (CTAB) and poly(propylene oxide) (PPO, H[OCH(CH3)CH2],OH) as co-templates. Addition of the hydrophobic PPO significantly...... influences the delicate hydrophilic-hydrophobic balance in the well-studied CTAB-silicate co-assembling system, resulting in various mesostructures (such as hexagonal, lamellar, and hierarchical structure). The co-assembly of CTAB, silicate clusters, and a low-molecular-weight PPO (average M-n 425) results...... in a uniform lamellar structure, while the use of a high-molecular-weight PPO (average M-n 2000), which is more hydrophobic, leads to the formation of hierarchical pore structure that contains meso-meso or meso-macro pore structure. The role of PPO additives on the mesostructure evolution in the CTAB...

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

Science.gov (United States)

Brand, John; Johnson, Aaron P.

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675

Content Analysis of Tobacco-related Twitter Posts

OpenAIRE

Mysl?n, Mark; Zhu, Shu-Hong; Conway, Michael

2013-01-01

Objective We present results of a content analysis of tobacco-related Twitter posts (tweets), focusing on tweets referencing e-cigarettes and hookah. Introduction Vast amounts of free, real-time, localizable Twitter data offer new possibilities for public health workers to identify trends and attitudes that more traditional surveillance methods may not capture, particularly in emerging areas of public health concern where reliable statistical evidence is not readily accessible. Existing appli...

Hierarchical Load Tracking Control of a Grid-connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

DEFF Research Database (Denmark)

Li, Yonghui; Wu, Qiuwei; Zhu, Haiyu

2015-01-01

efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active...... power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model......Based on the benchmark solid oxide fuel cell (SOFC) dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject...

Comparison of sodium content of workplace and homemade meals through chemical analysis and salinity measurements.

Science.gov (United States)

Shin, Eun-Kyung; Lee, Yeon-Kyung

2014-10-01

Most Koreans consume nearly 70-80% of the total sodium through their dishes. The use of a salinometer to measure salinity is recommended to help individuals control their sodium intake. The purpose of this study was to compare sodium content through chemical analysis and salinity measurement in foods served by industry foodservice operations and homemade meals. Workplace and homemade meals consumed by employees in 15 cafeterias located in 8 districts in Daegu were collected and the sodium content was measured through chemical analysis and salinity measurements and then compared. The foods were categorized into 9 types of menus with 103 workplace meals and 337 homemade meals. Workplace meals did not differ significantly in terms of sodium content per 100 g of food but had higher sodium content via chemical analysis in roasted foods per portion. Homemade meals had higher broth salt content and higher salt content by chemical analysis per 100 g of roasted foods and hard-boiled foods. One-dish workplace meals had higher salinity (P content (P content per 100 g of foods was higher in one-dish workplace meals (P content in foods and control one's sodium intake within the daily intake target as a way to promote cooking bland foods at home. However, estimated and actual measured values may differ.

Health and nutrition content claims on websites advertising infant formula available in Australia: A content analysis.

Science.gov (United States)

Berry, Nina J; Gribble, Karleen D

2017-10-01

The use of health and nutrition content claims in infant formula advertising is restricted by many governments in response to WHO policies and WHA resolutions. The purpose of this study was to determine whether such prohibited claims could be observed in Australian websites that advertise infant formula products. A comprehensive internet search was conducted to identify websites that advertise infant formula available for purchase in Australia. Content analysis was used to identify prohibited claims. The coding frame was closely aligned with the provisions of the Australian and New Zealand Food Standard Code, which prohibits these claims. The outcome measures were the presence of health claims, nutrition content claims, or references to the nutritional content of human milk. Web pages advertising 25 unique infant formula products available for purchase in Australia were identified. Every advertisement (100%) contained at least one health claim. Eighteen (72%) also contained at least one nutrition content claim. Three web pages (12%) advertising brands associated with infant formula products referenced the nutritional content of human milk. All of these claims appear in spite of national regulations prohibiting them indicating a failure of monitoring and/or enforcement. Where countries have enacted instruments to prohibit health and other claims in infant formula advertising, the marketing of infant formula must be actively monitored to be effective. © 2016 John Wiley & Sons Ltd.

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis.

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W David Walter

Full Text Available Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles, brushtail possum (Trichosurus vulpecula, and white-tailed deer (Odocoileus virginianus. Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research on M. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type. Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovis identified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis

Science.gov (United States)

Walter, W. David; Smith, Rick; Vanderklok, Mike; VerCauterren, Kurt C.

2014-01-01

Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles), brushtail possum (Trichosurus vulpecula), and white-tailed deer (Odocoileus virginianus). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research onM. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovisidentified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd

Using the DOM Tree for Content Extraction

Directory of Open Access Journals (Sweden)

David Insa

2012-10-01

Full Text Available The main information of a webpage is usually mixed between menus, advertisements, panels, and other not necessarily related information; and it is often difficult to automatically isolate this information. This is precisely the objective of content extraction, a research area of widely interest due to its many applications. Content extraction is useful not only for the final human user, but it is also frequently used as a preprocessing stage of different systems that need to extract the main content in a web document to avoid the treatment and processing of other useless information. Other interesting application where content extraction is particularly used is displaying webpages in small screens such as mobile phones or PDAs. In this work we present a new technique for content extraction that uses the DOM tree of the webpage to analyze the hierarchical relations of the elements in the webpage. Thanks to this information, the technique achieves a considerable recall and precision. Using the DOM structure for content extraction gives us the benefits of other approaches based on the syntax of the webpage (such as characters, words and tags, but it also gives us a very precise information regarding the related components in a block, thus, producing very cohesive blocks.

Hierarchical classification with a competitive evolutionary neural tree.

Science.gov (United States)

Adams, R G.; Butchart, K; Davey, N

1999-04-01

A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT offers over other hierarchical competitive networks is its ability to self determine the number, and structure, of the competitive nodes in the network, without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated heuristics. The results of network simulations are presented over a range of data sets, including Anderson's IRIS data set. The CENT network demonstrates its ability to produce a representative hierarchical structure to classify a broad range of data sets.

Goleman's Leadership styles at different hierarchical levels in medical education.

Science.gov (United States)

Saxena, Anurag; Desanghere, Loni; Stobart, Kent; Walker, Keith

2017-09-19

With current emphasis on leadership in medicine, this study explores Goleman's leadership styles of medical education leaders at different hierarchical levels and gain insight into factors that contribute to the appropriateness of practices. Forty two leaders (28 first-level with limited formal authority, eight middle-level with wider program responsibility and six senior- level with higher organizational authority) rank ordered their preferred Goleman's styles and provided comments. Eight additional senior leaders were interviewed in-depth. Differences in ranked styles within groups were determined by Friedman tests and Wilcoxon tests. Based upon style descriptions, confirmatory template analysis was used to identify Goleman's styles for each interviewed participant. Content analysis was used to identify themes that affected leadership styles. There were differences in the repertoire and preferred styles at different leadership levels. As a group, first-level leaders preferred democratic, middle-level used coaching while the senior leaders did not have one preferred style and used multiple styles. Women and men preferred democratic and coaching styles respectively. The varied use of styles reflected leadership conceptualizations, leader accountabilities, contextual adaptations, the situation and its evolution, leaders' awareness of how they themselves were situated, and personal preferences and discomfort with styles. The not uncommon use of pace-setting and commanding styles by senior leaders, who were interviewed, was linked to working with physicians and delivering quickly on outcomes. Leaders at different levels in medical education draw from a repertoire of styles. Leadership development should incorporate learning of different leadership styles, especially at first- and mid-level positions.

Direct hierarchical assembly of nanoparticles

Science.gov (United States)

Xu, Ting; Zhao, Yue; Thorkelsson, Kari

2014-07-22

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

Band structures of two dimensional solid/air hierarchical phononic crystals

Energy Technology Data Exchange (ETDEWEB)

Xu, Y.L.; Tian, X.G. [State Key Laboratory for Mechanical Structure Strength and Vibration, Xi' an Jiaotong University, Xi' an 710049 (China); Chen, C.Q., E-mail: chencq@tsinghua.edu.cn [Department of Engineering Mechanics, AML and CNMM, Tsinghua University, Beijing 100084 (China)

2012-06-15

The hierarchical phononic crystals to be considered show a two-order 'hierarchical' feature, which consists of square array arranged macroscopic periodic unit cells with each unit cell itself including four sub-units. Propagation of acoustic wave in such two dimensional solid/air phononic crystals is investigated by the finite element method (FEM) with the Bloch theory. Their band structure, wave filtering property, and the physical mechanism responsible for the broadened band gap are explored. The corresponding ordinary phononic crystal without hierarchical feature is used for comparison. Obtained results show that the solid/air hierarchical phononic crystals possess tunable outstanding band gap features, which are favorable for applications such as sound insulation and vibration attenuation.

The Authoritarian Personality in Emerging Adulthood: Longitudinal Analysis Using Standardized Scales, Observer Ratings, and Content Coding of the Life Story.

Science.gov (United States)

Peterson, Bill E; Pratt, Michael W; Olsen, Janelle R; Alisat, Susan

2016-04-01

Three different methods (a standardized scale, an observer-based Q-sort, and content coding of narratives) were used to study the continuity of authoritarianism longitudinally in emerging and young adults. Authoritarianism was assessed in a Canadian sample (N = 92) of men and women at ages 19 and 32 with Altemeyer's (1996) Right-Wing Authoritarianism (RWA) Scale. In addition, components of the authoritarian personality were assessed at age 26 through Q-sort observer methods (Block, 2008) and at age 32 through content coding of life stories. Age 19 authoritarianism predicted the Q-sort and life story measures of authoritarianism. Two hierarchical regression analyses showed that the Q-sort and life story measures of authoritarianism also predicted the RWA scale at age 32 beyond educational level and parental status, and even after the inclusion of age 19 RWA. Differences and similarities in the pattern of correlates for the Q-sort and life story measures are discussed, including the overall lack of results for authoritarian aggression. Content in narratives may be the result of emerging adult authoritarianism and may serve to maintain levels of authoritarianism in young adulthood. © 2014 Wiley Periodicals, Inc.

SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

Directory of Open Access Journals (Sweden)

KwangHee Choi

2014-10-01

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

A Case Study of Knowledge Exchange in a Hierarchical Mechanism

Directory of Open Access Journals (Sweden)

Indria Handoko

2017-04-01

Full Text Available This research investigates knowledge exchange in an organization applying hierarchical mechanisms, and the influence of social interactions on knowledge flow across different levels of analysis. The research uses a qualitative case study method of an Indonesian automotive component-making company, applying semi-structured interviews, observations, and focus groups at interorganizational, internal company, and shop floor levels. The research main finding is that in an organization applying hierarchical mechanisms, social interactions that exist at one level are able to influence interactions at other levels, and that the interactions can both facilitate and inhibit knowledge exchange across levels and boundaries. The application of any formal mechanism at interorganizational level needs to consider both the dynamics operating at social level and the potentially disparate and contradictory effects it may have if its aim is to promote knowledge flow across levels. The application of in-depth exploratory case study research contributes to the conceptualization of relationships between knowledge exchange, social interactions, and governance mechanism.

Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems

DEFF Research Database (Denmark)

Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung

2015-01-01

The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...

[Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

Science.gov (United States)

Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

2014-11-01

Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

Hierarchical Material Properties in Finite Element Analysis: The Oilfield Infrastructure Problem.

Science.gov (United States)

Weiss, C. J.; Wilson, G. A.

2017-12-01

Geophysical simulation of low-frequency electromagnetic signals within built environments such as urban centers and industrial landscapes facilities is a challenging computational problem because strong conductors (e.g., pipes, fences, rail lines, rebar, etc.) are not only highly conductive and/or magnetic relative to the surrounding geology, but they are very small in one or more of their physical length coordinates. Realistic modeling of such structures as idealized conductors has long been the standard approach; however this strategy carries with it computational burdens such as cumbersome implementation of internal boundary conditions, and limited flexibility for accommodating realistic geometries. Another standard approach is "brute force" discretization (often coupled with an equivalent medium model) whereby 100's of millions of voxels are used to represent these strong conductors, but at the cost of extreme computation times (and mesh design) for a simulation result when possible. To minimize these burdens, a new finite element scheme (Weiss, Geophysics, 2017) has been developed in which the material properties reside on a hierarchy of geometric simplicies (i.e., edges, facets and volumes) within an unstructured tetrahedral mesh. This allows thin sheet—like structures, such as subsurface fractures, to be economically represented by a connected set of triangular facets, for example, that freely conform to arbitrary "real world" geometries. The same holds thin pipe/wire-like structures, such as casings or pipelines. The hierarchical finite element scheme has been applied to problems in electro- and magnetostatics for oilfield problems where the elevated, but finite, conductivity and permeability of the steel-cased oil wells must be properly accounted for, yielding results that are otherwise unobtainable, with run times as low as a few 10s of seconds. Extension of the hierarchical finite element concept to broadband electromagnetics is presently underway, as

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

Science.gov (United States)

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

Content Analysis of Assessment Data in Marketing Education

Science.gov (United States)

Vowles, Nicole; Hutto, Alexandra; Miller, Peter Max M.

2017-01-01

This study analyzes a sample of students' writing to assess their understanding of marketing concepts in the context of a Principles of Marketing course. Content analysis of pre- and post-essays was used to assess student knowledge of marketing concepts. The data was collected in Principles of Marketing classes. and highlight that many students…

Static and dynamic friction of hierarchical surfaces.

Science.gov (United States)

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

2016-12-01

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

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

Science.gov (United States)

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

2017-11-01

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

Deep hierarchical attention network for video description

Science.gov (United States)

Li, Shuohao; Tang, Min; Zhang, Jun

2018-03-01

Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

Utilizing a Photo-Analysis Software for Content Identifying Method (CIM

Directory of Open Access Journals (Sweden)

Nejad Nasim Sahraei

2015-01-01

Full Text Available Content Identifying Methodology or (CIM was developed to measure public preferences in order to reveal the common characteristics of landscapes and aspects of underlying perceptions including the individual's reactions to content and spatial configuration, therefore, it can assist with the identification of factors that influenced preference. Regarding the analysis of landscape photographs through CIM, there are several studies utilizing image analysis software, such as Adobe Photoshop, in order to identify the physical contents in the scenes. This study attempts to evaluate public’s ‘preferences for aesthetic qualities of pedestrian bridges in urban areas through a photo-questionnaire survey, in which respondents evaluated images of pedestrian bridges in urban areas. Two groups of images were evaluated as the most and least preferred scenes that concern the highest and lowest mean scores respectively. These two groups were analyzed by CIM and also evaluated based on the respondent’s description of each group to reveal the pattern of preferences and the factors that may affect them. Digimizer Software was employed to triangulate the two approaches and to determine the role of these factors on people’s preferences. This study attempts to introduce the useful software for image analysis which can measure the physical contents and also their spatial organization in the scenes. According to the findings, it is revealed that Digimizer could be a useful tool in CIM approaches through preference studies that utilizes photographs in place of the actual landscape in order to determine the most important factors in public preferences for pedestrian bridges in urban areas.

Content Analysis as a Foundation for Programmatic Research in Communication.

Science.gov (United States)

Slater, Michael D

2013-06-01

Previous arguments that content analyses provide the descriptive foundation for media effects research (McLeod & Reeves, 1980) are extended to include that content analyses can provide a sound and useful foundation for programmatic research by individual communication scientists. I discuss examples from my own work and from that of colleagues in communication and related disciplines. Use of messages sampled and coded in a content analysis in combination with survey data sets or as stimuli in experiments are highlighted. The particular potential for employing larger numbers of randomly sampled messages in experimental designs, and, with use of appropriate statistical methods, being able to generalize to populations of messages, is described.

Reliability in content analysis: The case of semantic feature norms classification.

Science.gov (United States)

Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

2017-12-01

Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

The construction of hierarchical structure on Ti substrate with superior osteogenic activity and intrinsic antibacterial capability

Science.gov (United States)

Huang, Ying; Zha, Guangyu; Luo, Qiaojie; Zhang, Jianxiang; Zhang, Feng; Li, Xiaohui; Zhao, Shifang; Zhu, Weipu; Li, Xiaodong

2014-01-01

The deficient osseointegration and implant-associated infections are pivotal issues for the long-term clinical success of endosteal Ti implants, while development of functional surfaces that can simultaneously overcome these problems remains highly challenging. This study aimed to fabricate sophisticated Ti implant surface with both osteogenic inducing activity and inherent antibacterial ability simply via tailoring surface topographical features. Micro/submciro/nano-scale structure was constructed on Ti by three cumulative subtractive methods, including sequentially conducted sandblasting as well as primary and secondary acid etching treatment. Topographical features of this hierarchical structure can be well tuned by the time of the secondary acid treatment. Ti substrate with mere micro/submicro-scale structure (MS0-Ti) served as a control to examine the influence of hierarchical structures on surface properties and biological activities. Surface analysis indicated that all hierarchically structured surfaces possessed exactly the same surface chemistry as that of MS0-Ti, and all of them showed super-amphiphilicity, high surface free energy, and high protein adsorption capability. Biological evaluations revealed surprisingly antibacterial ability and excellent osteogenic activity for samples with optimized hierarchical structure (MS30-Ti) when compared with MS0-Ti. Consequently, for the first time, a hierarchically structured Ti surface with topography-induced inherent antibacterial capability and excellent osteogenic activity was constructed. PMID:25146099

Domains and facets: hierarchical personality assessment using the revised NEO personality inventory.

Science.gov (United States)

Costa, P T; McCrae, R R

1995-02-01

Personality traits are organized hierarchically, with narrow, specific traits combining to define broad, global factors. The Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 1992c) assesses personality at both levels, with six specific facet scales in each of five broad domains. This article describes conceptual issues in specifying facets of a domain and reports evidence on the validity of NEO-PI-R facet scales. Facet analysis-the interpretation of a scale in terms of the specific facets with which it correlates-is illustrated using alternative measures of the five-factor model and occupational scales. Finally, the hierarchical interpretation of personality profiles is discussed. Interpretation on the domain level yields a rapid understanding of the individual interpretation of specific facet scales gives a more detailed assessment.

What are hierarchical models and how do we analyze them?

Science.gov (United States)

Royle, Andy

2016-01-01

In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

Facile synthesis and photocatalytic activity of zinc oxide hierarchical microcrystals

KAUST Repository

Xu, Xinjiang

2013-04-04

ZnO microcrystals with hierarchical structure have been synthesized by a simple solvothermal approach. The microcrystals were studied by means of X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. Research on the formation mechanism of the hierarchical microstructure shows that the coordination solvent and precursor concentration have considerable influence on the size and morphology of the microstructures. A possible formation mechanism of the hierarchical structure was suggested. Furthermore, the catalytic activity of the ZnO microcrystals was studied by treating low concentration Rhodamine B (RhB) solution under UV light, and research results show the hierarchical microstructures of ZnO display high catalytic activity in photocatalysis, the catalysis process follows first-order reaction kinetics, and the apparent rate constant k = 0.03195 min-1.

Hierarchical representation and utilization of plant constitution knowledge

International Nuclear Information System (INIS)

Nishizawa, Y.; Asami, K.

1990-01-01

A method to represent and utilize plant constitution knowledge is described. A plant system is divided into many subsystems and hierarchically represented using frames. The frames include the slots of an upper-system, lower-systems and components' connections. Connections are divided into subsystems external connections and internal connections. This knowledge representation allows top-down analysis of the plant constitution and components' connectivities. The data are edited by drawing plant diagrams on a CRT and converting them into frames. The frame data area verified by checking upper-lower relationships and components' connectivities. As an example of knowledge utilization a method to find a components' connection route is described. This method prevents the combinatorial explosion of components' connections by finding rough routes in advance of detailed route analysis

Hierarchical decision making for flood risk reduction

DEFF Research Database (Denmark)

Custer, Rocco; Nishijima, Kazuyoshi

2013-01-01

. In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...

