Intuitionistic fuzzy (IF) evaluations of multidimensional model

International Nuclear Information System (INIS)

Valova, I.

2012-01-01

There are different logical methods for data structuring, but no one is perfect enough. Multidimensional model-MD of data is presentation of data in a form of cube (referred also as info-cube or hypercube) with data or in form of 'star' type scheme (referred as multidimensional scheme), by use of F-structures (Facts) and set of D-structures (Dimensions), based on the notion of hierarchy of D-structures. The data, being subject of analysis in a specific multidimensional model is located in a Cartesian space, being restricted by D-structures. In fact, the data is either dispersed or 'concentrated', therefore the data cells are not distributed evenly within the respective space. The moment of occurrence of any event is difficult to be predicted and the data is concentrated as per time periods, location of performed business event, etc. To process such dispersed or concentrated data, various technical strategies are needed. The basic methods for presentation of such data should be selected. The approaches of data processing and respective calculations are connected with different options for data representation. The use of intuitionistic fuzzy evaluations (IFE) provide us new possibilities for alternative presentation and processing of data, subject of analysis in any OLAP application. The use of IFE at the evaluation of multidimensional models will result in the following advantages: analysts will dispose with more complete information for processing and analysis of respective data; benefit for the managers is that the final decisions will be more effective ones; enabling design of more functional multidimensional schemes. The purpose of this work is to apply intuitionistic fuzzy evaluations of multidimensional model of data. (authors)

ROMANIA’S FISCAL STRUCTURE IN VIEW OF EURO ADOPTION. A MULTIDIMENSIONAL ANALYSIS

Directory of Open Access Journals (Sweden)

Maria-Isadora Lazar

2014-04-01

Full Text Available The aim of this paper is to conclude whether the adoption of the single currency induced a trend of structural resemblance, and if so, to determine groups of countries with similar fiscal structures inside the Euro Area. Taking into consideration total revenues, indirect taxation, direct taxation and social contributions, we analyzed primary data and completed it with multidimensional classification. Having in view Romania’s objective of adopting Euro currency we aim to establish to which subgroup is Romania more similar in terms of fiscal structure and whether this resemblance enhanced since the accession to the European Union.

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

OpenAIRE

Wang, Feng; Sun, Jian-Gang; Zhang, Ning

2014-01-01

Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA) method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two compone...

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

International Nuclear Information System (INIS)

Olson, Gordon L.

2008-01-01

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

Energy Technology Data Exchange (ETDEWEB)

Olson, Gordon L. [Computer and Computational Sciences Division (CCS-2), Los Alamos National Laboratory, 5 Foxglove Circle, Madison, WI 53717 (United States)], E-mail: olson99@tds.net

2008-11-15

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution.

Applying 4-regular grid structures in large-scale access networks

DEFF Research Database (Denmark)

Pedersen, Jens Myrup; Knudsen, Thomas P.; Patel, Ahmed

2006-01-01

4-Regular grid structures have been used in multiprocessor systems for decades due to a number of nice properties with regard to routing, protection, and restoration, together with a straightforward planar layout. These qualities are to an increasing extent demanded also in largescale access...... networks, but concerning protection and restoration these demands have been met only to a limited extent by the commonly used ring and tree structures. To deal with the fact that classical 4-regular grid structures are not directly applicable in such networks, this paper proposes a number of extensions...... concerning restoration, protection, scalability, embeddability, flexibility, and cost. The extensions are presented as a tool case, which can be used for implementing semi-automatic and in the longer term full automatic network planning tools....

Sparse regularization for EIT reconstruction incorporating structural information derived from medical imaging.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Mueller-Lisse, Ullrich; Moeller, Knut

2016-06-01

Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. This is an ill-posed inverse problem usually solved on a finite element mesh. For this article, a special regularization method incorporating structural information of the targeted domain is proposed and evaluated. Structural information was obtained either from computed tomography images or from preliminary EIT reconstructions by a modified k-means clustering. The proposed regularization method integrates this structural information into the reconstruction as a soft constraint preferring sparsity in group level. A first evaluation with Monte Carlo simulations indicated that the proposed solver is more robust to noise and the resulting images show fewer artifacts. This finding is supported by real data analysis. The structure based regularization has the potential to balance structural a priori information with data driven reconstruction. It is robust to noise, reduces artifacts and produces images that reflect anatomy and are thus easier to interpret for physicians.

Self-Concepts in Reading, Writing, Listening, and Speaking: A Multidimensional and Hierarchical Structure and Its Generalizability across Native and Foreign Languages

Science.gov (United States)

Arens, A. Katrin; Jansen, Malte

2016-01-01

Academic self-concept has been conceptualized as a multidimensional and hierarchical construct. Previous research has mostly focused on its multidimensionality, distinguishing between verbal and mathematical self-concept domains, and only a few studies have examined the factorial structure within specific self-concept domains. The present study…

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

Science.gov (United States)

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

The emergence and evolution of the multidimensional organization

OpenAIRE

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the Foundation for Management Studies which suggests that synergies across business divisions can be exploited by the M-form, a team approach to creating economic value, examples of multidimensional firms suc...

Multi-Dimensional Path Queries

DEFF Research Database (Denmark)

Bækgaard, Lars

1998-01-01

to create nested path structures. We present an SQL-like query language that is based on path expressions and we show how to use it to express multi-dimensional path queries that are suited for advanced data analysis in decision support environments like data warehousing environments......We present the path-relationship model that supports multi-dimensional data modeling and querying. A path-relationship database is composed of sets of paths and sets of relationships. A path is a sequence of related elements (atoms, paths, and sets of paths). A relationship is a binary path...

The emergence and evolution of the multidimensional organization

NARCIS (Netherlands)

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the

Multidimensional structure of employee motivation - Clustering approach

Science.gov (United States)

Gąsior, Marcin; Skowron, Łukasz; Sak-Skowron, Monika

2014-12-01

Employees' motivation along with their satisfaction with work is one of the most significant factors determining functioning and the success of an organization on the market. The purpose of this article is to demonstrate that motivation to work is a phenomenon whose nature is different among subsequent employees not only in terms of its general level, but also internal structure, and checking whether among various possible structures of motivation there is repeatability which could prove the existence of specific regularities and enabling possible classification of employees. Reasoning with regard to internal structure of motivation was conducted on the basis of the designated 14 variables expressing it, which included both internal factors (feelings) and external (actions), both positive and negative in its meaning. The conducted research consisted in segmentation of the surveyed employees using the generalized method of k-means, in order to separate groups with the same subsequent intensity profiles, so designated variables. By way of research, five various groups of employees were found. Each has a unique, different profile of motivation, at the same time, in each of them a different satisfaction level of the employed was observed. The analysis leads to a conclusion that the motivation profile itself is not completely connected with the perceived satisfaction with work. While signs of motivation positive in nature are usually stronger among satisfied employees, and the weaker - among dissatisfied ones, we cannot speak about a similar regularity when it comes to factors of negative nature. Furthermore, the presented research shows that within negative factors, larger intensification can be observed among ones of internal nature, while among these of external nature - it is smaller.

Fractional Regularization Term for Variational Image Registration

Directory of Open Access Journals (Sweden)

Rafael Verdú-Monedero

2009-01-01

Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

University Students' Knowledge Structures and Informal Reasoning on the Use of Genetically Modified Foods: Multidimensional Analyses

Science.gov (United States)

Wu, Ying-Tien

2013-01-01

This study aims to provide insights into the role of learners' knowledge structures about a socio-scientific issue (SSI) in their informal reasoning on the issue. A total of 42 non-science major university students' knowledge structures and informal reasoning were assessed with multidimensional analyses. With both qualitative and…

Examination of the Structure and Grade-Related Differentiation of Multidimensional Self-Concept Instruments for Children Using ESEM

Science.gov (United States)

Arens, A. Katrin; Morin, Alexandre J. S.

2016-01-01

This study is a substantive-methodological synergy in which exploratory structural equation modeling is applied to investigate the factor structure of multidimensional self-concept instruments. On the basis of a sample of German students (N = 1958) who completed the Self-Description Questionnaire I and the Self-Perception Profile for Children, the…

Examining Similarity Structure: Multidimensional Scaling and Related Approaches in Neuroimaging

Directory of Open Access Journals (Sweden)

Svetlana V. Shinkareva

2013-01-01

Full Text Available This paper covers similarity analyses, a subset of multivariate pattern analysis techniques that are based on similarity spaces defined by multivariate patterns. These techniques offer several advantages and complement other methods for brain data analyses, as they allow for comparison of representational structure across individuals, brain regions, and data acquisition methods. Particular attention is paid to multidimensional scaling and related approaches that yield spatial representations or provide methods for characterizing individual differences. We highlight unique contributions of these methods by reviewing recent applications to functional magnetic resonance imaging data and emphasize areas of caution in applying and interpreting similarity analysis methods.

Followee recommendation in microblog using matrix factorization model with structural regularization.

Science.gov (United States)

Yu, Yan; Qiu, Robin G

2014-01-01

Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.

Multidimensional Riemann problem with self-similar internal structure. Part II - Application to hyperbolic conservation laws on unstructured meshes

Science.gov (United States)

Balsara, Dinshaw S.; Dumbser, Michael

2015-04-01

Multidimensional Riemann solvers that have internal sub-structure in the strongly-interacting state have been formulated recently (D.S. Balsara (2012, 2014) [5,16]). Any multidimensional Riemann solver operates at the grid vertices and takes as its input all the states from its surrounding elements. It yields as its output an approximation of the strongly interacting state, as well as the numerical fluxes. The multidimensional Riemann problem produces a self-similar strongly-interacting state which is the result of several one-dimensional Riemann problems interacting with each other. To compute this strongly interacting state and its higher order moments we propose the use of a Galerkin-type formulation to compute the strongly interacting state and its higher order moments in terms of similarity variables. The use of substructure in the Riemann problem reduces numerical dissipation and, therefore, allows a better preservation of flow structures, like contact and shear waves. In this second part of a series of papers we describe how this technique is extended to unstructured triangular meshes. All necessary details for a practical computer code implementation are discussed. In particular, we explicitly present all the issues related to computational geometry. Because these Riemann solvers are Multidimensional and have Self-similar strongly-Interacting states that are obtained by Consistency with the conservation law, we call them MuSIC Riemann solvers. (A video introduction to multidimensional Riemann solvers is available on http://www.elsevier.com/xml/linking-roles/text/html". The MuSIC framework is sufficiently general to handle general nonlinear systems of hyperbolic conservation laws in multiple space dimensions. It can also accommodate all self-similar one-dimensional Riemann solvers and subsequently produces a multidimensional version of the same. In this paper we focus on unstructured triangular meshes. As examples of different systems of conservation laws we

Multidimensional spectrometer

Science.gov (United States)

Zanni, Martin Thomas; Damrauer, Niels H.

2010-07-20

A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.

Analysis of the time structure of synchronization in multidimensional chaotic systems

Energy Technology Data Exchange (ETDEWEB)

Makarenko, A. V., E-mail: avm.science@mail.ru [Constructive Cybernetics Research Group (Russian Federation)

2015-05-15

A new approach is proposed to the integrated analysis of the time structure of synchronization of multidimensional chaotic systems. The method allows one to diagnose and quantitatively evaluate the intermittency characteristics during synchronization of chaotic oscillations in the T-synchronization mode. A system of two identical logistic mappings with unidirectional coupling that operate in the developed chaos regime is analyzed. It is shown that the widely used approach, in which only synchronization patterns are subjected to analysis while desynchronization areas are considered as a background signal and removed from analysis, should be regarded as methodologically incomplete.

Analysis of the time structure of synchronization in multidimensional chaotic systems

International Nuclear Information System (INIS)

Makarenko, A. V.

2015-01-01

A new approach is proposed to the integrated analysis of the time structure of synchronization of multidimensional chaotic systems. The method allows one to diagnose and quantitatively evaluate the intermittency characteristics during synchronization of chaotic oscillations in the T-synchronization mode. A system of two identical logistic mappings with unidirectional coupling that operate in the developed chaos regime is analyzed. It is shown that the widely used approach, in which only synchronization patterns are subjected to analysis while desynchronization areas are considered as a background signal and removed from analysis, should be regarded as methodologically incomplete

Analysis of self-similar solutions of multidimensional conservation laws

Energy Technology Data Exchange (ETDEWEB)

Keyfitz, Barbara Lee [The Ohio State Univ., Columbus, OH (United States)

2014-02-15

This project focused on analysis of multidimensional conservation laws, specifically on extensions to the study of self-siminar solutions, a project initiated by the PI. In addition, progress was made on an approach to studying conservation laws of very low regularity; in this research, the context was a novel problem in chromatography. Two graduate students in mathematics were supported during the grant period, and have almost completed their thesis research.

Regularities of structure formation on different stages of WC-Co hard alloys fabrication

Energy Technology Data Exchange (ETDEWEB)

Chernyavskij, K S

1987-03-01

Some regularities of structural transformations in powder products of the hard alloys fabrication have been formulated on the basis of results of the author works and other native and foreign reseachers. New data confirming the influene of technological prehistory of carbide powder on the mechanism of its particle grinding as well as the influence of the structural-energy state of WC powder on the course of the WC-Co alloy structure formation processes are given. Some possibilities for the application in practice of the regularities studied are considered.

