Hierarchical Group Structure Research Articles

Identifying genetic associations with MRI-derived measures via tree-guided sparse learning.

In recent imaging genetic studies, much work has been focused on regression analysis that treats large-scale single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) as association variables. To deal with the weak detection and high-throughput data problem, feature selection methods such as the least absolute shrinkage and selection operator (Lasso) are often used for selecting the most relevant SNPs associated with QTs. However, one problem of Lasso as well as many other feature selection methods for imaging genetics is that some useful prior information, i.e., the hierarchical structure among SNPs throughout the whole genome, are rarely used for designing more powerful model. In this paper, we propose to identify the associations between candidate genetic features (i.e., SNPs) and magnetic resonance imaging (MRI)-derived measures using a tree-guided sparse learning (TGSL) method. The advantage of our method is that it explicitly models the priori hierarchical grouping structure among the SNPs in the objective function for feature selection. Specifically, two kinds of hierarchical structures, i.e., group by gene and group by linkage disequilibrium (LD) clusters, are imposed as a tree-guided regularization term in our sparse learning model. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database show that our method not only achieves better predictions on the two MRI measures (i.e., left and right hippocampal formation), but also identifies the informative SNPs to guide the disease-induced interpretation compared with other reference methods.

Grouping Hierarchy and Trajectories of Pacing in Performances of Chopin’s Mazurkas

Theories of expressive timing in the performance of tonal music emphasize the role of grouping structure, whereby performers are understood to communicate the ends of groups through group-final lengthening (GFL). But this approach depends on a one-way mapping from a single grouping-structural analysis onto performed durations, denying a role for interpretive difference on the part of performers and analysts. Drawing on contour theory, this article reverses this mapping by presenting a method for recovering the hierarchical grouping structure of a performed phrase that is sensitive to the constraints of temporal perception. Groups whose durational contour segments reduce to a contour adjacency series of <+> or <–,+> are understood to be GFL-reflective. By observing which levels of time-span organization are GFL-reflective among different performances of the same phrase, unique construals of grouping structure can be attributed to different renditions.The article employs this method in order to examine different approaches to pacing in performances of two of Chopin’s mazurkas. The pieces in question present eight-measure themes in which the salience of different levels of grouping structure contrast. Through duration decisions, performers can accentuate, amend, or bypass these suggestions of contrast in pacing. By presenting an analytical method that recognizes the creative power of performance to interact with a grouping structure implied by a score, I hope to reshape the relationship between performers and analysts as a dialog about the possible structural descriptions a piece can support.

SOCIOECONOMIC STATUS AND MICROSOCIAL STRUCTURE WITHIN FEMALE HANDBALL TEAM

In a sample of 18 players, members of the senior major league handball team, the correlation between the micro structure of handball in relation to their socioeconomic status, using the sociometric procedure, was analyzed. The research results lead to the acceptance of the hypothesis that the players of the same socioeconomic status, have better mutual emotional acceptance. The hypothesis of a better mutual functional accepting players of the same socioeconomic status, may be only partially accepted, in a field of the trend of cooperation in the game, but not in relation to the selection of players with the authority of leaders or handball knowledge. Hypothesis about the hierarchical microsocial structure of groups can be fully accepted. Players are in relation to sociometric status differentiated into four levels of hierarchy, while at the top of this hierarchy, team captain. Selection of team captain by players directed by a player (“leader”), according to the functional and emotional criteria.

Understanding Through-Composition in Post-Rock, Math-Metal, and other Post-Millennial Rock Genres

Since the dawn of experimental rock’s second coming in the new millennium, experimental artists have begun distancing themselves from Top-40 artists through formal structures that eschew recapitulatory verse/chorus conventions altogether. In order to understand the correlation between genre and form more thoroughly, this paper provides a taxonomic approach to through-composition in several post-millennial experimental rock genres including post-rock, math-metal, art rock, and neo-prog. Combining the presence or absence of two salient formal parameters (hierarchical grouping structure and thematic unification) generates four possible through-composed archetypes. Representative examples from the post-millennial rock corpus are provided for each archetype, and accompanying analyses identify the specific musical elements that engender such formal divisions. Included interviews suggest that this taxonomic model is congruent with the language musicians use to describe their own compositional strategies. Throughout the article, a case is made for the substantive link between specific types of through-composed forms and the genres in which those forms regularly appear, as well as for the difference between formal designs found in post-millennial experimental rock and those found in conventional rock music.