Toward a Mixed-Methods Research Approach to Content Analysis in The Digital Age: The Combined Content-Analysis Model and its Applications to Health Care Twitter Feeds

Science.gov (United States)

Hamad, Eradah O; Savundranayagam, Marie Y; Holmes, Jeffrey D; Kinsella, Elizabeth Anne

2016-01-01

Background Twitter’s 140-character microblog posts are increasingly used to access information and facilitate discussions among health care professionals and between patients with chronic conditions and their caregivers. Recently, efforts have emerged to investigate the content of health care-related posts on Twitter. This marks a new area for researchers to investigate and apply content analysis (CA). In current infodemiology, infoveillance and digital disease detection research initiatives, quantitative and qualitative Twitter data are often combined, and there are no clear guidelines for researchers to follow when collecting and evaluating Twitter-driven content. Objective The aim of this study was to identify studies on health care and social media that used Twitter feeds as a primary data source and CA as an analysis technique. We evaluated the resulting 18 studies based on a narrative review of previous methodological studies and textbooks to determine the criteria and main features of quantitative and qualitative CA. We then used the key features of CA and mixed-methods research designs to propose the combined content-analysis (CCA) model as a solid research framework for designing, conducting, and evaluating investigations of Twitter-driven content. Methods We conducted a PubMed search to collect studies published between 2010 and 2014 that used CA to analyze health care-related tweets. The PubMed search and reference list checks of selected papers identified 21 papers. We excluded 3 papers and further analyzed 18. Results Results suggest that the methods used in these studies were not purely quantitative or qualitative, and the mixed-methods design was not explicitly chosen for data collection and analysis. A solid research framework is needed for researchers who intend to analyze Twitter data through the use of CA. Conclusions We propose the CCA model as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that

Toward a Mixed-Methods Research Approach to Content Analysis in The Digital Age: The Combined Content-Analysis Model and its Applications to Health Care Twitter Feeds.

Science.gov (United States)

Hamad, Eradah O; Savundranayagam, Marie Y; Holmes, Jeffrey D; Kinsella, Elizabeth Anne; Johnson, Andrew M

2016-03-08

Twitter's 140-character microblog posts are increasingly used to access information and facilitate discussions among health care professionals and between patients with chronic conditions and their caregivers. Recently, efforts have emerged to investigate the content of health care-related posts on Twitter. This marks a new area for researchers to investigate and apply content analysis (CA). In current infodemiology, infoveillance and digital disease detection research initiatives, quantitative and qualitative Twitter data are often combined, and there are no clear guidelines for researchers to follow when collecting and evaluating Twitter-driven content. The aim of this study was to identify studies on health care and social media that used Twitter feeds as a primary data source and CA as an analysis technique. We evaluated the resulting 18 studies based on a narrative review of previous methodological studies and textbooks to determine the criteria and main features of quantitative and qualitative CA. We then used the key features of CA and mixed-methods research designs to propose the combined content-analysis (CCA) model as a solid research framework for designing, conducting, and evaluating investigations of Twitter-driven content. We conducted a PubMed search to collect studies published between 2010 and 2014 that used CA to analyze health care-related tweets. The PubMed search and reference list checks of selected papers identified 21 papers. We excluded 3 papers and further analyzed 18. Results suggest that the methods used in these studies were not purely quantitative or qualitative, and the mixed-methods design was not explicitly chosen for data collection and analysis. A solid research framework is needed for researchers who intend to analyze Twitter data through the use of CA. We propose the CCA model as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that adds rigor to health care social media

Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

Energy Technology Data Exchange (ETDEWEB)

Zhang, Dieqing [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China); Wen, Meicheng; Jiang, Bo; Li, Guisheng [The Education Ministry Key Lab of Resource Chemistry and Shanghai Key Laboratory of Rare Earth Functional Materials, Shanghai Normal University, 100 Guilin Road, Shanghai 200231 (China); Yu, Jimmy C., E-mail: jimyu@cuhk.edu.hk [Department of Chemistry and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (China)

2012-04-15

Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: Black-Right-Pointing-Pointer Ionothermal synthesis of BiOBr microspheres with hierarchical structure. Black-Right-Pointing-Pointer Efficient mass transfer and excellent light-harvesting ability. Black-Right-Pointing-Pointer Suitable for removing heavy metals and treatment of organic dyes. Black-Right-Pointing-Pointer Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

Ionothermal synthesis of hierarchical BiOBr microspheres for water treatment

International Nuclear Information System (INIS)

Zhang, Dieqing; Wen, Meicheng; Jiang, Bo; Li, Guisheng; Yu, Jimmy C.

2012-01-01

Graphical abstract: Hierarchical BiOBr microspheres were prepared from a bromine-containing ionic liquid. The material was found effective for removing heavy metals, degrading organic pollutants and killing bacteria. Highlight: ► Ionothermal synthesis of BiOBr microspheres with hierarchical structure. ► Efficient mass transfer and excellent light-harvesting ability. ► Suitable for removing heavy metals and treatment of organic dyes. ► Remarkable photocatalytic bactericidal property. - Abstract: Bismuth oxybromide (BiOBr) micropsheres with hierarchical morphologies have been fabricated via an ionothermal synthesis route. Ionic liquid acts as a unique soft material capable of promoting nucleation and in situ growth of 3D hierarchical BiOBr mesocrystals without the help of surfactants. The as-prepared BiOBr nanomaterials can effectively remove heavy metal ions and organic dyes from wastewater. They can also kill Micrococcus lylae, a Gram positive bacterium, in water under fluorescent light irradiation. Their high adaptability in water treatment may be ascribed to their hierarchical structure, allowing them high surface to volume ratio, facile species transportation and excellent light-harvesting ability.

BiOCl nanowire with hierarchical structure and its Raman features

International Nuclear Information System (INIS)

Tian Ye; Guo Chuanfei; Guo Yanjun; Wang Qi; Liu Qian

2012-01-01

BiOCl is a promising V-VI-VII-compound semiconductor with excellent optical and electrical properties, and has great potential applications in photo-catalysis, photoelectric, etc. We successfully synthesize BiOCl nanowire with a hierarchical structure by combining wet etch (top-down) with liquid phase crystal growth (bottom-up) process, opening a novel method to construct ordered bismuth-based nanostructures. The morphology and lattice structures of Bi nanowires, β-Bi 2 O 3 nanowires and BiOCl nanowires with the hierarchical structure are investigated by scanning electron microscope (SEM) and transition electron microscope (TEM). The formation mechanism of such ordered BiOCl hierarchical structure is considered to mainly originate from the highly preferred growth, which is governed by the lattice match between (1 1 0) facet of BiOCl and (2 2 0) or (0 0 2) facet of β-Bi 2 O 3 . A schematic model is also illustrated to depict the formation process of the ordered BiOCl hierarchical structure. In addition, Raman properties of the BiOCl nanowire with the hierarchical structure are investigated deeply.

The Roy Adaptation Model and Content Analysis

OpenAIRE

Fawcett, Jacqueline

2006-01-01

The purpose of this paper is to explain how the Roy Adaptation Model can be used to guide a combined qualitative and quantitative content analysis of responses to open-ended interviews questions. Responses can be categorized as adaptive or ineffective within the physiological, self-concept, role function, and interdependence modes of adaptation and then tallied to yield an adaptation score. El objetivo del presente estudio consiste en explicar de qué manera se puede utilizar el Modelo de A...

On Utmost Multiplicity of Hierarchical Stellar Systems

Directory of Open Access Journals (Sweden)

Gebrehiwot Y. M.

2016-12-01

Full Text Available According to theoretical considerations, multiplicity of hierarchical stellar systems can reach, depending on masses and orbital parameters, several hundred, while observational data confirm the existence of at most septuple (seven-component systems. In this study, we cross-match the stellar systems of very high multiplicity (six and more components in modern catalogues of visual double and multiple stars to find among them the candidates to hierarchical systems. After cross-matching the catalogues of closer binaries (eclipsing, spectroscopic, etc., some of their components were found to be binary/multiple themselves, what increases the system's degree of multiplicity. Optical pairs, known from literature or filtered by the authors, were flagged and excluded from the statistics. We compiled a list of hierarchical systems with potentially very high multiplicity that contains ten objects. Their multiplicity does not exceed 12, and we discuss a number of ways to explain the lack of extremely high multiplicity systems.

Hierarchical capillary adhesion of microcantilevers or hairs

International Nuclear Information System (INIS)

Liu Jianlin; Feng Xiqiao; Xia Re; Zhao Hongping

2007-01-01

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

Mutual Perception of USA and China based on Content-Analysis of Media

Directory of Open Access Journals (Sweden)

Farida Halmuratovna Autova

2015-12-01

Full Text Available The article evaluates mutual perception of the United States and China in the XXI century, based on content analysis of American and Chinese media. The research methodology includes both content and event analysis. To conduct content analysis we used leading weekly news magazines of US and China - “Newsweek” and “Beijing Review”. The events, limiting the time frame of analysis are Barack Obama's re-election to the second term in 2012, and the entry of Xi Jinping as the chairman of China in 2013. As a result, we have analyzed the issues of each magazine one year before and after the events respectively. Thematic areas covered by articles (politics, economy, culture, as well as stylistic coloring titles of articles are examined. Following the results of the analysis China confidently perceives itself in the international arena. In turn, the US are committed by emphasizing speed and power of the Chinese point out the negative consequences of such a jump (“growing pains”, on the challenges facing China in domestic and foreign policy, in order to create a negative image of China in the minds of American citizens.