On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

DEFF Research Database (Denmark)

Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreses distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law depen...

Visualizing information across multidimensional post-genomic structured and textual databases.

Science.gov (United States)

Tao, Ying; Friedman, Carol; Lussier, Yves A

2005-04-15

Visualizing relationships among biological information to facilitate understanding is crucial to biological research during the post-genomic era. Although different systems have been developed to view gene-phenotype relationships for specific databases, very few have been designed specifically as a general flexible tool for visualizing multidimensional genotypic and phenotypic information together. Our goal is to develop a method for visualizing multidimensional genotypic and phenotypic information and a model that unifies different biological databases in order to present the integrated knowledge using a uniform interface. We developed a novel, flexible and generalizable visualization tool, called PhenoGenesviewer (PGviewer), which in this paper was used to display gene-phenotype relationships from a human-curated database (OMIM) and from an automatic method using a Natural Language Processing tool called BioMedLEE. Data obtained from multiple databases were first integrated into a uniform structure and then organized by PGviewer. PGviewer provides a flexible query interface that allows dynamic selection and ordering of any desired dimension in the databases. Based on users' queries, results can be visualized using hierarchical expandable trees that present views specified by users according to their research interests. We believe that this method, which allows users to dynamically organize and visualize multiple dimensions, is a potentially powerful and promising tool that should substantially facilitate biological research. PhenogenesViewer as well as its support and tutorial are available at http://www.dbmi.columbia.edu/pgviewer/ Lussier@dbmi.columbia.edu.

A Conceptual Model for Multidimensional Analysis of Documents

Science.gov (United States)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

Regularities development of entrepreneurial structures in regions

Directory of Open Access Journals (Sweden)

Julia Semenovna Pinkovetskaya

2012-12-01

Full Text Available Consider regularities and tendencies for the three types of entrepreneurial structures — small enterprises, medium enterprises and individual entrepreneurs. The aim of the research was to confirm the possibilities of describing indicators of aggregate entrepreneurial structures with the use of normal law distribution functions. Presented proposed by the author the methodological approach and results of construction of the functions of the density distribution for the main indicators for the various objects: the Russian Federation, regions, as well as aggregates ofentrepreneurial structures, specialized in certain forms ofeconomic activity. All the developed functions, as shown by the logical and statistical analysis, are of high quality and well-approximate the original data. In general, the proposed methodological approach is versatile and can be used in further studies of aggregates of entrepreneurial structures. The received results can be applied in solving a wide range of problems justify the need for personnel and financial resources at the federal, regional and municipal levels, as well as the formation of plans and forecasts of development entrepreneurship and improvement of this sector of the economy.

Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers

NARCIS (Netherlands)

Bolt, J.H.; van der Gaag, L.C.

Multi-dimensional Bayesian network classifiers are Bayesian networks of restricted topological structure, which are tailored to classifying data instances into multiple dimensions. Like more traditional classifiers, multi-dimensional classifiers are typically learned from data and may include

Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal.

Science.gov (United States)

Ge, Qi; Jing, Xiao-Yuan; Wu, Fei; Wei, Zhi-Hui; Xiao, Liang; Shao, Wen-Ze; Yue, Dong; Li, Hai-Bo

2017-07-01

Nonlocal image representation methods, including group-based sparse coding and block-matching 3-D filtering, have shown their great performance in application to low-level tasks. The nonlocal prior is extracted from each group consisting of patches with similar intensities. Grouping patches based on intensity similarity, however, gives rise to disturbance and inaccuracy in estimation of the true images. To address this problem, we propose a structure-based low-rank model with graph nuclear norm regularization. We exploit the local manifold structure inside a patch and group the patches by the distance metric of manifold structure. With the manifold structure information, a graph nuclear norm regularization is established and incorporated into a low-rank approximation model. We then prove that the graph-based regularization is equivalent to a weighted nuclear norm and the proposed model can be solved by a weighted singular-value thresholding algorithm. Extensive experiments on additive white Gaussian noise removal and mixed noise removal demonstrate that the proposed method achieves a better performance than several state-of-the-art algorithms.

Selection of regularization parameter for l1-regularized damage detection

Science.gov (United States)

Hou, Rongrong; Xia, Yong; Bao, Yuequan; Zhou, Xiaoqing

2018-06-01

The l1 regularization technique has been developed for structural health monitoring and damage detection through employing the sparsity condition of structural damage. The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution. However, the l1 regularization problem has no closed-form solution, and the regularization parameter is usually selected by experience. This study proposes two strategies of selecting the regularization parameter for the l1-regularized damage detection problem. The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small. The other method is based on the discrepancy principle, which requires that the variance of the discrepancy between the calculated and measured responses is close to the variance of the measurement noise. The two methods are applied to a cantilever beam and a three-story frame. A range of the regularization parameter, rather than one single value, can be determined. When the regularization parameter in this range is selected, the damage can be accurately identified even for multiple damage scenarios. This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.

Confirmatory factor analysis and invariance testing between Blacks and Whites of the Multidimensional Health Locus of Control scale.

Science.gov (United States)

LaNoue, Marianna; Harvey, Abby; Mautner, Dawn; Ku, Bon; Scott, Kevin

2015-07-01

The factor structure of the Multidimensional Health Locus of Control scale remains in question. Additionally, research on health belief differences between Black and White respondents suggests that the Multidimensional Health Locus of Control scale may not be invariant. We reviewed the literature regarding the latent variable structure of the Multidimensional Health Locus of Control scale, used confirmatory factor analysis to confirm the three-factor structure of the Multidimensional Health Locus of Control, and analyzed between-group differences in the Multidimensional Health Locus of Control structure and means across Black and White respondents. Our results indicate differences in means and structure, indicating more research is needed to inform decisions regarding whether and how to deploy the Multidimensional Health Locus of Control appropriately.

Multidimensional generalized-ensemble algorithms for complex systems.

Science.gov (United States)

Mitsutake, Ayori; Okamoto, Yuko

2009-06-07

We give general formulations of the multidimensional multicanonical algorithm, simulated tempering, and replica-exchange method. We generalize the original potential energy function E(0) by adding any physical quantity V of interest as a new energy term. These multidimensional generalized-ensemble algorithms then perform a random walk not only in E(0) space but also in V space. Among the three algorithms, the replica-exchange method is the easiest to perform because the weight factor is just a product of regular Boltzmann-like factors, while the weight factors for the multicanonical algorithm and simulated tempering are not a priori known. We give a simple procedure for obtaining the weight factors for these two latter algorithms, which uses a short replica-exchange simulation and the multiple-histogram reweighting techniques. As an example of applications of these algorithms, we have performed a two-dimensional replica-exchange simulation and a two-dimensional simulated-tempering simulation using an alpha-helical peptide system. From these simulations, we study the helix-coil transitions of the peptide in gas phase and in aqueous solution.

Structural diversity: a multi-dimensional approach to assess recreational services in urban parks.

Science.gov (United States)

Voigt, Annette; Kabisch, Nadja; Wurster, Daniel; Haase, Dagmar; Breuste, Jürgen

2014-05-01

Urban green spaces provide important recreational services for urban residents. In general, when park visitors enjoy "the green," they are in actuality appreciating a mix of biotic, abiotic, and man-made park infrastructure elements and qualities. We argue that these three dimensions of structural diversity have an influence on how people use and value urban parks. We present a straightforward approach for assessing urban parks that combines multi-dimensional landscape mapping and questionnaire surveys. We discuss the method as well the results from its application to differently sized parks in Berlin and Salzburg.

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

Directory of Open Access Journals (Sweden)

Feng Wang

2014-01-01

Full Text Available Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two components earthquake excitations, and independent analysis in each direction is not required and the application of simplified superposition formulas is avoided. The strength reduction factor spectra based on superposition of earthquake excitations are discussed and compared with the traditional strength reduction factor spectra. The step-by-step procedure is proposed to estimate seismic demands of structures. Two examples are implemented to verify the accuracy of the method, and the results of the examples show that (1 the IMMPA method can be used to estimate the responses of structure subjected to bidirectional earthquake excitations. (2 Along with increase of peak of earthquake acceleration, structural response deviation estimated with the IMMPA method may also increase. (3 Along with increase of the number of total floors of structures, structural response deviation estimated with the IMMPA method may also increase.

Influence of the volume ratio of solid phase on carrying capacity of regular porous structure

Directory of Open Access Journals (Sweden)

Monkova Katarina

2017-01-01

Full Text Available Direct metal laser sintering is spread technology today. The main advantage of this method is the ability to produce parts which have a very complex geometry and which can be produced only in very complicated way by classical conventional methods. Special category of such components are parts with porous structure, which can give to the product extraordinary combination of properties. The article deals with some aspects that influence the manufacturing of regular porous structures in spite of the fact that input technological parameters at various samples were the same. The main goal of presented research has been to investigate the influence of the volume ratio of solid phase on carrying capacity of regular porous structure. Realized tests have indicated that the unit of regular porous structure with lower volume ratio is able to carry a greater load to failure than the unit with higher volume ratio.

Multidimensional Structure for Definingthe Effect of Organizational Culture and Supply Chain Culture on Knowledge Sharing in Supply Chain of Automotive Industry: With Emphasis on Improving Supply Chain Performance

Directory of Open Access Journals (Sweden)

Mohsen Shafiei Nikabadi

2012-12-01

Full Text Available : One of the key aspects of knowledge management is organizational culture. Finding an appropriate culture and key indicators for culture in implementation and execution of knowledge management are one the most important matter in knowledge management implementation in any organization. So, the main purpose of this article was presenting a multidimensional structure for organizational culture and supply chain culture with the aim of effective knowledge sharing in supply chain of automotive industry of Iran. First, according to the literature review, key indicators for any dimension of multidimensional structure of the research were defined. Then, key indicators were revised, adjusted and modified by three industry experts and three college professors, so 4 questions and 5 hypotheses were offered. Next, that multidimensional structure has been assessed as a survey and cause-effect study in supply chains of Iran Khodro Company and Saipa Company.115 industry professionals have participated in this study. In the research, after testing co-linearity between variables, relations between different dimensions of the multidimensional structure have been assessed with the help of path analysis. Research findings showed that the multidimensional structure introduced in the study had an appropriate fitness in automotive industry. The results of path analysis also showed that the culture of the supply chain has had the greatest impact of Business culture. On the other hand, business culture had a strong but indirect effect on supply chain performance. And finally, the greatest effect of knowledge sharing and transferring was on non-financial performance of supply chain.

Multi-dimensional Fuzzy Euler Approximation

Directory of Open Access Journals (Sweden)

Yangyang Hao

2017-05-01

Full Text Available Multi-dimensional Fuzzy differential equations driven by multi-dimen-sional Liu process, have been intensively applied in many fields. However, we can not obtain the analytic solution of every multi-dimensional fuzzy differential equation. Then, it is necessary for us to discuss the numerical results in most situations. This paper focuses on the numerical method of multi-dimensional fuzzy differential equations. The multi-dimensional fuzzy Taylor expansion is given, based on this expansion, a numerical method which is designed for giving the solution of multi-dimensional fuzzy differential equation via multi-dimensional Euler method will be presented, and its local convergence also will be discussed.

The significance of the structural regularity for the seismic response of buildings

International Nuclear Information System (INIS)

Hampe, E.; Goldbach, R.; Schwarz, J.

1991-01-01

The paper gives an state-of-the-art report about the international design practice and submits fundamentals for a systematic approach to the solution of that problem. Different criteria of regularity are presented and discussed with respect to EUROCODE Nr. 8. Still remaining questions and the main topics of future research activities are announced and come into consideration. Frame structures with or without additional stiffening wall elements are investigated to illustrate the qualitative differences of the vibrational properties and the earthquake response of regular and irregular systems. (orig./HP) [de

On multidimensional item response theory -- a coordinate free approach

OpenAIRE

Antal, Tamás

2007-01-01

A coordinate system free definition of complex structure multidimensional item response theory (MIRT) for dichotomously scored items is presented. The point of view taken emphasizes the possibilities and subtleties of understanding MIRT as a multidimensional extension of the ``classical'' unidimensional item response theory models. The main theorem of the paper is that every monotonic MIRT model looks the same; they are all trivial extensions of univariate item response theory.

Strictly-regular number system and data structures

DEFF Research Database (Denmark)

Elmasry, Amr Ahmed Abd Elmoneim; Jensen, Claus; Katajainen, Jyrki

2010-01-01

We introduce a new number system that we call the strictly-regular system, which efficiently supports the operations: digit-increment, digit-decrement, cut, concatenate, and add. Compared to other number systems, the strictly-regular system has distinguishable properties. It is superior to the re...

Optimal analysis of structures by concepts of symmetry and regularity

CERN Document Server

Kaveh, Ali

2013-01-01

Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The ...

Multidimensional Heat Conduction

DEFF Research Database (Denmark)

Rode, Carsten

1998-01-01

Analytical theory of multidimensional heat conduction. General heat conduction equation in three dimensions. Steay state, analytical solutions. The Laplace equation. Method of separation of variables. Principle of superposition. Shape factors. Transient, multidimensional heat conduction....