Adaptation of Grouping Structure Analysis in GTTM to Hierarchical Segmentation of Dance Motion

In this paper, the authors propose the adaptation of the rules used in the grouping structure analysis in Lerdahl and Jackendoff's “A Generative Theory of Tonal Music (GTTM)” to dance motion analysis. The success of the adaptation realizes the segmentation of dance motion in a hierarchical fashion. The analysis method obtained by the trial of the above adaptation consists of the following procedures. A motion-capture data stream of a dance is first divided into a sequence of events by piecewise linear regression. The hierarchical structure of groups each of which consists of a sequence of the events is then extracted by applying the grouping rules adapted to dance motion analysis. The above method is applied to motion-data streams acquired by motion capture systems. The obtained results indicate the following advantages: (1) The structure of hierarchical segmentation is precisely extracted in response to the characteristic of an analyzed dance. (2) The extraction of the hierarchical segmentation provides the possibility of the development of a technique distinguishing the oversegmentation from regular boundaries. (3) The possibility of utilizing the information of hierarchical segmentation for the comparison of dance performances is suggested.

GraphClus, a MATLAB program for cluster analysis using graph theory

Cluster analysis is used in numerous scientific disciplines. A method of cluster analysis based on graph theory is discussed and a MATLAB™ code for its implementation is presented. The algorithm is based on the number of variables that are similar between samples. By changing the similarity criterion in a stepwise fashion, a hierarchical group structure develops, and can be displayed by a dendrogram. Three indexes describe the homogeneity of a given variable in a group, the heterogeneity of that variable between two groups, and the usefulness of that variable in distinguishing two groups. The algorithm is applied to both a synthetic dataset and a set of trace element analyses of lavas from Mount Etna in order to compare GraphClus to other cluster analysis algorithms.

FzMail: Using FIS-CRM for E-mail Classification

In this work a brief summary of FIS-CRM (Fuzzy Interrelations and Synonymy Conceptual Representation Model) and its application to intelligent e-mail management are presented. FzMail tool is based on a soft computing methodology for automatic classification of the mailbox into a fuzzy and hierarchical structure of groups of “conceptually related” messages. FIS-CRM is used to conceptually represent messages and it is also used in the process carried out to deal with the incoming messages in order to keep the achieved conceptual organization. The aim is to make an optimum exploitation of the concepts contained in these messages possible. Therefore, we apply Fuzzy Deformable Prototypes for the document clusters representation. The effectiveness of the method has been proved by applying these techniques in an IR system. The documents considered are composed by a set of e-mail messages produced by some distribution lists about different subjects and languages.

Key management for Pay-TV broadcast systems in hierarchy

In recent years, cable TV has enjoyed rapid growth and is now well established as one of the major broadcast media types. However, it is necessary to reinforce the security and confidentiality of current cable transmission data. In this paper, we introduce cryptographic accessing control into the architectural hierarchy of the Pay-TV system. The channels provided by the system can be categorized into various groups of a similar type. A subscriber to a specific group would be allowed to watch all channels within that group. In this way, the system’s key management is simplified and the private keys for accessibility to channels are reduced. Also, the access keys associated with each channel can be computationally derived and the updating procedure simplified. This means less time and lower costs are associated with the use of a hierarchical group structure. The access keys are then updated periodically during the month, depending on which day of the month the customer subscribed and paid for the service. The method we propose for a secure Pay-TV system with cryptographic key management has the following advantages including higher security, efficient encryption/decryption, hierarchy of groups and flexible key management.

Resource aware programming

We introduce the Resource Aware Programming framework, which allows users to monitor the resources used by their programs and to programmatically express policies for the management of such resources. The framework is based on a notion of hierarchical groups, which act as resource containers for the computations they sponsor. Asynchronous notifications for resource exhaustion and for computation termination can be handled by arbitrary user code, which is also executed under the control of this hierarchical group structure. Resources are manipulated by the programmer using resource descriptors, whose operations are specified by a resource algebra. In this article, we overview the Resource Aware Programming framework and describe its semantics in the form of a language-independent abstract machine able to model both shared and distributed memory environments. Finally, we discuss a prototype implementation of the Resource Aware Programming framework in Java.