Content-based analysis and indexing of sports video

Science.gov (United States)

Luo, Ming; Bai, Xuesheng; Xu, Guang-you

2001-12-01

An explosion of on-line image and video data in digital form is already well underway. With the exponential rise in interactive information exploration and dissemination through the World-Wide Web, the major inhibitors of rapid access to on-line video data are the management of capture and storage, and content-based intelligent search and indexing techniques. This paper proposes an approach for content-based analysis and event-based indexing of sports video. It includes a novel method to organize shots - classifying shots as close shots and far shots, an original idea of blur extent-based event detection, and an innovative local mutation-based algorithm for caption detection and retrieval. Results on extensive real TV programs demonstrate the applicability of our approach.

Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

Science.gov (United States)

Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

2017-12-01

Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream

Hierarchical periodic micro/nano-structures on nitinol and their influence on oriented endothelialization and anti-thrombosis

International Nuclear Information System (INIS)

Nozaki, Kosuke; Shinonaga, Togo; Ebe, Noriko; Horiuchi, Naohiro; Nakamura, Miho; Tsutsumi, Yusuke; Hanawa, Takao; Tsukamoto, Masahiro; Yamashita, Kimihiro; Nagai, Akiko

2015-01-01

The applications of hierarchical micro/nano-structures, which possess properties of two-scale roughness, have been studied in various fields. In this study, hierarchical periodic micro/nano-structures were fabricated on nitinol, an equiatomic Ni–Ti alloy, using a femtosecond laser for the surface modification of intravascular stents. By controlling the laser fluence, two types of surfaces were developed: periodic nano- and micro/nano-structures. Evaluation of water contact angles indicated that the nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. Endothelial cells aligned along the nano-structures on both surfaces, whereas platelets failed to adhere to the micro/nano-surface. Decorrelation between the responses of the two cell types and the results of water contact angle analysis were a result of the pinning effect. This is the first study to show the applicability of hierarchical periodic micro/nano-structures for surface modification of nitinol. - Highlights: • Hierarchical micro/nano-structures were created on nitinol using a femtosecond laser. • The nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. • Endothelial cells aligned along the nano-structures • Platelets failed to adhere to the micro/nano-surface

Hierarchical periodic micro/nano-structures on nitinol and their influence on oriented endothelialization and anti-thrombosis

Energy Technology Data Exchange (ETDEWEB)

Nozaki, Kosuke [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Shinonaga, Togo [Joining and Welding Research Institute, Osaka University, 11-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Ebe, Noriko; Horiuchi, Naohiro; Nakamura, Miho; Tsutsumi, Yusuke; Hanawa, Takao [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Tsukamoto, Masahiro [Joining and Welding Research Institute, Osaka University, 11-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Yamashita, Kimihiro [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan); Nagai, Akiko, E-mail: nag-bcr@tmd.ac.jp [Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, 2-3-10 Kanda-Surugadai, Chiyoda, Tokyo 101-0062 (Japan)

2015-12-01

The applications of hierarchical micro/nano-structures, which possess properties of two-scale roughness, have been studied in various fields. In this study, hierarchical periodic micro/nano-structures were fabricated on nitinol, an equiatomic Ni–Ti alloy, using a femtosecond laser for the surface modification of intravascular stents. By controlling the laser fluence, two types of surfaces were developed: periodic nano- and micro/nano-structures. Evaluation of water contact angles indicated that the nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. Endothelial cells aligned along the nano-structures on both surfaces, whereas platelets failed to adhere to the micro/nano-surface. Decorrelation between the responses of the two cell types and the results of water contact angle analysis were a result of the pinning effect. This is the first study to show the applicability of hierarchical periodic micro/nano-structures for surface modification of nitinol. - Highlights: • Hierarchical micro/nano-structures were created on nitinol using a femtosecond laser. • The nano-surface was hydrophilic and the micro/nano-surface was hydrophobic. • Endothelial cells aligned along the nano-structures • Platelets failed to adhere to the micro/nano-surface.

Understanding Extraordinary Architectural Experiences through Content Analysis of Written Narratives

Directory of Open Access Journals (Sweden)

Brandon Richard Ro

2015-12-01

Full Text Available This study a identifies how people describe, characterize, and communicate in written form Extraordinary Architectural Experiences (EAE, and b expands the traditional qualitative approach to architectural phenomenology by demonstrating a quantitative method to analyze written narratives. Specifically, this study reports on the content analysis of 718 personal accounts of EAEs. Using a deductive, ‘theory-driven’ approach, these narratives were read, coded, and statistically analyzed to identify storyline structure, convincing power, and the relationship between subjective and objective experiential qualities used in the story-telling process. Statistical intercoder agreement tests were conducted to verify the reliability of the interpretations to approach the hard problem of “extraordinary aesthetics” in architecture empirically. The results of this study confirm the aesthetic nature of EAE narratives (and of told experiences by showing their higher dependence on external objective content (e.g., a building’s features and location rather than its internal subjective counterpart (e.g., emotions and sensations, which makes them more outwardly focused. The strong interrelationships and intercoder agreement between the thematic realms provide a unique aesthetic construct revealing EAE narratives as memorable, embodied, emotional events mapped by the externally focused content of place, social setting, time, and building features. A majority of EAE narratives were found to possess plot-structure along with significant relationships to objective-subjective content that further grounded their storylines. This study concludes that content analysis provides not only a valid method to understand written narratives about extraordinary architectural experiences quantitatively, but also a view as to how to map the unique nature of aesthetic phenomenology empirically.

CONTENT ANALYSIS, DISCOURSE ANALYSIS, AND CONVERSATION ANALYSIS: PRELIMINARY STUDY ON CONCEPTUAL AND THEORETICAL METHODOLOGICAL DIFFERENCES

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Anderson Tiago Peixoto Gonçalves

2016-08-01

Full Text Available This theoretical essay aims to reflect on three models of text interpretation used in qualitative research, which is often confused in its concepts and methodologies (Content Analysis, Discourse Analysis, and Conversation Analysis. After the presentation of the concepts, the essay proposes a preliminary discussion on conceptual and theoretical methodological differences perceived between them. A review of the literature was performed to support the conceptual and theoretical methodological discussion. It could be verified that the models have differences related to the type of strategy used in the treatment of texts, the type of approach, and the appropriate theoretical position.

A Hierarchical Dispatch Structure for Distribution Network Pricing

OpenAIRE

Yuan, Zhao; Hesamzadeh, Mohammad Reza

2015-01-01

This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...

A new application of hierarchical cluster analysis to investigate organic peaks in bulk mass spectra obtained with an Aerodyne Aerosol Mass Spectrometer

Science.gov (United States)

Middlebrook, A. M.; Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.

2006-12-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

Characterizing the structure and content of nurse handoffs: A Sequential Conversational Analysis approach.

Science.gov (United States)

Abraham, Joanna; Kannampallil, Thomas; Brenner, Corinne; Lopez, Karen D; Almoosa, Khalid F; Patel, Bela; Patel, Vimla L

2016-02-01

Effective communication during nurse handoffs is instrumental in ensuring safe and quality patient care. Much of the prior research on nurse handoffs has utilized retrospective methods such as interviews, surveys and questionnaires. While extremely useful, an in-depth understanding of the structure and content of conversations, and the inherent relationships within the content is paramount to designing effective nurse handoff interventions. In this paper, we present a methodological framework-Sequential Conversational Analysis (SCA)-a mixed-method approach that integrates qualitative conversational analysis with quantitative sequential pattern analysis. We describe the SCA approach and provide a detailed example as a proof of concept of its use for the analysis of nurse handoff communication in a medical intensive care unit. This novel approach allows us to characterize the conversational structure, clinical content, disruptions in the conversation, and the inherently phasic nature of nurse handoff communication. The characterization of communication patterns highlights the relationships underlying the verbal content of nurse handoffs with specific emphasis on: the interactive nature of conversation, relevance of role-based (incoming, outgoing) communication requirements, clinical content focus on critical patient-related events, and discussion of pending patient management tasks. We also discuss the applicability of the SCA approach as a method for providing in-depth understanding of the dynamics of communication in other settings and domains. Copyright © 2015 Elsevier Inc. All rights reserved.

Strategic Planning to Conduct Joint Force Network Operations: A Content Analysis of NETOPS Organizations Strategic Plans

Science.gov (United States)

2007-03-01

flowing texts coding ( Denzin & Lincoln , 2000) and therefore the most appropriate methodology for this research is a content analysis. Content Analysis...Leady & Ormrod, Cresswell, Denzin & Lincoln , and Neuendorf (Leady, 2005; Denzin & Lincoln , 2000; Cresswell, 2003; Neuendorf, 2002). The steps used in...uncil Clinger Methods Denzin eneral Govern y ol Press omputers olsti, O.R. (1969). Content Analysis for the Social Sciences and

[Hierarchical structure of authors collaboration. An analysis of papers on imaging diagnosis published by hospital radiology departments in Comunidad Valenciana (1994-2001)].

Science.gov (United States)

Miguel-Dasit, A; Martí-Bonmatí, L; Sanfeliu, P; Aleixandre, R; Valderrama, J C

2005-06-01

Analyze the different contribution of hierarchical categories in the papers published by radiologists of hospitals belonging to Comunidad Valenciana along the period 1994-2001, as well as their distribution in the different journals. For the recovery of the papers sample we have designed specific search profiles for EMI and Medline databases. Hierarchical category of the authors was identified through personal interviews. We have analyzed 417 works, with 1,321 authors distributed in the following form: chief of service, 8.8%; chief of section, 12.4%; assistant physician, 50.7%, and resident, 28%. Hierarchical groupings with participation of residents were more consistent for publishing papers along all the study period (1994-2001). Higher percentage of papers (21%) corresponded to grouping. Radiología was the most productive journal (42% papers). All results were statistically significant (p Comunidad Valenciana hospitals showed an active participation in research papers published along the period 1994-2001, in collaboration with the rest of the hierarchical categories, basically with the assistant physician. Assistant physicians contributed most of papers. Chief of section and chief of department contributed fifth of papers.

A Historical Context Analysis of Changes in Content Management Ideology

National Research Council Canada - National Science Library

Lee, William, Jr

2005-01-01

.... This research will be a qualitative study using a combined approach of historical and context analysis of literary artifacts for drawing inferences to explore the evolutionary changes in content management ideology...