Identification of moving vehicle forces on bridge structures via moving average Tikhonov regularization

Science.gov (United States)

Pan, Chu-Dong; Yu, Ling; Liu, Huan-Lin

2017-08-01

Traffic-induced moving force identification (MFI) is a typical inverse problem in the field of bridge structural health monitoring. Lots of regularization-based methods have been proposed for MFI. However, the MFI accuracy obtained from the existing methods is low when the moving forces enter into and exit a bridge deck due to low sensitivity of structural responses to the forces at these zones. To overcome this shortcoming, a novel moving average Tikhonov regularization method is proposed for MFI by combining with the moving average concepts. Firstly, the bridge-vehicle interaction moving force is assumed as a discrete finite signal with stable average value (DFS-SAV). Secondly, the reasonable signal feature of DFS-SAV is quantified and introduced for improving the penalty function (∣∣x∣∣2 2) defined in the classical Tikhonov regularization. Then, a feasible two-step strategy is proposed for selecting regularization parameter and balance coefficient defined in the improved penalty function. Finally, both numerical simulations on a simply-supported beam and laboratory experiments on a hollow tube beam are performed for assessing the accuracy and the feasibility of the proposed method. The illustrated results show that the moving forces can be accurately identified with a strong robustness. Some related issues, such as selection of moving window length, effect of different penalty functions, and effect of different car speeds, are discussed as well.

Multidimensional high harmonic spectroscopy

International Nuclear Information System (INIS)

Bruner, Barry D; Soifer, Hadas; Shafir, Dror; Dudovich, Nirit; Serbinenko, Valeria; Smirnova, Olga

2015-01-01

High harmonic generation (HHG) has opened up a new frontier in ultrafast science where attosecond time resolution and Angstrom spatial resolution are accessible in a single measurement. However, reconstructing the dynamics under study is limited by the multiple degrees of freedom involved in strong field interactions. In this paper we describe a new class of measurement schemes for resolving attosecond dynamics, integrating perturbative nonlinear optics with strong-field physics. These approaches serve as a basis for multidimensional high harmonic spectroscopy. Specifically, we show that multidimensional high harmonic spectroscopy can measure tunnel ionization dynamics with high precision, and resolves the interference between multiple ionization channels. In addition, we show how multidimensional HHG can function as a type of lock-in amplifier measurement. Similar to multi-dimensional approaches in nonlinear optical spectroscopy that have resolved correlated femtosecond dynamics, multi-dimensional high harmonic spectroscopy reveals the underlying complex dynamics behind attosecond scale phenomena. (paper)

Numeric invariants from multidimensional persistence

Energy Technology Data Exchange (ETDEWEB)

Skryzalin, Jacek [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlsson, Gunnar [Stanford Univ., Stanford, CA (United States)

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data.

Frost Multidimensional Perfectionism Scale: the portuguese version

Directory of Open Access Journals (Sweden)

Ana Paula Monteiro Amaral

2013-01-01

Full Text Available BACKGROUND: The Frost Multidimensional Perfectionism Scale is one of the most world widely used measures of perfectionism. OBJECTIVE: To analyze the psychometric properties of the Portuguese version of the Frost Multidimensional Perfectionism Scale. METHODS: Two hundred and seventeen (178 females students from two Portuguese Universities filled in the scale, and a subgroup (n = 166 completed a retest with a four weeks interval. RESULTS: The scale reliability was good (Cronbach alpha = .857. Corrected item-total correlations ranged from .019 to .548. The scale test-retest reliability suggested a good temporal stability with a test-retest correlation of .765. A principal component analysis with Varimax rotation was performed and based on the Scree plot, two robust factorial structures were found (four and six factors. The principal component analyses, using Monte Carlo PCA for parallel analyses confirmed the six factor solution. The concurrent validity with Hewitt and Flett MPS was high, as well as the discriminant validity of positive and negative affect (Profile of Mood Stats-POMS. DISCUSSION: The two factorial structures (of four and six dimensions of the Portuguese version of Frost Multidimensional Perfectionism Scale replicate the results from different authors, with different samples and cultures. This suggests this scale is a robust instrument to assess perfectionism, in several clinical and research settings as well as in transcultural studies.

General inverse problems for regular variation

DEFF Research Database (Denmark)

Damek, Ewa; Mikosch, Thomas Valentin; Rosinski, Jan

2014-01-01

Regular variation of distributional tails is known to be preserved by various linear transformations of some random structures. An inverse problem for regular variation aims at understanding whether the regular variation of a transformed random object is caused by regular variation of components ...

A function space framework for structural total variation regularization with applications in inverse problems

Science.gov (United States)

Hintermüller, Michael; Holler, Martin; Papafitsoros, Kostas

2018-06-01

In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semi-continuous envelope (relaxation) of a suitable TV type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted TV for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddle-point problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson log-likelihood data discrepancy terms. Finally, we provide proof-of-concept numerical examples where we solve the saddle-point problem for weighted TV denoising as well as for MR guided PET image reconstruction.

Multi-Dimensional Customer Data Analysis in Online Auctions

Institute of Scientific and Technical Information of China (English)

LAO Guoling; XIONG Kuan; QIN Zheng

2007-01-01

In this paper, we designed a customer-centered data warehouse system with five subjects: listing, bidding, transaction,accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example,analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types: impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

Energy Technology Data Exchange (ETDEWEB)

Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn; Huang, Jing; Zhang, Hua; Lu, Lijun; Lyu, Wenbing; Feng, Qianjin; Chen, Wufan; Ma, Jianhua, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn [Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515, China and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong 510515 (China); Zhang, Jing [Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052 (China)

2016-05-15

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.

On Line Segment Length and Mapping 4-regular Grid Structures in Network Infrastructures

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Nielsen, Rasmus Hjorth; Pedersen, Jens Myrup

2006-01-01

The paper focuses on mapping the road network into 4-regular grid structures. A mapping algorithm is proposed. To model the road network GIS data have been used. The Geographic Information System (GIS) data for the road network are composed with different size of line segment lengths...

Effective field theory dimensional regularization

International Nuclear Information System (INIS)

Lehmann, Dirk; Prezeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed

Effective field theory dimensional regularization

Science.gov (United States)

Lehmann, Dirk; Prézeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed.

A new multidimensional model with text dimensions: definition and implementation

Directory of Open Access Journals (Sweden)

MariaJ. Martin-Bautista

2013-02-01

Full Text Available We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic way, without user's intervention, so all the classical operations in the multidimensional model can been defined for this textual dimension. While most of the models dealing with texts that can be found in the literature are not implemented, in this proposal, the multidimensional model and the OLAP system have been implemented in a software tool, so it can be tested on real data. A case study with medical data is included in this work.

Multi-Dimensional Damage Detection for Surfaces and Structures

Science.gov (United States)

Williams, Martha; Lewis, Mark; Roberson, Luke; Medelius, Pedro; Gibson, Tracy; Parks, Steen; Snyder, Sarah

2013-01-01

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or

STRUCTURE OPTIMIZATION OF RESERVATION BY PRECISE QUADRATIC REGULARIZATION

Directory of Open Access Journals (Sweden)

KOSOLAP A. I.

2015-11-01

Full Text Available The problem of optimization of the structure of systems redundancy elements. Such problems arise in the design of complex systems. To improve the reliability of operation of such systems of its elements are duplicated. This increases system cost and improves its reliability. When optimizing these systems is maximized probability of failure of the entire system while limiting its cost or the cost is minimized for a given probability of failure-free operation. A mathematical model of the problem is a discrete backup multiextremal. To search for the global extremum of currently used methods of Lagrange multipliers, coordinate descent, dynamic programming, random search. These methods guarantee a just and local solutions are used in the backup tasks of small dimension. In the work for solving redundancy uses a new method for accurate quadratic regularization. This method allows you to convert the original discrete problem to the maximization of multi vector norm on a convex set. This means that the diversity of the tasks given to the problem of redundancy maximize vector norm on a convex set. To solve the problem, a reformed straightdual interior point methods. Currently, it is the best method for local optimization of nonlinear problems. Transformed the task includes a new auxiliary variable, which is determined by dichotomy. There have been numerous comparative numerical experiments in problems with the number of redundant subsystems to one hundred. These experiments confirm the effectiveness of the method of precise quadratic regularization for solving problems of redundancy.

New multidimensional functional diversity indices for a multifaceted framework in functional ecology.

Science.gov (United States)

Villéger, Sébastien; Mason, Norman W H; Mouillot, David

2008-08-01

Functional diversity is increasingly identified as an important driver of ecosystem functioning. Various indices have been proposed to measure the functional diversity of a community, but there is still no consensus on which are most suitable. Indeed, none of the existing indices meets all the criteria required for general use. The main criteria are that they must be designed to deal with several traits, take into account abundances, and measure all the facets of functional diversity. Here we propose three indices to quantify each facet of functional diversity for a community with species distributed in a multidimensional functional space: functional richness (volume of the functional space occupied by the community), functional evenness (regularity of the distribution of abundance in this volume), and functional divergence (divergence in the distribution of abundance in this volume). Functional richness is estimated using the existing convex hull volume index. The new functional evenness index is based on the minimum spanning tree which links all the species in the multidimensional functional space. Then this new index quantifies the regularity with which species abundances are distributed along the spanning tree. Functional divergence is measured using a novel index which quantifies how species diverge in their distances (weighted by their abundance) from the center of gravity in the functional space. We show that none of the indices meets all the criteria required for a functional diversity index, but instead we show that the set of three complementary indices meets these criteria. Through simulations of artificial data sets, we demonstrate that functional divergence and functional evenness are independent of species richness and that the three functional diversity indices are independent of each other. Overall, our study suggests that decomposition of functional diversity into its three primary components provides a meaningful framework for its quantification

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Skip-webs: Efficient distributed data structures for multi-dimensional data sets

DEFF Research Database (Denmark)

Arge, Lars; Eppstein, David; Goodrich, Michael T.

2005-01-01

querying scenarios, which include linear (one-dimensional) data, such as sorted sets, as well as multi-dimensional data, such as d-dimensional octrees and digital tries of character strings defined over a fixed alphabet. We show how to perform a query over such a set of n items spread among n hosts using O...

New strategy for stable-isotope-aided, multidimensional NMR spectroscopy of DNA oligomers

Energy Technology Data Exchange (ETDEWEB)

Ono, Okira; Tate, Shin-Ichi; Kainosho, Masatsune [Tokyo Metropolitan Univ., Tokyo (Japan)

1994-12-01

Nuclear Magnetic Resonance (NMR) is the most efficient method for determining the solution structures of biomolecules. By applying multidimensional heteronuclear NMR techniques to {sup 13}C/{sup 15}N-labeled proteins, we can determine the solution structures of proteins with molecular mass of 20 to 30kDa at an accuracy similar to that of x-ray crystallography. Improvements in NMR instrumentation and techniques as well as the development of protein engineering methods for labeling proteins have rapidly advanced multidimensional heteronuclear NMR of proteins. In contrast, multidimensional heteronuclear NMR studies of nucleic acids is less advanced because there were no efficient methods for preparing large amounts of labeled DNA/RNA oligomers. In this report, we focused on the chemical synthesis of DNA oligomers labeled at specific residue(s). RNA oligomers with specific labels, which are difficult to synthesize by the enzyme method, can be synthesized by the chemical method. The specific labels are useful for conformational analysis of larger molecules such as protein-nucleic acid complexes.

Application of random coherence order selection in gradient-enhanced multidimensional NMR

International Nuclear Information System (INIS)

Bostock, Mark J.; Nietlispach, Daniel

2016-01-01

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1 -norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1 -norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended

Psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of Chilean university students

Directory of Open Access Journals (Sweden)

Berta Schnettler

2017-07-01

Full Text Available The Multidimensional Students’ Life Satisfaction Scale is an instrument to assess life satisfaction in children and adolescents in five life domains. However, research on multidimensional life satisfaction in older students, such as those attending university, is still scarce. This paper undertook to evaluate the psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of university students from five state universities in Chile. The Multidimensional Students’ Life Satisfaction Scale and Satisfaction with Life Scale were applied to 369 participants. Confirmatory factor analysis was used to evaluate the expected correlated five-factor model of the long version (40 items and the abbreviated version (30 items of the Multidimensional Students’ Life Satisfaction Scale. The goodness-of-fit values obtained from confirmatory factor analysis revealed that the data fit better to the 30-items and five-factor structure than to the 40-item structure. The convergent, concurrent and discriminant validity of the 30-item version was demonstrated. The 30-item version of the Multidimensional Students’ Life Satisfaction Scale may be a promising alternative to measure satisfaction in different life domains in university students, and a valuable tool for differential assessments that guide research and intervention on this population.

Manifold Regularized Correlation Object Tracking

OpenAIRE

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2017-01-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

Applied multidimensional systems theory

CERN Document Server

Bose, Nirmal K

2017-01-01

Revised and updated, this concise new edition of the pioneering book on multidimensional signal processing is ideal for a new generation of students. Multidimensional systems or m-D systems are the necessary mathematical background for modern digital image processing with applications in biomedicine, X-ray technology and satellite communications. Serving as a firm basis for graduate engineering students and researchers seeking applications in mathematical theories, this edition eschews detailed mathematical theory not useful to students. Presentation of the theory has been revised to make it more readable for students, and introduce some new topics that are emerging as multidimensional DSP topics in the interdisciplinary fields of image processing. New topics include Groebner bases, wavelets, and filter banks.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

SQL and Multidimensional Data

Directory of Open Access Journals (Sweden)

Mihaela MUNTEAN

2006-01-01

Full Text Available Using SQL you can manipulate multidimensional data and extract that data into a relational table. There are many PL/SQL packages that you can use directly in SQL*Plus or indirectly in Analytic Workspace Manager and OLAP Worksheet. In this article I discussed about some methods that you can use for manipulating and extracting multidimensional data.