Tlib—a library to support programming with hierarchical multi-processor tasks

The paper considers the modular programming with hierarchically structured multi-processor tasks on top of SPMD tasks for distributed memory machines. The parallel execution requires a corresponding decomposition of the set of processors into a hierarchical group structure onto which the tasks are mapped. The result is a multi-level group SPMD computation model with varying processor group structures. The advantage of this kind of mixed task and data parallelism is a potential to reduce the communication overhead and to increase scalability. We present a runtime library to support the coordination of hierarchically structured multi-processor tasks. The library exploits an extended parallel group SPMD programming model and manages the entire task execution including the dynamic hierarchy of processor groups. The library is built on top of MPI, has an easy-to-use interface, and leads to only a marginal overhead while allowing static planning and dynamic restructuring.

Timing variations in music performance: musical communication, perceptual compensation, and/or motor control?

A perceptual performance paradigm was designed to disentangle the timing variations in music performance that are due to perceptual compensation, motor control, and musical communication. First, pianists perceptually adjusted the interonset intervals of three excerpts so that they sounded regular. These adjustments deviated systematically from regularity, highlighting two sources of perceptual biases in time perception: rhythmic grouping and a psychoacoustic intensity effect. Then the participants performed the excerpts on the piano in the same regular way. The intensity effect disappeared, and some variations due to motor constraints were observed in relation to rhythmic groups. Finally, the participants performed the excerpts musically. Variations due to musical communication involved additional group-final lengthening that reflected the hierarchical grouping structure of the excerpts. These results underline the nuclear role of grouping in musical time perception and production.

An application of the FIS-CRM model to the FISS metasearcher: Using fuzzy synonymy and fuzzy generality for representing concepts in documents

The main objective of this work is to improve the quality of the results produced by the Internet search engines. In order to achieve it, the FIS-CRM model (Fuzzy Interrelations and Synonymy based Concept Representation Model) is proposed as a mechanism for representing the concepts (not only terms) contained in any kind of document. This model, based on the vector space model, incorporates a fuzzy readjustment process of the term weights of each document. The readjustment lies on the study of two types of fuzzy interrelations between terms: the fuzzy synonymy interrelation and the fuzzy generality interrelations (“broader than” and “narrower than” interrelations). The model has been implemented in the FISS metasearcher (Fuzzy Interrelations and Synonymy based Searcher) that, using a soft-clustering algorithm (based on the SISC algorithm), dynamically produces a hierarchical structure of groups of “conceptually related” documents (snippets of web pages, in this case).

Social network size in humans.

This paper examines social network size in contemporary Western society based on the exchange of Christmas cards. Maximum network size averaged 153.5 individuals, with a mean network size of 124.9 for those individuals explicitly contacted; these values are remarkably close to the group size of 150 predicted for humans on the basis of the size of their neocortex. Age, household type, and the relationship to the individual influence network structure, although the proportion of kin remained relatively constant at around 21%. Frequency of contact between network members was primarily determined by two classes of variable: passive factors (distance, work colleague, overseas) and active factors (emotional closeness, genetic relatedness). Controlling for the influence of passive factors on contact rates allowed the hierarchical structure of human social groups to be delimited. These findings suggest that there may be cognitive constraints on network size.

Nonparametric discriminant analysis of phytoplankton species using data from analytical flow cytometry.

Analytical flow cytometry (AFC) provides rapid and accurate measurement of particles from heterogeneous populations. AFC has been used to classify and identify phytoplankton species, but most methods of discriminant analysis of resulting data have depended on normality assumptions and outcomes have been disappointing. In this study, we consider nonparametric methods based on density estimation. In addition to the familiar kernel method, methods based on wavelets are also implemented. Full five-dimensional wavelet estimation proves to be computationally prohibitive with current workstation power, so we employ projection pursuit for reduction of dimensionality. AFC typically produces very large samples, so we also investigate data simplification through binning. Further modifications to the discrimination strategy are suggested by specific features of phytoplankton data, namely, a hierarchical group structure, the possible presence of many groups, and the likelihood of encountering an aberrant group in a test sample. We apply all the resultant procedures to appropriate subsets of a very large data set, demonstrate their efficacy, and compare their error rates with those of more conventional methods. We further show that incorporation of the specific features of phytoplankton data into the analysis leads to improved results and provides a general framework for analysis of such data.