Psychoactive drug advertising: content analysis.

Science.gov (United States)

Mastroianni, Patrícia C; Vaz, Amanda Cristina R; Noto, Ana Regina; Galduróz, José Carlos F

2008-10-01

The goal of this study was to describe the human figures portrayed in psychoactive drug advertising in terms of gender, age, ethnic group, and social context. Content analysis for 86 new pieces of printed advertisements released in 2005 was carried out. Fisher exact test was used to analyze the association between categories. There was a preponderance of women (62.8%) who were four times more present in advertisements for antidepressants and anxyolitics than men. Most of the people shown were Caucasian (98.8%) young adults (72%). These people were pictured in leisure activities (46.5%), at home (29%), or in contact with nature (16.2%). The message conveyed was that the drugs treat routinely felt subjective symptoms of discomfort, inducing in an irrational appeal that may affect drug prescription.

Hierarchical cultural values predict success and mortality in high-stakes teams

Science.gov (United States)

Anicich, Eric M.; Swaab, Roderick I.; Galinsky, Adam D.

2015-01-01

Functional accounts of hierarchy propose that hierarchy increases group coordination and reduces conflict. In contrast, dysfunctional accounts claim that hierarchy impairs performance by preventing low-ranking team members from voicing their potentially valuable perspectives and insights. The current research presents evidence for both the functional and dysfunctional accounts of hierarchy within the same dataset. Specifically, we offer empirical evidence that hierarchical cultural values affect the outcomes of teams in high-stakes environments through group processes. Experimental data from a sample of expert mountain climbers from 27 countries confirmed that climbers expect that a hierarchical culture leads to improved team coordination among climbing teams, but impaired psychological safety and information sharing compared with an egalitarian culture. An archival analysis of 30,625 Himalayan mountain climbers from 56 countries on 5,104 expeditions found that hierarchy both elevated and killed in the Himalayas: Expeditions from more hierarchical countries had more climbers reach the summit, but also more climbers die along the way. Importantly, we established the role of group processes by showing that these effects occurred only for group, but not solo, expeditions. These findings were robust to controlling for environmental factors, risk preferences, expedition-level characteristics, country-level characteristics, and other cultural values. Overall, this research demonstrates that endorsing cultural values related to hierarchy can simultaneously improve and undermine group performance. PMID:25605883

In situ one-step synthesis of hierarchical nitrogen-doped porous carbon for high-performance supercapacitors.

Science.gov (United States)

Jeon, Ju-Won; Sharma, Ronish; Meduri, Praveen; Arey, Bruce W; Schaef, Herbert T; Lutkenhaus, Jodie L; Lemmon, John P; Thallapally, Praveen K; Nandasiri, Manjula I; McGrail, Benard Peter; Nune, Satish K

2014-05-28

A hierarchically structured nitrogen-doped porous carbon is prepared from a nitrogen-containing isoreticular metal-organic framework (IRMOF-3) using a self-sacrificial templating method. IRMOF-3 itself provides the carbon and nitrogen content as well as the porous structure. For high carbonization temperatures (950 °C), the carbonized MOF required no further purification steps, thus eliminating the need for solvents or acid. Nitrogen content and surface area are easily controlled by the carbonization temperature. The nitrogen content decreases from 7 to 3.3 at % as carbonization temperature increases from 600 to 950 °C. There is a distinct trade-off between nitrogen content, porosity, and defects in the carbon structure. Carbonized IRMOFs are evaluated as supercapacitor electrodes. For a carbonization temperature of 950 °C, the nitrogen-doped porous carbon has an exceptionally high capacitance of 239 F g(-1). In comparison, an analogous nitrogen-free carbon bears a low capacitance of 24 F g(-1), demonstrating the importance of nitrogen dopants in the charge storage process. The route is scalable in that multi-gram quantities of nitrogen-doped porous carbons are easily produced.

Hierarchical Planning Methodology for a Supply Chain Management

Directory of Open Access Journals (Sweden)

Virna ORTIZ-ARAYA

2012-01-01

Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.

Content and user-based music visual analysis

Science.gov (United States)

Guo, Xiaochun; Tang, Lei

2015-12-01

In recent years, people's ability to collect music got enhanced greatly. Many people who prefer listening music offline even stored thousands of music on their local storage or portable device. However, their ability to deal with music information has not been improved accordingly, which results in two problems. One is how to find out the favourite songs from large music dataset and satisfy different individuals. The other one is how to compose a play list quickly. To solve these problems, the authors proposed a content and user-based music visual analysis approach. We first developed a new recommendation algorithm based on the content of music and user's behaviour, which satisfy individual's preference. Then, we make use of visualization and interaction tools to illustrate the relationship between songs and help people compose a suitable play list. At the end of this paper, a survey is mentioned to show that our system is available and effective.

[Content of mineral elements of Gastrodia elata by principal components analysis].

Science.gov (United States)

Li, Jin-ling; Zhao, Zhi; Liu, Hong-chang; Luo, Chun-li; Huang, Ming-jin; Luo, Fu-lai; Wang, Hua-lei

2015-03-01

To study the content of mineral elements and the principal components in Gastrodia elata. Mineral elements were determined by ICP and the data was analyzed by SPSS. K element has the highest content-and the average content was 15.31 g x kg(-1). The average content of N element was 8.99 g x kg(-1), followed by K element. The coefficient of variation of K and N was small, but the Mn was the biggest with 51.39%. The highly significant positive correlation was found among N, P and K . Three principal components were selected by principal components analysis to evaluate the quality of G. elata. P, B, N, K, Cu, Mn, Fe and Mg were the characteristic elements of G. elata. The content of K and N elements was higher and relatively stable. The variation of Mn content was biggest. The quality of G. elata in Guizhou and Yunnan was better from the perspective of mineral elements.

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

Science.gov (United States)

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

High content analysis of phagocytic activity and cell morphology with PuntoMorph

DEFF Research Database (Denmark)

Al-Ali, Hassan; Gao, Han; Dalby-Hansen, Camilla

2017-01-01

methods for quantifying phagocytic activity in multiple dimensions including speed, accuracy, and resolution. Conclusions We provide a framework to facilitate the development of high content assays suitable for drug screening. For convenience, we implemented our algorithm in a standalone software package...... with image-based quantification of phagocytic activity. New method We present a robust algorithm and cell-based assay system for high content analysis of phagocytic activity. The method utilizes fluorescently labeled beads as a phagocytic substrate with defined physical properties. The algorithm employs...... content screening. Results We tested our assay system using microglial cultures. Our results recapitulated previous findings on the effects of microglial stimulation on cell morphology and phagocytic activity. Moreover, our cell-level analysis revealed that the two phenotypes associated with microglial...

Ultrafast Hierarchical OTDM/WDM Network

Directory of Open Access Journals (Sweden)

Hideyuki Sotobayashi

2003-12-01

Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

Content analysis in information flows

Energy Technology Data Exchange (ETDEWEB)

Grusho, Alexander A. [Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Vavilova str., 44/2, Moscow (Russian Federation); Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow (Russian Federation); Grusho, Nick A.; Timonina, Elena E. [Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Vavilova str., 44/2, Moscow (Russian Federation)

2016-06-08

The paper deals with architecture of content recognition system. To analyze the problem the stochastic model of content recognition in information flows was built. We proved that under certain conditions it is possible to solve correctly a part of the problem with probability 1, viewing a finite section of the information flow. That means that good architecture consists of two steps. The first step determines correctly certain subsets of contents, while the second step may demand much more time for true decision.

Children's Perceptions of Tests: A Content Analysis

Science.gov (United States)

Bulgan, Gokce

2018-01-01

Anxiety that students experience during test taking negatively influences their academic achievement. Understanding how students perceive tests and how they feel during test taking could help in taking effective preventive measures. Hence, the current study focused on assessing children's perceptions of tests using content analysis. The sample…

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-07

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-01

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

An Investigation of Potential Fraud in Commercial Orange Juice Products in Malaysian Market by Cluster Analysis and Principal Component Analysis

International Nuclear Information System (INIS)

Keng, S.E.; Abbas Fadhl Mubarek Al-Karkhi; Mohd Khairuddin Mohd Talib; Azhar Mat Easa; Hoong, C.L.

2015-01-01

This study was triggered by Malaysia Ministry of Health to monitor quality of commercial orange juice products sold in Malaysia market. A total of 19 orange juice samples from 14 different brands of packed orange juice products and 5 different brands of fresh orange fruit juices were analyzed for total soluble solids content, total titratable acidity, sugar composition and amino acid profiles. Hierarchical Cluster analysis (HCA) and Principal component analysis (PCA) on amino acid composition alone allowed visual discrimination between fresh squeezed orange juices and commercial packed orange juices. Suspicion of mislabel was raised in cases of miss-classification. (author)

Facile fabrication of superhydrophobic surfaces with hierarchical structures.

Science.gov (United States)

Lee, Eunyoung; Lee, Kun-Hong

2018-03-06

Hierarchical structures were fabricated on the surfaces of SUS304 plates using a one-step process of direct microwave irradiation under a carbon dioxide atmosphere. The surface nanostructures were composed of chrome-doped hematite single crystals. Superhydrophobic surfaces with a water contact angle up to 169° were obtained by chemical modification of the hierarchical structures. The samples maintained superhydrophobicity under NaCl solution up to 2 weeks.

A hierarchical modeling methodology for the definition and selection of requirements

Science.gov (United States)

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

Educational expansion and the education gradient in health: A hierarchical age-period-cohort analysis.