Multi-dimensional database design and implementation of dam safety monitoring system

Directory of Open Access Journals (Sweden)

Zhao Erfeng

2008-09-01

Full Text Available To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design was achieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

Multidimensional Databases and Data Warehousing

CERN Document Server

Jensen, Christian

2010-01-01

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes data cubes and their elements, such as dimensions, facts, and measures and their representation in a relational setting; it includes architecture-related concepts; and it includes the querying of multidimensional databases.The book also covers advanced multidimensional concepts that are considered to b

The necessity-concerns framework: a multidimensional theory benefits from multidimensional analysis.

Science.gov (United States)

Phillips, L Alison; Diefenbach, Michael A; Kronish, Ian M; Negron, Rennie M; Horowitz, Carol R

2014-08-01

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity beliefs on their adherence to stroke-prevention medication. Survivors (n = 600) rated their concerns, necessity beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. As posited by the necessity-concerns framework (NCF), the greatest and lowest adherence was reported by those necessity weak concerns and strong concerns/weak Necessity-Beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

Mechanical properties of regular hexahedral lattice structure formed by selective laser melting

International Nuclear Information System (INIS)

Sun, Jianfeng; Yang, Yongqiang; Wang, Di

2013-01-01

The Ti–6Al–4V lattice structure is widely used in the aerospace field. This research first designs a regular hexahedral unit, processes the lattice structure composed of the Ti–6Al–4V units by selective laser melting technology, obtains the experimental fracture load and the compression deformation of them through compression tests, then conducts a simulation of the unit and the lattice structure through ANSYS to analyze the failure point. Later, according to the force condition of the point, the model of maximum load is built, through which the analytical formula of the fracture load of the unit and the lattice structure are obtained. The results of groups of experiments demonstrate that there exists an exponential relationship between the practical fracture load and the porosity of the lattice structure. There also exists a trigonometric function relationship between the compression deformation and the porosity of the lattice structure. The fracture analysis indicates that fracture of the units and lattice structure is brittle fracture due to cleavage fracture. (paper)

Multi-dimensional imaging

CERN Document Server

Javidi, Bahram; Andres, Pedro

2014-01-01

Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and

Rapid prediction of multi-dimensional NMR data sets

International Nuclear Information System (INIS)

Gradmann, Sabine; Ader, Christian; Heinrich, Ines; Nand, Deepak; Dittmann, Marc; Cukkemane, Abhishek; Dijk, Marc van; Bonvin, Alexandre M. J. J.; Engelhard, Martin; Baldus, Marc

2012-01-01

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such “in silico” data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAShttp://www.wenmr.eu/services/FANDAS).

Rapid prediction of multi-dimensional NMR data sets

Energy Technology Data Exchange (ETDEWEB)

Gradmann, Sabine; Ader, Christian [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Heinrich, Ines [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Nand, Deepak [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Dittmann, Marc [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Cukkemane, Abhishek; Dijk, Marc van; Bonvin, Alexandre M. J. J. [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Engelhard, Martin [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Baldus, Marc, E-mail: m.baldus@uu.nl [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands)

2012-12-15

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such 'in silico' data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAShttp://www.wenmr.eu/services/FANDAS).

[Clustered regularly interspaced short palindromic repeats: structure, function and application--a review].

Science.gov (United States)

Cui, Yujun; Li, Yanjun; Yan, Yanfeng; Yang, Ruifu

2008-11-01

CRISPRs (Clustered Regularly Interspaced Short Palindromic Repeats), the basis of spoligotyping technology, can provide prokaryotes with heritable adaptive immunity against phages' invasion. Studies on CRISPR loci and their associated elements, including various CAS (CRISPR-associated) proteins and leader sequences, are still in its infant period. We introduce the brief history', structure, function, bioinformatics research and application of this amazing immunity system in prokaryotic organism for inspiring more scientists to find their interest in this developing topic.

University Students' Knowledge Structures and Informal Reasoning on the Use of Genetically Modified Foods: Multidimensional Analyses

Science.gov (United States)

Wu, Ying-Tien

2013-10-01

This study aims to provide insights into the role of learners' knowledge structures about a socio-scientific issue (SSI) in their informal reasoning on the issue. A total of 42 non-science major university students' knowledge structures and informal reasoning were assessed with multidimensional analyses. With both qualitative and quantitative analyses, this study revealed that those students with more extended and better-organized knowledge structures, as well as those who more frequently used higher-order information processing modes, were more oriented towards achieving a higher-level informal reasoning quality. The regression analyses further showed that the "richness" of the students' knowledge structures explained 25 % of the variation in their rebuttal construction, an important indicator of reasoning quality, indicating the significance of the role of students' sophisticated knowledge structure in SSI reasoning. Besides, this study also provides some initial evidence for the significant role of the "core" concept within one's knowledge structure in one's SSI reasoning. The findings in this study suggest that, in SSI-based instruction, science instructors should try to identify students' core concepts within their prior knowledge regarding the SSI, and then they should try to guide students to construct and structure relevant concepts or ideas regarding the SSI based on their core concepts. Thus, students could obtain extended and well-organized knowledge structures, which would then help them achieve better learning transfer in dealing with SSIs.

Some regularity of the grain size distribution in nuclear fuel with controllable structure

International Nuclear Information System (INIS)

Loktev, Igor

2008-01-01

It is known, the fission gas release from ceramic nuclear fuel depends from average size of grains. To increase grain size they use additives which activate sintering of pellets. However, grain size distribution influences on fission gas release also. Fuel with different structures, but with the same average size of grains has different fission gas release. Other structure elements, which influence operational behavior of fuel, are pores and inclusions. Earlier, in Kyoto, questions of distribution of grain size for fuel with 'natural' structure were discussed. Some regularity of grain size distribution of fuel with controllable structure and high average size of grains are considered in the report. Influence of inclusions and pores on an error of the automated definition of parameters of structure is shown. The criterion, which describe of behavior of fuel with specific grain size distribution, is offered

Traveling in the dark: the legibility of a regular and predictable structure of the environment extends beyond its borders.

Science.gov (United States)

Yaski, Osnat; Portugali, Juval; Eilam, David

2012-04-01

The physical structure of the surrounding environment shapes the paths of progression, which in turn reflect the structure of the environment and the way that it shapes behavior. A regular and coherent physical structure results in paths that extend over the entire environment. In contrast, irregular structure results in traveling over a confined sector of the area. In this study, rats were tested in a dark arena in which half the area contained eight objects in a regular grid layout, and the other half contained eight objects in an irregular layout. In subsequent trials, a salient landmark was placed first within the irregular half, and then within the grid. We hypothesized that rats would favor travel in the area with regular order, but found that activity in the area with irregular object layout did not differ from activity in the area with grid layout, even when the irregular half included a salient landmark. Thus, the grid impact in one arena half extended to the other half and overshadowed the presumed impact of the salient landmark. This could be explained by mechanisms that control spatial behavior, such as grid cells and odometry. However, when objects were spaced irregularly over the entire arena, the salient landmark became dominant and the paths converged upon it, especially from objects with direct access to the salient landmark. Altogether, three environmental properties: (i) regular and predictable structure; (ii) salience of landmarks; and (iii) accessibility, hierarchically shape the paths of progression in a dark environment. Copyright © 2012 Elsevier B.V. All rights reserved.

Testlet-Based Multidimensional Adaptive Testing.

Science.gov (United States)

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Testlet-based Multidimensional Adaptive Testing

Directory of Open Access Journals (Sweden)

Andreas Frey

2016-11-01

Full Text Available Multidimensional adaptive testing (MAT is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT. MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, 1.5 and testlet sizes (3 items, 6 items, 9 items with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Evidence for a Multidimensional Self-Efficacy for Exercise Scale

Science.gov (United States)

Rodgers, W. M.; Wilson, P. M.; Hall, C. R.; Fraser, S. N.; Murray, T. C.

2008-01-01

This series of three studies considers the multidimensionality of exercise self-efficacy by examining the psychometric characteristics of an instrument designed to assess three behavioral subdomains: task, scheduling, and coping. In Study 1, exploratory factor analysis revealed the expected factor structure in a sample of 395 students.…

Multidimensional structure of a questionnaire to assess barriers to and motivators of physical activity in recipients of solid organ transplantation.

Science.gov (United States)

van Adrichem, Edwin J; Krijnen, Wim P; Dekker, Rienk; Ranchor, Adelita V; Dijkstra, Pieter U; van der Schans, Cees P

2017-11-01

To explore the underlying dimensions of the Barriers and Motivators Questionnaire that is used to assess barriers to and motivators of physical activity experienced by recipients of solid organ transplantation and thereby improve the application in research and clinical settings. A cross-sectional study was performed in recipients of solid organ transplantation (n = 591; median (IQR) age = 59 (49; 66); 56% male). The multidimensional structure of the questionnaire was analyzed by exploratory principal component analysis. Cronbach's α was calculated to determine internal consistency of the entire questionnaire and individual components. The barriers scale had a Cronbach's α of 0.86 and was subdivided into four components; α of the corresponding subscales varied between 0.80 and 0.66. The motivator scale had an α of 0.91 and was subdivided into four components with an α between 0.88 to 0.70. Nine of the original barrier items and two motivator items were not included in the component structure. A four-dimensional structure for both the barriers and motivators scale of the questionnaire is supported. The use of the indicated subscales increases the usability in research and clinical settings compared to the overall scores and provide opportunities to identify modifiable constructs to be targeted in interventions. Implications for rehabilitation Organ transplant recipients are less active than the general population despite established health benefits of physical activity. A multidimensional structure is shown in the Barriers and Motivators Questionnaire, the use of the identified subscales increases applicability in research and clinical settings. The use of the questionnaire with its component structure in the clinical practice of a rehabilitation physician could result in a faster assessment of problem areas in daily practice and result in a higher degree of clarity as opposed to the use of the individual items of the questionnaire.

UNFOLDED REGULAR AND SEMI-REGULAR POLYHEDRA

Directory of Open Access Journals (Sweden)

IONIŢĂ Elena

2015-06-01

Full Text Available This paper proposes a presentation unfolding regular and semi-regular polyhedra. Regular polyhedra are convex polyhedra whose faces are regular and equal polygons, with the same number of sides, and whose polyhedral angles are also regular and equal. Semi-regular polyhedra are convex polyhedra with regular polygon faces, several types and equal solid angles of the same type. A net of a polyhedron is a collection of edges in the plane which are the unfolded edges of the solid. Modeling and unfolding Platonic and Arhimediene polyhedra will be using 3dsMAX program. This paper is intended as an example of descriptive geometry applications.

Multidimensional upwind hydrodynamics on unstructured meshes using graphics processing units - I. Two-dimensional uniform meshes

Science.gov (United States)

Paardekooper, S.-J.

2017-08-01

We present a new method for numerical hydrodynamics which uses a multidimensional generalization of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidimensional integration, is its inherently multidimensional nature, and as a consequence its ability to recognize multidimensional stationary states that are not hydrostatic. A second novelty is the focus on graphics processing units (GPUs). By tailoring the algorithms specifically to GPUs, we are able to get speedups of 100-250 compared to a desktop machine. We compare the multidimensional upwind scheme to a traditional, dimensionally split implementation of the Roe solver on several test problems, and we find that the new method significantly outperforms the Roe solver in almost all cases. This comes with increased computational costs per time-step, which makes the new method approximately a factor of 2 slower than a dimensionally split scheme acting on a structured grid.

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

Science.gov (United States)

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

Extending Validity Evidence for Multidimensional Measures of Coaching Competency

Science.gov (United States)

Myers, Nicholas D.; Wolfe, Edward W.; Maier, Kimberly S.; Feltz, Deborah L.; Reckase, Mark D.

2006-01-01

This study extended validity evidence for multidimensional measures of coaching competency derived from the Coaching Competency Scale (CCS; Myers, Feltz, Maier, Wolfe, & Reckase, 2006) by examining use of the original rating scale structure and testing how measures related to satisfaction with the head coach within teams and between teams.…

Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models

Directory of Open Access Journals (Sweden)

Marius Pesavento

2004-08-01

Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.

Manifold Regularized Correlation Object Tracking.

Science.gov (United States)

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2018-05-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

arXiv Describing dynamical fluctuations and genuine correlations by Weibull regularity

CERN Document Server

Nayak, Ranjit K.; Sarkisyan-Grinbaum, Edward K.; Tasevsky, Marek

The Weibull parametrization of the multiplicity distribution is used to describe the multidimensional local fluctuations and genuine multiparticle correlations measured by OPAL in the large statistics $e^{+}e^{-} \\to Z^{0} \\to hadrons$ sample. The data are found to be well reproduced by the Weibull model up to higher orders. The Weibull predictions are compared to the predictions by the two other models, namely by the negative binomial and modified negative binomial distributions which mostly failed to fit the data. The Weibull regularity, which is found to reproduce the multiplicity distributions along with the genuine correlations, looks to be the optimal model to describe the multiparticle production process.