The Reproduction of Social Inequality

Ideological assumptions of equality and economic individualism have permeated the traditional analysis of social mobility. This is shown most clearly in the use of perfect mobility as the theoretical model that underlies most of the empirical analyses. A major consequence is that these analyses have offered a poor conceptualisation of the nature of the structure within which movement occurs, and have tended to ignore the question of relative distances between the objects, typically conceived as social classes, making up that structure. A further consequence is that they have concentrated on the issue of how much mobility, rather than on why it does, or does not, occur. It is argued that a more adequate conceptualisation would involve a move away from rigidly defined class categories towards a recognition of the hierarchical structure of occupational groups.

Star Complexes and Associations: Fundamental and Elementary Cells of Star Formation

view Abstract Citations (159) References (130) Co-Reads Similar Papers Volume Content Graphics Metrics Export Citation NASA/ADS Star Complexes and Associations: Fundamental and Elementary Cells of Star Formation Efremov, Yuri N. Abstract This paper discusses data on young star groups that imply the existence of two distinct scales of star formation. The largest scale is that of the star complexes which we assume to be the initial scale, connected with the gas superclouds. The smaller scale is for the well known OB associations and young clusters, which relate to the elementary scale of star formation, that connected with individual giant molecular clouds. An intermediate scale, that of aggregates (groups of a few associations), probably also exists and corresponds to clusters of a few GMCs. The great majority of associations and young clusters are found inside huge star complexes, which include individual older stars (plausible former members of dissolved associations). This hierarchical structure of young star groups, together with the generally different luminosities of individual stars within the different scale aggregates explain the very different estimates of sizes of these groups (all of which have previously been called "associations") in galaxies at different distances and therefore resolution. Concentrations of gas clouds, young associations, and stars within vast complexes are consistent with a top-down scenario of star formation, implying that superclouds producing star complexes are the initial structures, which formed faster than clouds of smaller scale in gaseous galactic disks and especially within spiral density waves, mainly owing to large scale gravitational instability. Sheared star complexes form a flocculent spiral structure without older stars in spiraling patches. Probably all young galactic disks consist of units with masses of about 10^7^ in solar units. Most of the specimens of star complexes- the huge groups of clusters, associations, and high luminosity stars in our Galaxy, luminous patches in unresolved galaxies, and the vast star clouds in nearby galaxies-are not accidental agglomerations but physical entities deserving careful investigation. Publication: The Astronomical Journal Pub Date: December 1995 DOI: 10.1086/117728 Bibcode: 1995AJ....110.2757E Keywords: STARS: FORMATION; ISM: STRUCTURE full text sources ADS | data products SIMBAD (27) NED (10)

Diversity and commonality in music performance: an analysis of timing microstructure in Schumann's "Träumerei".

This study attempts to characterize the temporal commonalities and differences among distinguished pianists' interpretations of a well-known piece, Robert Schumann's "Träumerei." Intertone onset intervals (IOIs) were measured in 28 recorded performances. These data were subjected to a variety of statistical analyses, including principal components analysis of longer stretches of music and curve fitting to series of IOIs within brief melodic gestures. Global timing patterns reflected the hierarchical grouping structure of the composition, with pronounced ritardandi at the ends of major sections and frequent expressive lengthening of accented tones within melodic gestures. Analysis of local timing patterns, particularly of within-gesture ritardandi, revealed that they often followed a parabolic timing function. The major variation in these patterns can be modeled by families of parabolas with a single degree of freedom. The grouping structure, which prescribes the location of major tempo changes, and the parabolic timing function, which represents a natural manner of executing such changes, seem to be the two major constraints under which pianists are operating. Within these constraints, there is room for much individual variation, and there are always exceptions to the rules. The striking individuality of two legendary pianists, Alfred Cortot and Vladimir Horowitz, is objectively demonstrated here, as is the relative eccentricity of several other artists.

An alterative method for hospital partition determination using hierarchical cluster analysis.

The classification of short-term hospitals into homogeneous groups has become an integral part of many systems designed to abate continuing cost inflation in the hospital industry. This paper describes one approach which was developed to identify homogeneous groups of short-term hospitals. The approach, based on hierarchical cluster analysis, defines an objective measure (called expected distinctiveness) to evaluate any group of hospitals identified by a hierarchical grouping structure or dendrogram. Using this measure, an efficient algorithm is developed which finds the hospital partition from the identified groups which maximizes total expected distinctiveness. A numerical example illustrates the application and extensions.