Science.gov (United States)

Delaruelle, Katrijn; Buffel, Veerle; Bracke, Piet

2015-11-01

Researchers have recently been investigating the temporal variation in the educational gradient in health. While there is abundant literature concerning age trajectories, theoretical knowledge about cohort differences is relatively limited. Therefore, in analogy with the life course perspective, we introduce two contrasting cohort-specific hypotheses. The diminishing health returns hypothesis predicts a decrease in educational disparities in health across cohorts. By contrast, the cohort accretion hypothesis suggests that the education-health gap will be more pronounced among younger cohorts. To shed light on this, we perform a hierarchical age-period-cohort analysis (HAPC), using data from a subsample of individuals between 25 and 85 years of age (N = 232,573) from 32 countries in the European Social Survey (six waves: 2002-2012). The analysis leads to three important conclusions. First, we observe a widening health gap between different educational levels over the life course. Second, we find that these educational differences in the age trajectories of health seem to strengthen with each successive birth cohort. However, the two age-related effects disappear when we control for employment status, household income, and family characteristics. Last, when adjusting for these mediators, we reveal evidence to support the diminishing health returns hypothesis, implying that it is primarily the direct association between education and health that decreases across cohorts. This finding raises concerns about potential barriers to education being a vehicle for empowerment and the promotion of health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

Science.gov (United States)

Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

Science.gov (United States)

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.

Issues in Athletic Administration: A Content Analysis of Syllabi from Intercollegiate Athletics Graduate Courses

Science.gov (United States)

Comeaux, Eddie; Brown, Alan; Sieben, Nicole P.

2015-01-01

This study examined courses focused on intercollegiate athletics in sport-related graduate programs (e.g., Sport Leadership, Sport Management, and Athletic/Sport Administration). A content analysis of course syllabi was used to determine the alignment of course scope and content. Analysis included course type (i.e., required or elective),…

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

Directory of Open Access Journals (Sweden)

Ma MG

2012-04-01

Full Text Available Ming-Guo MaInstitute of Biomass Chemistry and Technology, College of Materials Science and Technology, Beijing Forestry University, Beijing, People's Republic of ChinaAbstract: Hierarchically nanosized hydroxyapatite (HA with flower-like structure assembled from nanosheets consisting of nanorod building blocks was successfully synthesized by using CaCl2, NaH2PO4, and potassium sodium tartrate via a hydrothermal method at 200°C for 24 hours. The effects of heating time and heating temperature on the products were investigated. As a chelating ligand and template molecule, the potassium sodium tartrate plays a key role in the formation of hierarchically nanostructured HA. On the basis of experimental results, a possible mechanism based on soft-template and self-assembly was proposed for the formation and growth of the hierarchically nanostructured HA. Cytotoxicity experiments indicated that the hierarchically nanostructured HA had good biocompatibility. It was shown by in-vitro experiments that mesenchymal stem cells could attach to the hierarchically nanostructured HA after being cultured for 48 hours.Objective: The purpose of this study was to develop facile and effective methods for the synthesis of novel hydroxyapatite (HA with hierarchical nanostructures assembled from independent and discrete nanobuilding blocks.Methods: A simple hydrothermal approach was applied to synthesize HA by using CaCl2, NaH2PO4, and potassium sodium tartrate at 200°C for 24 hours. The cell cytotoxicity of the hierarchically nanostructured HA was tested by MTT (3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide assay.Results: HA displayed the flower-like structure assembled from nanosheets consisting of nanorod building blocks. The potassium sodium tartrate was used as a chelating ligand, inducing the formation and self-assembly of HA nanorods. The heating time and heating temperature influenced the aggregation and morphology of HA. The cell viability did

Beyond Mirrors and Windows: A Critical Content Analysis of Latinx Children's Books

Science.gov (United States)

Braden, Eliza G.; Rodriguez, Sanjuana C.

2016-01-01

This critical content analysis examines the representation of Latinx characters in 15 picture books published in 2013 and identified by Children's Cooperative Book Center (CCBC) as having significant Latinx content. The theoretical framework undergirding this study is Critical Race Theory (Ladson-Billings, 1998; Solórzano & Yosso, 2002;…

MR-AFS: a global hierarchical file-system

International Nuclear Information System (INIS)

Reuter, H.

2000-01-01

The next generation of fusion experiments will use object-oriented technology creating the need for world wide sharing of an underlying hierarchical file-system. The Andrew file system (AFS) is a well known and widely spread global distributed file-system. Multiple-resident-AFS (MR-AFS) combines the features of AFS with hierarchical storage management systems. Files in MR-AFS therefore may be migrated on secondary storage, such as roboted tape libraries. MR-AFS is in use at IPP for the current experiments and data originating from super-computer applications. Experiences and scalability issues are discussed

Implementation of Hierarchical Task Analysis for User Interface Design in Drawing Application for Early Childhood Education

Directory of Open Access Journals (Sweden)

Mira Kania Sabariah

2016-05-01

Full Text Available Draw learning in early childhood is an important lesson and full of stimulation of the process of growth and development of children which could help to train the fine motor skills. We have had a lot of applications that can be used to perform learning, including interactive learning applications. Referring to the observations that have been conducted showed that the experiences given by the applications that exist today are very diverse and have not been able to represent the model of learning and characteristics of early childhood (4-6 years. Based on the results, Hierarchical Task Analysis method generated a list of tasks that must be done in designing an user interface that represents the user experience in draw learning. Then by using the Heuristic Evaluation method the usability of the model has fulfilled a very good level of understanding and also it can be enhanced and produce a better model.

Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

Science.gov (United States)

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

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Zahra Sharafi

2017-01-01

Full Text Available Background. The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods. The ordinal logistic regression (OLR and hierarchical ordinal logistic regression (HOLR were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™ 4.0 collected from 576 healthy school children were analyzed. Results. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

Hierarchical wave functions revisited

International Nuclear Information System (INIS)

Li Dingping.

1997-11-01

We study the hierarchical wave functions on a sphere and on a torus. We simplify some wave functions on a sphere or a torus using the analytic properties of wave functions. The open question, the construction of the wave function for quasi electron excitation on a torus, is also solved in this paper. (author)

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

Science.gov (United States)

Ma, Ming-Guo

2012-01-01

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

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

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

Hierarchical control of a nuclear reactor using uncertain dynamics techniques

International Nuclear Information System (INIS)

Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.; Perez, R.B.

1988-01-01

Recent advances in the nonlinear optimal control area are opening new possibilities towards its implementation in process control. Algorithms for multivariate control, hierarchical decomposition, parameter tracking, model uncertainties actuator saturation effects and physical limits to state variables can be implemented on the basis of a consistent mathematical formulation. In this paper, good agreement is shown between a centralized and a hierarchical implementation of a controller for a hypothetical nuclear power plant subject to multiple demands. The performance of the hierarchical distributed system in the presence of localized subsystem failures is analyzed. 4 refs., 13 figs

Analytical and numerical studies of creation probabilities of hierarchical trees

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S.S. Borysov

2011-03-01

Full Text Available We consider the creation conditions of diverse hierarchical trees both analytically and numerically. A connection between the probabilities to create hierarchical levels and the probability to associate these levels into a united structure is studied. We argue that a consistent probabilistic picture requires the use of deformed algebra. Our consideration is based on the study of the main types of hierarchical trees, among which both regular and degenerate ones are studied analytically, while the creation probabilities of Fibonacci, scale-free and arbitrary trees are determined numerically.

Hierarchical drivers of reef-fish metacommunity structure.

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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

A Content Analysis of Peer Feedback in Triadic Supervision

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Avent, Janeé R.; Wahesh, Edward; Purgason, Lucy L.; Borders, L. DiAnne; Mobley, A. Keith

2015-01-01

There is limited research on the types of peer feedback exchanged during triadic supervision. Through a content analysis, the authors found that students provided feedback about counseling performance and cognitive counseling skills most often in supervision sessions. However, there were differences in the types of feedback exchanged across three…

Four Decades of JDE Interviews: a Historical Content Analysis

Science.gov (United States)

Stahl, Norman A.; Theriault, Jennifer C.; Armstrong, Sonya L.

2016-01-01

This content analysis examines the topics, trends, and issues impacting developmental education and its professionals as evaluated by interviews that have appeared in the "Journal of Developmental Education" ("JDE") between the issuance of Volume 1 through Volume 39. A total of 76 interviews were analyzed with attention to…

Content Analysis Schedule for Bilingual Education Programs: Proyecto PAL.

Science.gov (United States)

Gonzalez, Castor

This content analysis schedule for "Proyecto PAL" in San Jose, California, presents information on the history, funding, and scope of the project. Included are sociolinguistic process variables such as the native and dominant languages of students and their interaction. Information is provided on staff selection and the linguistic…

A Modified Content Analysis of Existing School Psychology Reports

Science.gov (United States)

Mallin, Barry; Schellenberg, Miriam E.; Smith, Christiane

2012-01-01

Discrepancies between our university's training program's report-writing guidelines and common practice in Manitoba could not be resolved by reference to the literature. To inform the discussion, we collected a sample of local real world school psychology reports and undertook a modified content analysis to operationally define and measure…

Fabrication of flexible hierarchical porous nitrogen-doped carbon nanofiber films for application in binder-free supercapacitors

International Nuclear Information System (INIS)

Huang, Kaibing; Yao, Yiyuan; Yang, Xiuwen; Chen, Zhenhua; Li, Min

2016-01-01

Hierarchical porous nitrogen-doped carbon nanofiber (HPNCNF) films were prepared via a simple electrospinning process, in which polyacrylonitrile and silicone surfactants were adopted as carbon source and porogen, respectively, followed by a thermal treatment. The morphology, chemical composition, and porosity of the HPNCNFs were investigated by scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy and nitrogen adsorption–desorption experiments. The as-prepared HPNCNFs with a specific surface area of 656 m"2 g"−"1, a hierarchical pore structure, and a nitrogen content of 8.1 at% showed a specific capacitance of 289 F g"−"1 in a 6 mol L"−"1 KOH aqueous solution with excellent cycle durability, making HPNCNF films a promising electrode material for a future application in supercapacitors. - Highlights: • HPNCNF films are prepared by electrospinning followed by thermal treatment. • Silicone surfactants are adopted as porogen to prepare HPNCNF films. • The HPNCNF films show a specific capacitance of 289 F g"−"1 at a current density of 0.2 A g"−"1.

Portrayals of Wundt and Titchener in Introductory Psychology Texts: A Content Analysis.