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

A Multidimensional Partial Credit Model with Associated Item and Test Statistics: An Application to Mixed-Format Tests

Science.gov (United States)

Yao, Lihua; Schwarz, Richard D.

2006-01-01

Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…

Multidimensional singular integrals and integral equations

CERN Document Server

Mikhlin, Solomon Grigorievich; Stark, M; Ulam, S

1965-01-01

Multidimensional Singular Integrals and Integral Equations presents the results of the theory of multidimensional singular integrals and of equations containing such integrals. Emphasis is on singular integrals taken over Euclidean space or in the closed manifold of Liapounov and equations containing such integrals. This volume is comprised of eight chapters and begins with an overview of some theorems on linear equations in Banach spaces, followed by a discussion on the simplest properties of multidimensional singular integrals. Subsequent chapters deal with compounding of singular integrals

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

Science.gov (United States)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Evaluation of content validity for the FACT-G quality of life questionaire through multidimensional escalation techniques

International Nuclear Information System (INIS)

Sanchez, Ricardo; Ballesteros, Monica; Ortiz, Natascha

2010-01-01

Objective: To evaluate the structure of FACT-G latent variables in a sample of patients attending the National Cancer Institute of Colombia Methods: The FACT-G questionnaire was applied in 473 patients with different types of cancer during 2005-2007. A factor analysis was done based on a polychoric matrix and multidimensional escalation techniques for ordinal variables determining the domain structure of the questionnaire. Results: Breast and prostate cancer were the most frequent types of tumors. In total 54.6% were men and the mean age was 61 years (SD 11.7). The four domains of the questionnaire revealed a similar score. The factor analysis showed a similar structure to the original FACT-G with the emotional function as the less consistent domain. According to the multidimensional escalation analysis, a bidimensional structure is suitable after different adjustment indexes. Only the emotional function domain exposed a heterogeneous structure; the remaining revealed clustered structures and independence among them. Central components for quality of life were functional well-being and social/family well-being. Conclusions: The FACT-G quality of life questionnaire applied in a sample of Colombian patients was consistent wit the original instrument. The multidimensional escalation techniques provide additional information to conventional analysis and are useful to validate quality of life questionnaires.

Sample Heterogeneity and the Measurement Structure of the Multidimensional Students' Life Satisfaction Scale

Science.gov (United States)

Sawatzky, Richard; Ratner, Pamela A.; Johnson, Joy L.; Kopec, Jacek A.; Zumbo, Bruno D.

2009-01-01

Several measurement assumptions were examined with the goal of assessing the validity of the Multidimensional Students' Life Satisfaction Scale (MSLSS), a measure of adolescents' satisfaction with their family, friends, living environment, school, self, and general quality of life. The data were obtained via a cross-sectional survey of 8,225…

Multidimensional Data Model and Query Language for Informetrics.

Science.gov (United States)

Niemi, Timo; Hirvonen, Lasse; Jarvelin, Kalervo

2003-01-01

Discusses multidimensional data analysis, or online analytical processing (OLAP), which offer a single subject-oriented source for analyzing summary data based on various dimensions. Develops a conceptual/logical multidimensional model for supporting the needs of informetrics, including a multidimensional query language whose basic idea is to…

Stochastic Simulation of Chloride Ingress into Reinforced Concrete Structures by Means of Multi-Dimensional Gaussian Random Fields

DEFF Research Database (Denmark)

Frier, Christian; Sørensen, John Dalsgaard

2005-01-01

For many reinforced concrete structures corrosion of the reinforcement is an important problem since it can result in expensive maintenance and repair actions. Further, a significant reduction of the load-bearing capacity can occur. One mode of corrosion initiation occurs when the chloride content...... is modeled by a 2-dimensional diffusion process by FEM (Finite Element Method) and the diffusion coefficient, surface chloride concentration and reinforcement cover depth are modeled by multidimensional stochastic fields, which are discretized using the EOLE (Expansion Optimum Linear Estimation) approach....... As an example a bridge pier in a marine environment is considered and the results are given in terms of the distribution of the time for initialization of corrosion...

Multidimensional (OLAP) Analysis for Designing Dynamic Learning Strategy

Science.gov (United States)

Rozeva, A.; Deliyska, B.

2010-10-01

Learning strategy in an intelligent learning system is generally elaborated on the basis of assessment of the following factors: learner's time for reaction, content of the learning object, amount of learning material in a learning object, learning object specification, e-learning medium and performance control. Current work proposes architecture for dynamic learning strategy design by implementing multidimensional analysis model of learning factors. The analysis model concerns on-line analytical processing (OLAP) of learner's data structured as multidimensional cube. Main components of the architecture are analysis agent for performing the OLAP operations on learner data cube, adaptation generator and knowledge selection agent for performing adaptive navigation in the learning object repository. The output of the analysis agent is involved in dynamic elaboration of learning strategy that fits best to learners profile and behavior. As a result an adaptive learning path for individual learner and for learner groups is generated.

Seismic interferometry by multidimensional deconvolution as a means to compensate for anisotropic illumination

Science.gov (United States)

Wapenaar, K.; van der Neut, J.; Ruigrok, E.; Draganov, D.; Hunziker, J.; Slob, E.; Thorbecke, J.; Snieder, R.

2008-12-01

It is well-known that under specific conditions the crosscorrelation of wavefields observed at two receivers yields the impulse response between these receivers. This principle is known as 'Green's function retrieval' or 'seismic interferometry'. Recently it has been recognized that in many situations it can be advantageous to replace the correlation process by deconvolution. One of the advantages is that deconvolution compensates for the waveform emitted by the source; another advantage is that it is not necessary to assume that the medium is lossless. The approaches that have been developed to date employ a 1D deconvolution process. We propose a method for seismic interferometry by multidimensional deconvolution and show that under specific circumstances the method compensates for irregularities in the source distribution. This is an important difference with crosscorrelation methods, which rely on the condition that waves are equipartitioned. This condition is for example fulfilled when the sources are regularly distributed along a closed surface and the power spectra of the sources are identical. The proposed multidimensional deconvolution method compensates for anisotropic illumination, without requiring knowledge about the positions and the spectra of the sources.

Formation Mechanism and Binding Energy for Body-Centred Regular Icosahedral Structure of Li13 Cluster

International Nuclear Information System (INIS)

Liu Weina; Li Ping; Gou Qingquan; Zhao Yanping

2008-01-01

The formation mechanism for the body-centred regular icosahedral structure of Li 13 cluster is proposed. The curve of the total energy versus the separation R between the nucleus at the centre and nuclei at the apexes for this structure of Li 13 has been calculated by using the method of Gou's modified arrangement channel quantum mechanics (MACQM). The result shows that the curve has a minimal energy of -96.951 39 a.u. at R = 5.46a 0 . When R approaches to infinity, the total energy of thirteen lithium atoms has the value of -96.564 38 a.u. So the binding energy of Li 13 with respect to thirteen lithium atoms is 0.387 01 a.u. Therefore the binding energy per atom for Li 13 is 0.029 77 a.u. or 0.810 eV, which is greater than the binding energy per atom of 0.453 eV for Li 2 , 0.494 eV for Li 3 , 0.7878 eV for Li 4 , 0.632 eV for Li 5 , and 0.674 eV for Li 7 calculated by us previously. This means that the Li 13 cluster may be formed stably in a body-centred regular icosahedral structure with a greater binding energy

CAMS: OLAPing Multidimensional Data Streams Efficiently

Science.gov (United States)

Cuzzocrea, Alfredo

In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.

[Multidimensional family therapy: which influences, which specificities?].

Science.gov (United States)

Bonnaire, C; Bastard, N; Couteron, J-P; Har, A; Phan, O

2014-10-01

Among illegal psycho-active drugs, cannabis is the most consumed by French adolescents. Multidimensional family therapy (MDFT) is a family-based outpatient therapy which has been developed for adolescents with drug and behavioral problems. MDFT has shown its effectiveness in adolescents with substance abuse disorders (notably cannabis abuse) not only in the United States but also in Europe (International Cannabis Need of Treatment project). MDFT is a multidisciplinary approach and an evidence-based treatment, at the crossroads of developmental psychology, ecological theories and family therapy. Its psychotherapeutic techniques find its roots in a variety of approaches which include systemic family therapy and cognitive therapy. The aims of this paper are: to describe all the backgrounds of MDFT by highlighting its characteristics; to explain how structural and strategy therapies have influenced this approach; to explore the links between MDFT, brief strategic family therapy and multi systemic family therapy; and to underline the specificities of this family therapy method. The multidimensional family therapy was created on the bases of 1) the integration of multiple therapeutic techniques stemming from various family therapy theories; and 2) studies which have shown family therapy efficiency. Several trials have shown a better efficiency of MDFT compared to group treatment, cognitive-behavioral therapy and home-based treatment. Studies have also highlighted that MDFT led to superior treatment outcomes, especially among young people with severe drug use and psychiatric co-morbidities. In the field of systemic family therapies, MDFT was influenced by: 1) the structural family therapy (S. Minuchin), 2) the strategic family theory (J. Haley), and 3) the intergenerational family therapy (Bowen and Boszormenyi-Nagy). MDFT has specific aspects: MDFT therapists think in a multidimensional perspective (because an adolescent's drug abuse is a multidimensional disorder), they

On the MSE Performance and Optimization of Regularized Problems

KAUST Repository

Alrashdi, Ayed

2016-11-01

The amount of data that has been measured, transmitted/received, and stored in the recent years has dramatically increased. So, today, we are in the world of big data. Fortunately, in many applications, we can take advantages of possible structures and patterns in the data to overcome the curse of dimensionality. The most well known structures include sparsity, low-rankness, block sparsity. This includes a wide range of applications such as machine learning, medical imaging, signal processing, social networks and computer vision. This also led to a specific interest in recovering signals from noisy compressed measurements (Compressed Sensing (CS) problem). Such problems are generally ill-posed unless the signal is structured. The structure can be captured by a regularizer function. This gives rise to a potential interest in regularized inverse problems, where the process of reconstructing the structured signal can be modeled as a regularized problem. This thesis particularly focuses on finding the optimal regularization parameter for such problems, such as ridge regression, LASSO, square-root LASSO and low-rank Generalized LASSO. Our goal is to optimally tune the regularizer to minimize the mean-squared error (MSE) of the solution when the noise variance or structure parameters are unknown. The analysis is based on the framework of the Convex Gaussian Min-max Theorem (CGMT) that has been used recently to precisely predict performance errors.

Structural analysis and biological activity of a highly regular glycosaminoglycan from Achatina fulica.

Science.gov (United States)

Liu, Jie; Zhou, Lutan; He, Zhicheng; Gao, Na; Shang, Feineng; Xu, Jianping; Li, Zi; Yang, Zengming; Wu, Mingyi; Zhao, Jinhua

2018-02-01

Edible snails have been widely used as a health food and medicine in many countries. A unique glycosaminoglycan (AF-GAG) was purified from Achatina fulica. Its structure was analyzed and characterized by chemical and instrumental methods, such as Fourier transform infrared spectroscopy, analysis of monosaccharide composition, and 1D/2D nuclear magnetic resonance spectroscopy. Chemical composition analysis indicated that AF-GAG is composed of iduronic acid (IdoA) and N-acetyl-glucosamine (GlcNAc) and its average molecular weight is 118kDa. Structural analysis clarified that the uronic acid unit in glycosaminoglycan (GAG) is the fully epimerized and the sequence of AF-GAG is →4)-α-GlcNAc (1→4)-α-IdoA2S (1→. Although its structure with a uniform repeating disaccharide is similar to those of heparin and heparan sulfate, this GAG is structurally highly regular and homogeneous. Anticoagulant activity assays indicated that AF-GAG exhibits no anticoagulant activities, but considering its structural characteristic, other bioactivities such as heparanase inhibition may be worthy of further study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multidimensional poverty, household environment and short-term morbidity in India.

Science.gov (United States)

Dehury, Bidyadhar; Mohanty, Sanjay K

2017-01-01

Using the unit data from the second round of the Indian Human Development Survey (IHDS-II), 2011-2012, which covered 42,152 households, this paper examines the association between multidimensional poverty, household environmental deprivation and short-term morbidities (fever, cough and diarrhoea) in India. Poverty is measured in a multidimensional framework that includes the dimensions of education, health and income, while household environmental deprivation is defined as lack of access to improved sanitation, drinking water and cooking fuel. A composite index combining multidimensional poverty and household environmental deprivation has been computed, and households are classified as follows: multidimensional poor and living in a poor household environment, multidimensional non-poor and living in a poor household environment, multidimensional poor and living in a good household environment and multidimensional non-poor and living in a good household environment. Results suggest that about 23% of the population belonging to multidimensional poor households and living in a poor household environment had experienced short-term morbidities in a reference period of 30 days compared to 20% of the population belonging to multidimensional non-poor households and living in a poor household environment, 19% of the population belonging to multidimensional poor households and living in a good household environment and 15% of the population belonging to multidimensional non-poor households and living in a good household environment. Controlling for socioeconomic covariates, the odds of short-term morbidity was 1.47 [CI 1.40-1.53] among the multidimensional poor and living in a poor household environment, 1.28 [CI 1.21-1.37] among the multidimensional non-poor and living in a poor household environment and 1.21 [CI 1.64-1.28] among the multidimensional poor and living in a good household environment compared to the multidimensional non-poor and living in a good household

Analysis of regularized Navier-Stokes equations, 2

Science.gov (United States)

Ou, Yuh-Roung; Sritharan, S. S.