Science.gov (United States)

Zehr, David

2000-01-01

Examines the content of introductory psychology books by performing a content analysis on texts from the 1970s and 1990s to determine whether the books incorporated recent historical scholarship in discussions of Wilhelm Wundt and Edward Titchener. Finds that some texts still misrepresent the relation between Wundt and Titchener. (CMK)

Hierarchical mesosilicalite nanoformulation integrated with cisplatin exhibits target-specific efficient anticancer activity

Science.gov (United States)

Jermy, B. Rabindran; Acharya, Sadananda; Ravinayagam, Vijaya; Alghamdi, Hajer Saleh; Akhtar, Sultan; Basuwaidan, Rehab S.

2018-04-01

Hierarchically structured zeolitic ZSM-5 and meso MCM-41 interlinked domain had an impeccable use as catalysis in many applications. The aim of the study was to develop a new drug delivery nanoformulation, specifically, cisplatin/mesosilicalite using top-down approach for cancer therapy. Hierarchical mesosilicalite with variable porosity was synthesized using alkaline molar solution (0.2 and 0.7 M NaOH) and was loaded with cisplatin through equilibrium adsorption technique. Physico-chemical properties of the nanoformulation (IAUM-56—Imam Abdulrahman Bin Faisal University Mesosilicalite-56) were characterized using X-ray diffraction, surface area analysis (BET), Fourier transformed infrared spectroscopy (FT-IR), diffuse reflectance UV-Vis spectroscopy, and transmission electron microscopy. Drug release study and anticancer activity were assayed on HeLa and MCF7 cancer cells using MTT assay. X-ray diffraction pattern showed interrelated meso- and microphases, while BET analysis revealed considerable mesoporosity formation with a remodulation of isotherm hysteresis indicating the presence of hierarchical pores. FT-IR showed the presence of nanozeolitic subunits into mesostructure with a band at about 550 cm-1. IAUM-56 demonstrated high cytotoxic activity against HeLa cancer cells with an LC50 of 0.02 mg/ml, MCF7 cancer cells with an LC50 of 0.05 mg/ml, and less toxic to normal fibroblast cells with an LC50 of approximately ten times higher at 0.5 mg/ml. Overall, IAUM-56 showed a high rate of sustained release of cisplatin imparting target specific cytotoxic effect against tumor cells with at least tenfold lower toxicity on normal fibroblast cells. Our nanoformulation has the potential use in cancer therapy as a targeted drug delivery system.

Anticollusion Attack Noninteractive Security Hierarchical Key Agreement Scheme in WHMS

Directory of Open Access Journals (Sweden)

Kefei Mao

2016-01-01

Full Text Available Wireless Health Monitoring Systems (WHMS have potential to change the way of health care and bring numbers of benefits to patients, physicians, hospitals, and society. However, there are crucial barriers not only to transmit the biometric information but also to protect the privacy and security of the patients’ information. The key agreement between two entities is an essential cryptography operation to clear the barriers. In particular, the noninteractive hierarchical key agreement scheme becomes an attractive direction in WHMS because each sensor node or gateway has limited resources and power. Recently, a noninteractive hierarchical key agreement scheme has been proposed by Kim for WHMS. However, we show that Kim’s cryptographic scheme is vulnerable to the collusion attack if the physicians can be corrupted. Obviously, it is a more practical security condition. Therefore, we proposed an improved key agreement scheme against the attack. Security proof, security analysis, and experimental results demonstrate that our proposed scheme gains enhanced security and more efficiency than Kim’s previous scheme while inheriting its qualities of one-round communication and security properties.

Hierarchically structured materials for lithium batteries

International Nuclear Information System (INIS)

Xiao, Jie; Zheng, Jianming; Li, Xiaolin; Shao, Yuyan; Zhang, Ji-Guang

2013-01-01

The lithium-ion battery (LIB) is one of the most promising power sources to be deployed in electric vehicles, including solely battery powered vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. With the increasing demand for devices of high-energy densities (>500 Wh kg −1 ), new energy storage systems, such as lithium–oxygen (Li–O 2 ) batteries and other emerging systems beyond the conventional LIB, have attracted worldwide interest for both transportation and grid energy storage applications in recent years. It is well known that the electrochemical performance of these energy storage systems depends not only on the composition of the materials, but also on the structure of the electrode materials used in the batteries. Although the desired performance characteristics of batteries often have conflicting requirements with the micro/nano-structure of electrodes, hierarchically designed electrodes can be tailored to satisfy these conflicting requirements. This work will review hierarchically structured materials that have been successfully used in LIB and Li–O 2 batteries. Our goal is to elucidate (1) how to realize the full potential of energy materials through the manipulation of morphologies, and (2) how the hierarchical structure benefits the charge transport, promotes the interfacial properties and prolongs the electrode stability and battery lifetime. (paper)

Inferring hierarchical clustering structures by deterministic annealing

International Nuclear Information System (INIS)

Hofmann, T.; Buhmann, J.M.

1996-01-01

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

Optimization of Hierarchically Scheduled Heterogeneous Embedded Systems

DEFF Research Database (Denmark)

Pop, Traian; Pop, Paul; Eles, Petru

2005-01-01

We present an approach to the analysis and optimization of heterogeneous distributed embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organized in a hierarchy. In this paper, we address design problems that are characteristic to such hierarchically scheduled systems: assignment of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We present algorithms for solving these problems....... Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

Energy Technology Data Exchange (ETDEWEB)

Thornton, Peter E [ORNL; Wang, Weile [ORNL; Law, Beverly E. [Oregon State University; Nemani, Ramakrishna R [NASA Ames Research Center

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

"Textbook as a Contradictory Melting-Pot": An Analysis of Multicultural Content in Korean Textbooks

Science.gov (United States)

Cho, Youngdal; Park, Yunkyoung

2016-01-01

In this study we will observe how multicultural content is covered in elementary and secondary schools in Korea. For this purpose, a total of 52 textbooks (social studies, ethics and Korean language from third to ninth grade) were analysed using two analysis frames. The first frame is the "multicultural content analysis frame (MCAF)"…

UNCERTAINTY HANDLING IN DISASTER MANAGEMENT USING HIERARCHICAL ROUGH SET GRANULATION

Directory of Open Access Journals (Sweden)

H. Sheikhian

2015-08-01

Full Text Available Uncertainty is one of the main concerns in geospatial data analysis. It affects different parts of decision making based on such data. In this paper, a new methodology to handle uncertainty for multi-criteria decision making problems is proposed. It integrates hierarchical rough granulation and rule extraction to build an accurate classifier. Rough granulation provides information granules with a detailed quality assessment. The granules are the basis for the rule extraction in granular computing, which applies quality measures on the rules to obtain the best set of classification rules. The proposed methodology is applied to assess seismic physical vulnerability in Tehran. Six effective criteria reflecting building age, height and material, topographic slope and earthquake intensity of the North Tehran fault have been tested. The criteria were discretized and the data set was granulated using a hierarchical rough method, where the best describing granules are determined according to the quality measures. The granules are fed into the granular computing algorithm resulting in classification rules that provide the highest prediction quality. This detailed uncertainty management resulted in 84% accuracy in prediction in a training data set. It was applied next to the whole study area to obtain the seismic vulnerability map of Tehran. A sensitivity analysis proved that earthquake intensity is the most effective criterion in the seismic vulnerability assessment of Tehran.

Teaching Blended Content Analysis and Critically Vigilant Media Consumption

Science.gov (United States)

Harris, Christopher S.

2015-01-01

The semester-long activity described herein uses an integrated instructional approach to media studies to introduce students to the research method of qualitative content analysis and help them become more critically vigilant media consumers. The goal is to increase students' media literacy by guiding them in the design of an exploratory…

Trends of Science Education Research: An Automatic Content Analysis

Science.gov (United States)

Chang, Yueh-Hsia; Chang, Chun-Yen; Tseng, Yuen-Hsien

2010-01-01

This study used scientometric methods to conduct an automatic content analysis on the development trends of science education research from the published articles in the four journals of "International Journal of Science Education, Journal of Research in Science Teaching, Research in Science Education, and Science Education" from 1990 to 2007. The…

Content Analysis of Measures for Identification of Elder Abuse.

Science.gov (United States)

Sengstock, Mary C.; And Others

Measures designed to detect elder abuse lack uniformity as a result of having been designed in isolation. To develop and test a uniform index for the identification of elder abuse victims, an analysis of existing abuse identification instruments was conducted. Initially, seven elder abuse identification measures were content analyzed, resulting in…

Comparison of results of assaying and neutron activation analysis when determining gold and silver content

International Nuclear Information System (INIS)

Vaganov, P.A.; Bulnaev, A.I.; Kulikov, V.D.; Mejer, V.A.; Zakharevich, K.V.

1977-01-01

Compared are results of simultaneous determination of gold and silver content in rock samples by the methods of neutron activation analysis and assaying. Rock samples were irradiated by thermal neutron flux of 5x10 13 nxcm -2 xs -1 during 12 hours. The gold content was determined in 8-12 days after irradiation, and silver content in 40-50 days. T he gold content determination was performed by 411.8 keV γ quanta of 198 Au. To establish the silver content two analytical lines of sup(110m)Ag isomer with the energy of 657.7 and 937.4 keV were used. The sensitivity threshold of Au content determination amounts to 3x10 -6 % (or 1x10 -9 g) and that for Ag is 2x10 -40 % (using γ line with the energy of 657.7 keV). The comparison of the results of assaying and neutron-activation analysis has shown for silver a good agreement between the both methods, the coefficient of pair correlation being equal to 0.997. For gold the divergence between the methods is observed. The activation analysis provides on the average lower values of gold content

Hierarchical structure of moral stages assessed by a sorting task

NARCIS (Netherlands)

Boom, J.; Brugman, D.; Van der Heijden, P.G.M.