1989-01-01

A practically important regularization of the Navier-Stokes equations was analyzed. As a continuation of the previous work, the structure of the attractors characterizing the solutins was studied. Local as well as global invariant manifolds were found. Regularity properties of these manifolds are analyzed.

Cross-Cultural Validity of the Frost Multidimensional Perfectionism Scale in Korea

Science.gov (United States)

Lee, Dong-gwi; Park, Hyun-joo

2011-01-01

This study with 213 South Korean college students (113 men) examined the cross-cultural generalizability of (a) the factor structure of the Frost Multidimensional Perfectionism Scale (F-MPS) and (b) the existence of adaptive perfectionists, maladaptive perfectionists, and nonperfectionists. A confirmatory factor analysis did not support the…

Regularities of radiation heredity

International Nuclear Information System (INIS)

Skakov, M.K.; Melikhov, V.D.

2001-01-01

One analyzed regularities of radiation heredity in metals and alloys. One made conclusion about thermodynamically irreversible changes in structure of materials under irradiation. One offers possible ways of heredity transmittance of radiation effects at high-temperature transformations in the materials. Phenomenon of radiation heredity may be turned to practical use to control structure of liquid metal and, respectively, structure of ingot via preliminary radiation treatment of charge. Concentration microheterogeneities in material defect structure induced by preliminary irradiation represent the genetic factor of radiation heredity [ru

Consistent Partial Least Squares Path Modeling via Regularization.

Science.gov (United States)

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Consistent Partial Least Squares Path Modeling via Regularization

Directory of Open Access Journals (Sweden)

Sunho Jung

2018-02-01

Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Metric regularity and subdifferential calculus

International Nuclear Information System (INIS)

Ioffe, A D

2000-01-01

The theory of metric regularity is an extension of two classical results: the Lyusternik tangent space theorem and the Graves surjection theorem. Developments in non-smooth analysis in the 1980s and 1990s paved the way for a number of far-reaching extensions of these results. It was also well understood that the phenomena behind the results are of metric origin, not connected with any linear structure. At the same time it became clear that some basic hypotheses of the subdifferential calculus are closely connected with the metric regularity of certain set-valued maps. The survey is devoted to the metric theory of metric regularity and its connection with subdifferential calculus in Banach spaces

Multidimensional quantum entanglement with large-scale integrated optics.

Science.gov (United States)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

[Intraoperative multidimensional visualization].

Science.gov (United States)

Sperling, J; Kauffels, A; Grade, M; Alves, F; Kühn, P; Ghadimi, B M

2016-12-01

Modern intraoperative techniques of visualization are increasingly being applied in general and visceral surgery. The combination of diverse techniques provides the possibility of multidimensional intraoperative visualization of specific anatomical structures. Thus, it is possible to differentiate between normal tissue and tumor tissue and therefore exactly define tumor margins. The aim of intraoperative visualization of tissue that is to be resected and tissue that should be spared is to lead to a rational balance between oncological and functional results. Moreover, these techniques help to analyze the physiology and integrity of tissues. Using these methods surgeons are able to analyze tissue perfusion and oxygenation. However, to date it is not clear to what extent these imaging techniques are relevant in the clinical routine. The present manuscript reviews the relevant modern visualization techniques focusing on intraoperative computed tomography and magnetic resonance imaging as well as augmented reality, fluorescence imaging and optoacoustic imaging.

Multidimensional Poverty and Child Survival in India

Science.gov (United States)

Mohanty, Sanjay K.

2011-01-01

Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

Multidimensional poverty and child survival in India.

Directory of Open Access Journals (Sweden)

Sanjay K Mohanty

Full Text Available Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

Multidimensional poverty and child survival in India.

Science.gov (United States)

Mohanty, Sanjay K

2011-01-01

Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

On the regularized fermionic projector of the vacuum

Science.gov (United States)

Finster, Felix

2008-03-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed.

On the regularized fermionic projector of the vacuum

International Nuclear Information System (INIS)

Finster, Felix

2008-01-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed

Method of data mining including determining multidimensional coordinates of each item using a predetermined scalar similarity value for each item pair

Science.gov (United States)

Meyers, Charles E.; Davidson, George S.; Johnson, David K.; Hendrickson, Bruce A.; Wylie, Brian N.

1999-01-01

A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.

Optimal Tikhonov Regularization in Finite-Frequency Tomography

Science.gov (United States)

Fang, Y.; Yao, Z.; Zhou, Y.

2017-12-01

The last decade has witnessed a progressive transition in seismic tomography from ray theory to finite-frequency theory which overcomes the resolution limit of the high-frequency approximation in ray theory. In addition to approximations in wave propagation physics, a main difference between ray-theoretical tomography and finite-frequency tomography is the sparseness of the associated sensitivity matrix. It is well known that seismic tomographic problems are ill-posed and regularizations such as damping and smoothing are often applied to analyze the tradeoff between data misfit and model uncertainty. The regularizations depend on the structure of the matrix as well as noise level of the data. Cross-validation has been used to constrain data uncertainties in body-wave finite-frequency inversions when measurements at multiple frequencies are available to invert for a common structure. In this study, we explore an optimal Tikhonov regularization in surface-wave phase-velocity tomography based on minimization of an empirical Bayes risk function using theoretical training datasets. We exploit the structure of the sensitivity matrix in the framework of singular value decomposition (SVD) which also allows for the calculation of complete resolution matrix. We compare the optimal Tikhonov regularization in finite-frequency tomography with traditional tradeo-off analysis using surface wave dispersion measurements from global as well as regional studies.

Diverse Regular Employees and Non-regular Employment (Japanese)

OpenAIRE

MORISHIMA Motohiro

2011-01-01

Currently there are high expectations for the introduction of policies related to diverse regular employees. These policies are a response to the problem of disparities between regular and non-regular employees (part-time, temporary, contract and other non-regular employees) and will make it more likely that workers can balance work and their private lives while companies benefit from the advantages of regular employment. In this paper, I look at two issues that underlie this discussion. The ...

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

Science.gov (United States)

Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie

2008-06-01

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

Front propagation in a regular vortex lattice: Dependence on the vortex structure.

Science.gov (United States)

Beauvier, E; Bodea, S; Pocheau, A

2017-11-01

We investigate the dependence on the vortex structure of the propagation of fronts in stirred flows. For this, we consider a regular set of vortices whose structure is changed by varying both their boundary conditions and their aspect ratios. These configurations are investigated experimentally in autocatalytic solutions stirred by electroconvective flows and numerically from kinematic simulations based on the determination of the dominant Fourier mode of the vortex stream function in each of them. For free lateral boundary conditions, i.e., in an extended vortex lattice, it is found that both the flow structure and the front propagation negligibly depend on vortex aspect ratios. For rigid lateral boundary conditions, i.e., in a vortex chain, vortices involve a slight dependence on their aspect ratios which surprisingly yields a noticeable decrease of the enhancement of front velocity by flow advection. These different behaviors reveal a sensitivity of the mean front velocity on the flow subscales. It emphasizes the intrinsic multiscale nature of front propagation in stirred flows and the need to take into account not only the intensity of vortex flows but also their inner structure to determine front propagation at a large scale. Differences between experiments and simulations suggest the occurrence of secondary flows in vortex chains at large velocity and large aspect ratios.

New method for solving multidimensional scattering problem

International Nuclear Information System (INIS)

Melezhik, V.S.

1991-01-01

A new method is developed for solving the quantum mechanical problem of scattering of a particle with internal structure. The multichannel scattering problem is formulated as a system of nonlinear functional equations for the wave function and reaction matrix. The method is successfully tested for the scattering from a nonspherical potential well and a long-range nonspherical scatterer. The method is also applicable to solving the multidimensional Schroedinger equation with a discrete spectrum. As an example the known problem of a hydrogen atom in a homogeneous magnetic field is analyzed

Multi-dimensional technology-enabled social learning approach

DEFF Research Database (Denmark)

Petreski, Hristijan; Tsekeridou, Sofia; Prasad, Neeli R.

2013-01-01

’t respond to this systemic and structural changes and/or challenges and retains its status quo than it is jeopardizing its own existence or the existence of the education, as we know it. This paper aims to precede one step further by proposing a multi-dimensional approach for technology-enabled social...... in learning while socializing within their learning communities. However, their “educational” usage is still limited to facilitation of online learning communities and to collaborative authoring of learning material complementary to existing formal (e-) learning services. If the educational system doesn...

Multidimensionality of thinking in the context of creativity studies.

Directory of Open Access Journals (Sweden)

Belolutskaya A.K.

2015-03-01

Full Text Available This article describes the theoretical difference between the flexibility and the multidimensionality of thinking. Multidimensionality is discussed as a characteristic of thinking that is necessary for exploration of the variability of structural transformations of problematic situations. The objective of the study was to examine a number of theories concerning the correlative connection between the multidimensionality of thinking and other characteristics of creative, productive thinking: the flexibility of thinking; the formation of an operation of dialectical thinking such as “mediation”; the ability of a person to use a scheme as an abstraction for analysis of various specific content. A total of 85 people participated in the study: they were 15 to 17 years old, students at a senior school in Kaliningradskaya oblast, winners of different stages of the all-Russian academic competition in physics, chemistry, and mathematics. All respondents had a high level of academic success and of general intelligence. The following techniques were used in this study: (1 my technique for diagnostics of the multidimensionality of thinking; (2 my technique of “schemes and paintings,” designed for diagnostics of the ability to relate abstract schemes and various specific content; (3 the Torrance Tests of Creative Thinking (verbal battery; (4 a diagnostic technique for dialectical thinking: “What can be simultaneous?” All the hypotheses were confirmed. Confirmation was received of the existence of a correlation connection; this finding counts in favor of the assumption that the parameters of thinking my colleagues and I were working with can in aggregate be considered an integral characteristic of human thinking. It allows us to distinguish significant features of a situation from secondary ones—that is, to see a substantial contradiction and to propose several options for its transformation.

Assessment of urban green space structures and their quality from a multidimensional perspective.

Science.gov (United States)

Daniels, Benjamin; Zaunbrecher, Barbara S; Paas, Bastian; Ottermanns, Richard; Ziefle, Martina; Roß-Nickoll, Martina

2018-02-15

Facing the growing amount of people living in cities and, at the same time, the need for a compact and sustainable urban development to mitigate urban sprawl, it becomes increasingly important that green spaces in compact cities are designed to meet the various needs within an urban environment. Urban green spaces have a multitude of functions: Maintaining ecological processes and resulting services, e.g. providing habitat for animals and plants, providing a beneficial city microclimate as well as recreational space for citizens. Regarding these requirements, currently existing assessment procedures for green spaces have some major shortcomings, which are discussed in this paper. It is argued why a more detailed spatial level as well as a distinction between natural and artificial varieties of structural elements is justified and needed and how the assessment of urban green spaces benefits from the multidimensional perspective that is applied. By analyzing a selection of structural elements from an ecological, microclimatic and social perspective, indicator values are derived and a new, holistic metrics 1 is proposed. The results of the integrated analysis led to two major findings: first, that for some elements, the evaluation differs to a great extent between the different perspectives (disciplines) and second, that natural and artificial varieties are, in most cases, evaluated considerably different from each other. The differences between the perspectives call for an integrative planning policy which acknowledges the varying contribution of a structural element to different purposes (ecological, microclimatic, social) as well as a discussion about the prioritization of those purposes. The differences in the evaluation of natural vs. artificial elements verify the assumption that indicators which consider only generic elements fail to account for those refinements and are thus less suitable for planning and assessment purposes. Implications, challenges and

The Impact of Computerization on Regular Employment (Japanese)

OpenAIRE

SUNADA Mitsuru; HIGUCHI Yoshio; ABE Masahiro

2004-01-01

This paper uses micro data from the Basic Survey of Japanese Business Structure and Activity to analyze the effects of companies' introduction of information and telecommunications technology on employment structures, especially regular versus non-regular employment. Firstly, examination of trends in the ratio of part-time workers recorded in the Basic Survey shows that part-time worker ratios in manufacturing firms are rising slightly, but that companies with a high proportion of part-timers...

Multidimensional fatigue and its correlates in hospitalised advanced cancer patients.

NARCIS (Netherlands)

Echteld, M.A.; Passchier, J.; Teunissen, S.; Claessen, S.; Wit, R. de; Rijt, C.C.D. van der

2007-01-01

Although fatigue is a multidimensional concept, multidimensional fatigue is rarely investigated in hospitalised cancer patients. We determined the levels and correlates of multidimensional fatigue in 100 advanced cancer patients admitted for symptom control. Fatigue dimensions were general fatigue

Multi-dimensional analysis of high resolution γ-ray data

International Nuclear Information System (INIS)

Flibotte, S.; Huttmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J.; Bednarczyk, P.

1992-01-01

High resolution γ-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8π spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig

Multi-dimensional analysis of high resolution {gamma}-ray data

Energy Technology Data Exchange (ETDEWEB)

Flibotte, S; Huttmeier, U J; France, G de; Haas, B; Romain, P; Theisen, Ch; Vivien, J P; Zen, J [Centre National de la Recherche Scientifique (CNRS), 67 - Strasbourg (France); Bednarczyk, P [Institute of Nuclear Physics, Cracow (Poland)

1992-08-01

High resolution {gamma}-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8{pi} spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig.

Measurement of multi-dimensional flow structure for flow boiling in a tube

International Nuclear Information System (INIS)

Adachi, Yu; Ito, Daisuke; Saito, Yasushi

2014-01-01

With an aim of the measurement of multi-dimensional flow structure of in-tube boiling two-phase flow, the authors built their own wire mesh measurement system based on electrical conductivity measurement, and examined the relationship between the electrical conductivity obtained by the wire mesh sensor and the void fraction. In addition, the authors measured the void fraction using neutron radiography, and compared the result with the measured value using the wire mesh sensor. From the comparison with neutron radiography, it was found that the new method underestimated the void fraction in the flow in the vicinity of the void fraction of 0.2-0.5, similarly to the conventional result. In addition, since the wire mesh sensor cannot measure dispersed droplets, it tends to overestimate the void fraction in the high void fraction region, such as churn flow accompanied by droplet generation. In the electrical conductivity wire-mesh sensor method, it is necessary to correctly take into account the effect of liquid film or droplets. The authors also built a measurement system based on the capacitance wire mesh sensor method using the difference in dielectric constant, performed the confirmation of transmission and reception signals using deionized water as a medium, and showed the validity of the system. As for the dispersed droplets, the capacitance method has a potential to be able to measure them. (A.O.)

Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

Science.gov (United States)

Xiao, Mengting; Li, Cheng

2018-01-01

Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

Construction of multidimensional models by operators of composition: current state of art

Czech Academy of Sciences Publication Activity Database

Jiroušek, Radim; Vejnarová, J.

2003-01-01

Roč. 7, č. 5 (2003), s. 328-335 ISSN 1432-7643 R&D Projects: GA ČR GA201/02/1269 Institutional research plan: CEZ:AV0Z1075907 Keywords : structured multidimensional models * probability distributions * possibility distributions Subject RIV: BA - General Mathematics Impact factor: 0.333, year: 2002

Laplacian manifold regularization method for fluorescence molecular tomography

Science.gov (United States)

He, Xuelei; Wang, Xiaodong; Yi, Huangjian; Chen, Yanrong; Zhang, Xu; Yu, Jingjing; He, Xiaowei

2017-04-01

Sparse regularization methods have been widely used in fluorescence molecular tomography (FMT) for stable three-dimensional reconstruction. Generally, ℓ1-regularization-based methods allow for utilizing the sparsity nature of the target distribution. However, in addition to sparsity, the spatial structure information should be exploited as well. A joint ℓ1 and Laplacian manifold regularization model is proposed to improve the reconstruction performance, and two algorithms (with and without Barzilai-Borwein strategy) are presented to solve the regularization model. Numerical studies and in vivo experiment demonstrate that the proposed Gradient projection-resolved Laplacian manifold regularization method for the joint model performed better than the comparative algorithm for ℓ1 minimization method in both spatial aggregation and location accuracy.

The persistence of the attentional bias to regularities in a changing environment.

Science.gov (United States)

Yu, Ru Qi; Zhao, Jiaying

2015-10-01

The environment often is stable, but some aspects may change over time. The challenge for the visual system is to discover and flexibly adapt to the changes. We examined how attention is shifted in the presence of changes in the underlying structure of the environment. In six experiments, observers viewed four simultaneous streams of objects while performing a visual search task. In the first half of each experiment, the stream in the structured location contained regularities, the shapes in the random location were randomized, and gray squares appeared in two neutral locations. In the second half, the stream in the structured or the random location may change. In the first half of all experiments, visual search was facilitated in the structured location, suggesting that attention was consistently biased toward regularities. In the second half, this bias persisted in the structured location when no change occurred (Experiment 1), when the regularities were removed (Experiment 2), or when new regularities embedded in the original or novel stimuli emerged in the previously random location (Experiments 3 and 6). However, visual search was numerically but no longer reliably faster in the structured location when the initial regularities were removed and new regularities were introduced in the previously random location (Experiment 4), or when novel random stimuli appeared in the random location (Experiment 5). This suggests that the attentional bias was weakened. Overall, the results demonstrate that the attentional bias to regularities was persistent but also sensitive to changes in the environment.

Symbolic Multidimensional Scaling

NARCIS (Netherlands)

P.J.F. Groenen (Patrick); Y. Terada

2015-01-01

markdownabstract__Abstract__ Multidimensional scaling (MDS) is a technique that visualizes dissimilarities between pairs of objects as distances between points in a low dimensional space. In symbolic MDS, a dissimilarity is not just a value but can represent an interval or even a histogram. Here,

Factor Structure and Initial Validation of a Multidimensional Measure of Difficulties in the Regulation of Positive Emotions: The DERS-Positive.

Science.gov (United States)

Weiss, Nicole H; Gratz, Kim L; Lavender, Jason M

2015-05-01

Emotion regulation difficulties are a transdiagnostic construct relevant to numerous clinical difficulties. Although the Difficulties in Emotion Regulation Scale (DERS) is a multidimensional measure of maladaptive ways of responding to emotions, it focuses on difficulties with the regulation of negative emotions and does not assess emotion dysregulation in the form of problematic responding to positive emotions. The aim of this study was to develop and validate a measure of clinically relevant difficulties in the regulation of positive emotions (DERS-Positive). Findings revealed a three-factor structure and supported the internal consistency and construct validity of the total and subscale scores. © The Author(s) 2015.

Perceptual Salience and Children's Multidimensional Problem Solving

Science.gov (United States)

Odom, Richard D.; Corbin, David W.

1973-01-01

Uni- and multidimensional processing of 6- to 9-year olds was studied using recall tasks in which an array of stimuli was reconstructed to match a model array. Results indicated that both age groups were able to solve multidimensional problems, but that solution rate was retarded by the unidimensional processing of highly salient dimensions.…

REGULARITIES AND MECHANISM OF FORMATION OF STRUCTURE OF THE MECHANICALLY ALLOYED COMPOSITIONS GROUND ON THE BASIS OF METAL SYSTEMS

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F. G. Lovshenko

2014-01-01

Full Text Available Experimentally determined regularities and mechanism of formation of structure of the mechanically alloyed compositions foundations on the basis of the widely applied in mechanical engineering metals – iron, nickel, aluminum, copper are given. 

Multidimensional Measurement of Poverty among Women in Sub-Saharan Africa

Science.gov (United States)

Batana, Yele Maweki

2013-01-01

Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose…

Multidimensional Risk Management for Underground Electricity Networks

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Garcez Thalles V.

2014-08-01

Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

Application of multidimensional IRT models to longitudinal data

NARCIS (Netherlands)

te Marvelde, J.M.; Glas, Cornelis A.W.; Van Landeghem, Georges; Van Damme, Jan

2006-01-01

The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model

Multidimensional sexual perfectionism.

Science.gov (United States)

Stoeber, Joachim; Harvey, Laura N; Almeida, Isabel; Lyons, Emma

2013-11-01

Perfectionism is a multidimensional personality characteristic that can affect all areas of life. This article presents the first systematic investigation of multidimensional perfectionism in the domain of sexuality exploring the unique relationships that different forms of sexual perfectionism show with positive and negative aspects of sexuality. A sample of 272 university students (52 male, 220 female) completed measures of four forms of sexual perfectionism: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. In addition, they completed measures of sexual esteem, sexual self-efficacy, sexual optimism, sex life satisfaction (capturing positive aspects of sexuality) and sexual problem self-blame, sexual anxiety, sexual depression, and negative sexual perfectionism cognitions during sex (capturing negative aspects). Results showed unique patterns of relationships for the four forms of sexual perfectionism, suggesting that partner-prescribed and socially prescribed sexual perfectionism are maladaptive forms of sexual perfectionism associated with negative aspects of sexuality whereas self-oriented and partner-oriented sexual perfectionism emerged as ambivalent forms associated with positive and negative aspects.

Multidimensional real analysis I differentiation

CERN Document Server

Duistermaat, J J; van Braam Houckgeest, J P

2004-01-01

Part one of the authors' comprehensive and innovative work on multidimensional real analysis. This book is based on extensive teaching experience at Utrecht University and gives a thorough account of differential analysis in multidimensional Euclidean space. It is an ideal preparation for students who wish to go on to more advanced study. The notation is carefully organized and all proofs are clean, complete and rigorous. The authors have taken care to pay proper attention to all aspects of the theory. In many respects this book presents an original treatment of the subject and it contains man

Multidimensional First-Order Dominance Comparisons of Population Wellbeing

DEFF Research Database (Denmark)

Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave; Arndt, Thomas Channing

2017-01-01

This chapter conveys the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. It gives an account of the fundamental equivalent definitions of FOD both in the one-dimensional and multidimensional setting, illustrated...

Enhancing Low-Rank Subspace Clustering by Manifold Regularization.

Science.gov (United States)

Liu, Junmin; Chen, Yijun; Zhang, JiangShe; Xu, Zongben

2014-07-25

Recently, low-rank representation (LRR) method has achieved great success in subspace clustering (SC), which aims to cluster the data points that lie in a union of low-dimensional subspace. Given a set of data points, LRR seeks the lowest rank representation among the many possible linear combinations of the bases in a given dictionary or in terms of the data itself. However, LRR only considers the global Euclidean structure, while the local manifold structure, which is often important for many real applications, is ignored. In this paper, to exploit the local manifold structure of the data, a manifold regularization characterized by a Laplacian graph has been incorporated into LRR, leading to our proposed Laplacian regularized LRR (LapLRR). An efficient optimization procedure, which is based on alternating direction method of multipliers (ADMM), is developed for LapLRR. Experimental results on synthetic and real data sets are presented to demonstrate that the performance of LRR has been enhanced by using the manifold regularization.

Structural studies of the activation of the two component receiver domain NTRC by multidimensional heteronuclear NMR

Energy Technology Data Exchange (ETDEWEB)

Nohaile, Michael James [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry

1996-05-01

Multidimensional heteronuclear NMR spectroscopy was used to investigate the N-terminal domain of the transcriptional enhancer NTRC (NiTrogen Regulatory protein C). This domain belongs to the family of receiver domains of two-component regulatory systems involved in signal transduction. Phosphorylation of NTRC at D54 leads to an activated form of the molecule which stimulates transcription of genes involved in nitrogen regulation. Three and four dimensional NMR techniques were used to determine an intermediate resolution structure of the unphosphorylated, inactive form of the N-terminal domain of NTRC. The structure is comprised of five α-helices and a five-stranded β-sheet in a (β/α)₅ topology. Analysis of the backbone dynamics of NTRC indicate that helix 4 and strand 5 are significantly more flexible than the rest of the secondary structure of the protein and that the loops making up the active site are flexible. The short lifetime of phospho-NTRC hampers the study of this form. However, conditions for determining the resonance assignments and, possibly, the three dimensional structure of phosphorylated NTRC have been obtained. Tentative assignments of the phosphorylated form indicate that the majority of the changes that NTRC experiences upon phosphorylation occur in helix 3, strand 4, helix 4, strand 5, and the loop between strand 5 and helix 5 (the 3445 face of NTRC) as well as near the site of phosphorylation. In order to examine a stable, activated form of the protein, constitutively active mutants of NTRC were investigated.

A multidimensional subdiffusion model: An arbitrage-free market

International Nuclear Information System (INIS)

Li Guo-Hua; Zhang Hong; Luo Mao-Kang

2012-01-01

To capture the subdiffusive characteristics of financial markets, the subordinated process, directed by the inverse α-stale subordinator S α (t) for 0 < α < 1, has been employed as the model of asset prices. In this article, we introduce a multidimensional subdiffusion model that has a bond and K correlated stocks. The stock price process is a multidimensional subdiffusion process directed by the inverse α-stable subordinator. This model describes the period of stagnation for each stock and the behavior of the dependency between multiple stocks. Moreover, we derive the multidimensional fractional backward Kolmogorov equation for the subordinated process using the Laplace transform technique. Finally, using a martingale approach, we prove that the multidimensional subdiffusion model is arbitrage-free, and also gives an arbitrage-free pricing rule for contingent claims associated with the martingale measure. (interdisciplinary physics and related areas of science and technology)

A comparison of published multidimensional indices to predict outcome in idiopathic pulmonary fibrosis

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Charles Sharp

2017-03-01

Full Text Available Idiopathic pulmonary fibrosis (IPF has an unpredictable course and prognostic factors are incompletely understood. We aimed to identify prognostic factors, including multidimensional indices from a significant IPF cohort at the Bristol Interstitial Lung Disease Centre in the UK. Patients diagnosed with IPF between 2007 and 2014 were identified. Longitudinal pulmonary physiology and exercise testing results were collated, with all-cause mortality used as the primary outcome. Factors influencing overall, 12- and 24-month survival were identified using Cox proportional hazards modelling and receiver operating characteristic curve analysis. We found in this real-world cohort of 167 patients, diffusing capacity for carbon monoxide (DLCO and initiation of long-term oxygen were independent markers of poor prognosis. Exercise testing results predicted 12-month mortality as well as DLCO, but did not perform as well for overall survival. The Composite Physiological Index was the best performing multidimensional index, but did not outperform DLCO. Our data confirmed that patients who experienced a fall in forced vital capacity (FVC >10% had significantly worse survival after that point (p=0.024. Our data from longitudinal follow-up in IPF show that DLCO is the best individual prognostic marker, outperforming FVC. Exercise testing is important in predicting early poor outcome. Regular and complete review should be conducted to ensure appropriate care is delivered in a timely fashion.