2001-01-01

Following criticism of Kohlberg’s theory of moral judgment, an empirical re-examination of hierarchical stage structure was desirable. Utilizing Piaget’s concept of reflective abstraction as a basis, the hierarchical stage structure was investigated using a new method. Study participants (553 Dutch

Structural Group-based Auditing of Missing Hierarchical Relationships in UMLS

Science.gov (United States)

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

2009-01-01

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

Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies

Science.gov (United States)

Kocakaplan, Yusuf; Deviren, Bayram; Keskin, Mustafa

2012-12-01

We have examined the hierarchical structures of correlations networks among Turkey’s exports and imports by currencies for the 1996-2010 periods, using the concept of a minimal spanning tree (MST) and hierarchical tree (HT) which depend on the concept of ultrametricity. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial markets. We derived a hierarchical organization and build the MSTs and HTs during the 1996-2001 and 2002-2010 periods. The reason for studying two different sub-periods, namely 1996-2001 and 2002-2010, is that the Euro (EUR) came into use in 2001, and some countries have made their exports and imports with Turkey via the EUR since 2002, and in order to test various time-windows and observe temporal evolution. We have carried out bootstrap analysis to associate a value of the statistical reliability to the links of the MSTs and HTs. We have also used the average linkage cluster analysis (ALCA) to observe the cluster structure more clearly. Moreover, we have obtained the bidimensional minimal spanning tree (BMST) due to economic trade being a bidimensional problem. From the structural topologies of these trees, we have identified different clusters of currencies according to their proximity and economic ties. Our results show that some currencies are more important within the network, due to a tighter connection with other currencies. We have also found that the obtained currencies play a key role for Turkey’s exports and imports and have important implications for the design of portfolio and investment strategies.

Minnesota urban partnership agreement national evaluation : content analysis test plan.

Science.gov (United States)

2009-11-17

This report presents the content analysis test plan for the Minnesota Urban Partnership Agreement (UPA) under the United States Department of Transportation (U.S. DOT) UPA Program. The Minnesota UPA projects focus on reducing congestion by employing ...

Non-oxidic nanoscale composites: single-crystalline titanium carbide nanocubes in hierarchical porous carbon monoliths.

Science.gov (United States)

Sonnenburg, Kirstin; Smarsly, Bernd M; Brezesinski, Torsten

2009-05-07

We report the preparation of nanoscale carbon-titanium carbide composites with carbide contents of up to 80 wt%. The synthesis yields single-crystalline TiC nanocubes 20-30 nm in diameter embedded in a hierarchical porous carbon matrix. These composites were generated in the form of cylindrical monoliths but can be produced in various shapes using modern sol-gel and nanocasting methods in conjunction with carbothermal reduction. The monolithic material is characterized by a combination of microscopy, diffraction and physisorption. Overall, the results presented in this work represent a concrete design template for the synthesis of non-oxidic nanoscale composites with high surface areas.

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

Science.gov (United States)

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

2018-03-01

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

A content analysis of thinspiration, fitspiration, and bonespiration imagery on social media.

Science.gov (United States)

Talbot, Catherine Victoria; Gavin, Jeffrey; van Steen, Tommy; Morey, Yvette

2017-01-01

On social media, images such as thinspiration, fitspiration, and bonespiration, are shared to inspire certain body ideals. Previous research has demonstrated that exposure to these groups of content is associated with increased body dissatisfaction and decreased self-esteem. It is therefore important that the bodies featured within these groups of content are more fully understood so that effective interventions and preventative measures can be informed, developed, and implemented. A content analysis was conducted on a sample of body-focussed images with the hashtags thinspiration, fitspiration, and bonespiration from three social media platforms. The analyses showed that thinspiration and bonespiration content contained more thin and objectified bodies, compared to fitspiration which featured a greater prevalence of muscles and muscular bodies. In addition, bonespiration content contained more bone protrusions and fewer muscles than thinspiration content. The findings suggest fitspiration may be a less unhealthy type of content; however, a subgroup of imagery was identified which idealised the extremely thin body type and as such this content should also be approached with caution. Future research should utilise qualitative methods to further develop understandings of the body ideals that are constructed within these groups of content and the motivations behind posting this content.

Analysis of pedagogical content knowledge (PCK) ability of science teachers in planning and reflecting on environmental pollution content

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Purwianingsih, W.; Mardiyah, A.

2018-05-01

Pedagogical Content Knowledge (PCK) is a blend of content knowledge and pedagogy knowledge, which can illustrate the ability of teachers to design and to teach a content by accessing what they knows about the material, students, curriculum and how best to teach the content. Description of PCK ability of science teachers can be accessed through an analysis of their ability to plan and reflect on learning. This study aims to provide an overview of teachers’ PCK skills on environmental pollution materials through use of Content Representation (CoRe) and Pedagogical and Professional-experience Repertoires (PaP-eRs). Descriptive method used in this study with six of science teachers on 7th class from three different schools as subject. The results show that teachers’ PCK skills in planning through CoRe and reflecting through PaP-eRs are in fairly good category. The teacher’s ability in implementing environmental pollution learning materials is in good category. However, there is still a discrepancy between planning through CoRe and the implementation of classroom learning. The teacher’s PCK is influenced by teaching experience and educational background.

Content Themes of Alcohol Advertising in U.S. Television-Latent Class Analysis.

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Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W G; Stoolmiller, Michael; Sargent, James D

2015-09-01

There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in U.S. television. Studies of alcohol ads from 2 decades ago did not identify "Partying" as a social theme. Aim of this study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Content analysis of all ads from the top 20 U.S. beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. About half of the advertisements (46%) were aired between 3 am and 8 pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed 5 content classes that exploited the "Partying," "Quality," "Sports," "Manly," and "Relax" themes. The partying class, indicative of ad messages surrounding partying, love, and sex, was the dominant theme comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. Copyright © 2015 by the Research Society on Alcoholism.

Content Themes of Alcohol Advertising in US Television — Latent Class Analysis

Science.gov (United States)

Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W.G.; Stoolmiller, Michael; Sargent, James D.

2015-01-01

Background There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in US television. Studies of alcohol ads from two decades ago did not identify “partying” as a social theme. Aim of the present study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Methods Content analysis of all ads from the top 20 US beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. Results About half of the advertisements (46%) were aired between 3am and 8pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed five content classes that exploited the “Partying”, “Quality”, “Sports”, “Manly”, and “Relax” themes. The partying class, indicative of ad messages surrounding partying, love and sex, was the dominant theme, comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. Conclusions This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. PMID:26207317

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

Energy Technology Data Exchange (ETDEWEB)

Nash, Stephen G.

2013-11-11

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

Enriched namespace to support content-aware authorization policies

International Nuclear Information System (INIS)

Ghiselli, A; Stagni, F; Magnoni, L; Riccardo, Z

2008-01-01

In the near future, data on the order of hundreds of Petabytes will be spread in multiple storage systems worldwide dispersed in, potentially, billions of replicated data items. Users, typically, are agnostic about the location of their data and they want to get access by either specifying logical names or using some lookup mechanism. A global namespace is a logical layer that allows the view of data resources independently from the physical location. Usually, the naming scheme is designed to be easily interpreted by humans and it is organized into a purely user-defined directory hierarchy. Within this model, a data resource is uniquely addressed by file name and path. Nevertheless, this hierarchical structures of logical namespace lacks adequate flexibility to manage sophisticated organization of data. In particular the implicit classification of the data item derived from the path is not enough meaningful to classify data objects when different orthogonal dimensions are considered. In this paper we expose an enriched namespace able to support a new type of data access authorization policy based on tags. The tags are organized in well-defined hierarchies providing a simple representation of the domain ontology. Only authorized users can label data resources with different tags taken from the domain tag hierarchies. In this way an overlay of classical hierarchical structure of logical namespace with faceted hierarchical tags provides a semantics classification of data entities. Authorization policies defined in respect of tags are content-aware

Enriched namespace to support content-aware authorization policies

Energy Technology Data Exchange (ETDEWEB)

Ghiselli, A; Stagni, F [INFN Ferrara, Via Saragat, 1 I44100, Ferrara (Italy); Magnoni, L; Riccardo, Z, E-mail: antonia.ghiselli@cnaf.infn.it, E-mail: luca.magnoni@cnaf.infn.it, E-mail: riccardo.zappi@cnaf.infn.it, E-mail: federico.stagni@fe.infn.it

2008-07-15

In the near future, data on the order of hundreds of Petabytes will be spread in multiple storage systems worldwide dispersed in, potentially, billions of replicated data items. Users, typically, are agnostic about the location of their data and they want to get access by either specifying logical names or using some lookup mechanism. A global namespace is a logical layer that allows the view of data resources independently from the physical location. Usually, the naming scheme is designed to be easily interpreted by humans and it is organized into a purely user-defined directory hierarchy. Within this model, a data resource is uniquely addressed by file name and path. Nevertheless, this hierarchical structures of logical namespace lacks adequate flexibility to manage sophisticated organization of data. In particular the implicit classification of the data item derived from the path is not enough meaningful to classify data objects when different orthogonal dimensions are considered. In this paper we expose an enriched namespace able to support a new type of data access authorization policy based on tags. The tags are organized in well-defined hierarchies providing a simple representation of the domain ontology. Only authorized users can label data resources with different tags taken from the domain tag hierarchies. In this way an overlay of classical hierarchical structure of logical namespace with faceted hierarchical tags provides a semantics classification of data entities. Authorization policies defined in respect of tags are content-aware.

Language Learning of Gifted Individuals: A Content Analysis Study

Science.gov (United States)

Gokaydin, Beria; Baglama, Basak; Uzunboylu, Huseyin

2017-01-01

This study aims to carry out a content analysis of the studies on language learning of gifted individuals and determine the trends in this field. Articles on language learning of gifted individuals published in the Scopus database were examined based on certain criteria including type of publication, year of publication, language, research…

Mathematical Modelling Research in Turkey: A Content Analysis Study

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Çelik, H. Coskun

2017-01-01

The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…

Organization of excitable dynamics in hierarchical biological networks.

Directory of Open Access Journals (Sweden)

Mark Müller-Linow

Full Text Available 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.