Lifshitz anomalies, Ward identities and split dimensional regularization

Energy Technology Data Exchange (ETDEWEB)

Arav, Igal; Oz, Yaron; Raviv-Moshe, Avia [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University,55 Haim Levanon street, Tel-Aviv, 69978 (Israel)

2017-03-16

We analyze the structure of the stress-energy tensor correlation functions in Lifshitz field theories and construct the corresponding anomalous Ward identities. We develop a framework for calculating the anomaly coefficients that employs a split dimensional regularization and the pole residues. We demonstrate the procedure by calculating the free scalar Lifshitz scale anomalies in 2+1 spacetime dimensions. We find that the analysis of the regularization dependent trivial terms requires a curved spacetime description without a foliation structure. We discuss potential ambiguities in Lifshitz scale anomaly definitions.

Lifshitz anomalies, Ward identities and split dimensional regularization

International Nuclear Information System (INIS)

Arav, Igal; Oz, Yaron; Raviv-Moshe, Avia

2017-01-01

We analyze the structure of the stress-energy tensor correlation functions in Lifshitz field theories and construct the corresponding anomalous Ward identities. We develop a framework for calculating the anomaly coefficients that employs a split dimensional regularization and the pole residues. We demonstrate the procedure by calculating the free scalar Lifshitz scale anomalies in 2+1 spacetime dimensions. We find that the analysis of the regularization dependent trivial terms requires a curved spacetime description without a foliation structure. We discuss potential ambiguities in Lifshitz scale anomaly definitions.

Coordinate-invariant regularization

International Nuclear Information System (INIS)

Halpern, M.B.

1987-01-01

A general phase-space framework for coordinate-invariant regularization is given. The development is geometric, with all regularization contained in regularized DeWitt Superstructures on field deformations. Parallel development of invariant coordinate-space regularization is obtained by regularized functional integration of the momenta. As representative examples of the general formulation, the regularized general non-linear sigma model and regularized quantum gravity are discussed. copyright 1987 Academic Press, Inc

Multi-dimensional Laplace transforms and applications

International Nuclear Information System (INIS)

Mughrabi, T.A.

1988-01-01

In this dissertation we establish new theorems for computing certain types of multidimensional Laplace transform pairs from known one-dimensional Laplace transforms. The theorems are applied to the most commonly used special functions and so we obtain many two and three dimensional Laplace transform pairs. As applications, some boundary value problems involving linear partial differential equations are solved by the use of multi-dimensional Laplace transformation. Also we establish some relations between the Laplace transformation and other integral transformation in two variables

Multi-dimensional microanalysis of masklessly implanted atoms using focused heavy ion beam

International Nuclear Information System (INIS)

Mokuno, Yoshiaki; Iiorino, Yuji; Chayahara, Akiyoshi; Kiuchi, Masato; Fujii, Kanenaga; Satou, Mamoru

1992-01-01

Multi-dimensional structure fabricated by maskless MeV gold implantation in silicon wafer was analyzed by 3 MeV carbon ion microprobe using a microbeam line developed at GIRIO. The minimum line width of the implanted region was estimated to be about 5 μm. The advantages of heavy ions for microanalysis were demonstrated. (author)

Contributions to multidimensional quadrature formulas

International Nuclear Information System (INIS)

Guenther, C.

1976-11-01

The general objective of this paper is to construct multidimensional quadrature formulas similar to the Gaussian Quadrature Formulas in one dimension. The correspondence between these formulas and orthogonal and nonnegative polynomials is established. One part of the paper considers the construction of multidimensional quadrature formulas using only methods of algebraic geometry, on the other part it is tried to obtain results on quadrature formulas with real nodes and, if possible, with positive weights. The results include the existence of quadrature formulas, information on the number resp. on the maximum possible number of points in the formulas for given polynomial degree N and the construction of formulas. (orig.) [de

Manifold regularization for sparse unmixing of hyperspectral images.

Science.gov (United States)

Liu, Junmin; Zhang, Chunxia; Zhang, Jiangshe; Li, Huirong; Gao, Yuelin

2016-01-01

Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a very large spectral library, which is cast into the framework of sparse regression. However, traditional sparse regression models, such as collaborative sparse regression , ignore the intrinsic geometric structure in the hyperspectral data. In this paper, we propose a novel model, called manifold regularized collaborative sparse regression , by introducing a manifold regularization to the collaborative sparse regression model. The manifold regularization utilizes a graph Laplacian to incorporate the locally geometrical structure of the hyperspectral data. An algorithm based on alternating direction method of multipliers has been developed for the manifold regularized collaborative sparse regression model. Experimental results on both the simulated and real hyperspectral data sets have demonstrated the effectiveness of our proposed model.

A lattice Boltzmann model for substrates with regularly structured surface roughness

Science.gov (United States)

Yagub, A.; Farhat, H.; Kondaraju, S.; Singh, T.

2015-11-01

Superhydrophobic surface characteristics are important in many industrial applications, ranging from the textile to the military. It was observed that surfaces fabricated with nano/micro roughness can manipulate the droplet contact angle, thus providing an opportunity to control the droplet wetting characteristics. The Shan and Chen (SC) lattice Boltzmann model (LBM) is a good numerical tool, which holds strong potentials to qualify for simulating droplets wettability. This is due to its realistic nature of droplet contact angle (CA) prediction on flat smooth surfaces. But SC-LBM was not able to replicate the CA on rough surfaces because it lacks a real representation of the physics at work under these conditions. By using a correction factor to influence the interfacial tension within the asperities, the physical forces acting on the droplet at its contact lines were mimicked. This approach allowed the model to replicate some experimentally confirmed Wenzel and Cassie wetting cases. Regular roughness structures with different spacing were used to validate the study using the classical Wenzel and Cassie equations. The present work highlights the strength and weakness of the SC model and attempts to qualitatively conform it to the fundamental physics, which causes a change in the droplet apparent contact angle, when placed on nano/micro structured surfaces.

Regular Expression Matching and Operational Semantics

Directory of Open Access Journals (Sweden)

Asiri Rathnayake

2011-08-01

Full Text Available Many programming languages and tools, ranging from grep to the Java String library, contain regular expression matchers. Rather than first translating a regular expression into a deterministic finite automaton, such implementations typically match the regular expression on the fly. Thus they can be seen as virtual machines interpreting the regular expression much as if it were a program with some non-deterministic constructs such as the Kleene star. We formalize this implementation technique for regular expression matching using operational semantics. Specifically, we derive a series of abstract machines, moving from the abstract definition of matching to increasingly realistic machines. First a continuation is added to the operational semantics to describe what remains to be matched after the current expression. Next, we represent the expression as a data structure using pointers, which enables redundant searches to be eliminated via testing for pointer equality. From there, we arrive both at Thompson's lockstep construction and a machine that performs some operations in parallel, suitable for implementation on a large number of cores, such as a GPU. We formalize the parallel machine using process algebra and report some preliminary experiments with an implementation on a graphics processor using CUDA.

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

Science.gov (United States)

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Geostatistical regularization operators for geophysical inverse problems on irregular meshes

Science.gov (United States)

Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA

2018-05-01

Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.

Genetic and environmental multidimensionality of well- and ill-being in middle aged twin men.

Science.gov (United States)

Franz, Carol E; Panizzon, Matthew S; Eaves, Lindon J; Thompson, Wesley; Lyons, Michael J; Jacobson, Kristen C; Tsuang, Ming; Glatt, Stephen J; Kremen, William S

2012-07-01

The goals of the study were to determine the extent to which the underlying structure of different types of well-being was multidimensional and whether well- and ill-being were influenced by similar or different genetic and environmental factors. Participants were 1226 male twins ages 51-60, from the Vietnam Era Twin Study of Aging. Measures included: psychological well-being, Multidimensional Personality Questionnaire Well-Being scale (MPQWB), life satisfaction, self-esteem, and depressive symptoms. A two-orthogonal-factor common pathway model fit the data well. Psychological well-being and self-esteem loaded most strongly on Factor 1, which was highly heritable (h(2) = .79). Life satisfaction loaded most strongly on Factor 2, which was only moderately heritable (h(2) = .32). Only MPQWB had measure-specific genetic influences. Depressive symptoms loaded on both factors, and only depressive symptoms had measure-specific common environmental influences. All measures had specific unique environmental influences. Results indicate that well-being is genetically and environmentally multidimensional and that ill-being has partial overlap with both latent factors.

Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets.

Directory of Open Access Journals (Sweden)

Ilya Belevich

2016-01-01

Full Text Available Understanding the structure-function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.

A multidimensional strategy to detect polypharmacological targets in the absence of structural and sequence homology.

Science.gov (United States)

Durrant, Jacob D; Amaro, Rommie E; Xie, Lei; Urbaniak, Michael D; Ferguson, Michael A J; Haapalainen, Antti; Chen, Zhijun; Di Guilmi, Anne Marie; Wunder, Frank; Bourne, Philip E; McCammon, J Andrew

2010-01-22

Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.

Testing the Twofold Multidimensionality of Academic Self-Concept: A Study with Chinese Vocational Students

Science.gov (United States)

Yang, Lan; Arens, A. Katrin; Watkins, David A.

2016-01-01

In order to extend previous research on the twofold multidimensionality of academic self-concept (i.e. its domain-specific structure and separation into competence and affect components), the present study tests its generalisability among vocational students from mainland China. A Chinese version of self-description questionnaire I was…

Multidimensional carbon allotropes as electrochemical detectors in capillary and microchip electrophoresis.

Science.gov (United States)

Martín, Aída; López, Miguel Ángel; González, María Cristina; Escarpa, Alberto

2015-01-01

The main multidimensional carbon allotropes could be classified into carbon nanotubes as 1D material, graphene as 2D material, as well as graphite and diamond as 3D carbon materials. Along with this review, a discussion using these four structures as electrochemical detectors in CE and ME will permit us to explore the recent advances in this field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving personality facet scores with multidimensional computer adaptive testing

DEFF Research Database (Denmark)

Makransky, Guido; Mortensen, Erik Lykke; Glas, Cees A W

2013-01-01

personality tests contain many highly correlated facets. This article investigates the possibility of increasing the precision of the NEO PI-R facet scores by scoring items with multidimensional item response theory and by efficiently administering and scoring items with multidimensional computer adaptive...

DESIGN OF STRUCTURAL ELEMENTS IN THE EVENT OF THE PRE-SET RELIABILITY, REGULAR LOAD AND BEARING CAPACITY DISTRIBUTION

Directory of Open Access Journals (Sweden)

Tamrazyan Ashot Georgievich

2012-10-01

Full Text Available Accurate and adequate description of external influences and of the bearing capacity of the structural material requires the employment of the probability theory methods. In this regard, the characteristic that describes the probability of failure-free operation is required. The characteristic of reliability means that the maximum stress caused by the action of the load will not exceed the bearing capacity. In this paper, the author presents a solution to the problem of calculation of structures, namely, the identification of reliability of pre-set design parameters, in particular, cross-sectional dimensions. If the load distribution pattern is available, employment of the regularities of distributed functions make it possible to find the pattern of distribution of maximum stresses over the structure. Similarly, we can proceed to the design of structures of pre-set rigidity, reliability and stability in the case of regular load distribution. We consider the element of design (a monolithic concrete slab, maximum stress S which depends linearly on load q. Within a pre-set period of time, the probability will not exceed the values according to the Poisson law. The analysis demonstrates that the variability of the bearing capacity produces a stronger effect on relative sizes of cross sections of a slab than the variability of loads. It is therefore particularly important to reduce the coefficient of variation of the load capacity. One of the methods contemplates the truncation of the bearing capacity distribution by pre-culling the construction material.

A Comparison of Multidimensional Item Selection Methods in Simple and Complex Test Designs

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Eren Halil ÖZBERK

2017-03-01

Full Text Available In contrast with the previous studies, this study employed various test designs (simple and complex which allow the evaluation of the overall ability score estimations across multiple real test conditions. In this study, four factors were manipulated, namely the test design, number of items per dimension, correlation between dimensions and item selection methods. Using the generated item and ability parameters, dichotomous item responses were generated in by using M3PL compensatory multidimensional IRT model with specified correlations. MCAT composite ability score accuracy was evaluated using absolute bias (ABSBIAS, correlation and the root mean square error (RMSE between true and estimated ability scores. The results suggest that the multidimensional test structure, number of item per dimension and correlation between dimensions had significant effect on item selection methods for the overall score estimations. For simple structure test design it was found that V1 item selection has the lowest absolute bias estimations for both long and short tests while estimating overall scores. As the model gets complex KL item selection method performed better than other two item selection method.

Enhanced manifold regularization for semi-supervised classification.

Science.gov (United States)

Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong

2016-06-01

Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.

Graph theoretical ordering of structures as a basis for systematic searches for regularities in molecular data

International Nuclear Information System (INIS)

Randic, M.; Wilkins, C.L.

1979-01-01

Selected molecular data on alkanes have been reexamined in a search for general regularities in isomeric variations. In contrast to the prevailing approaches concerned with fitting data by searching for optimal parameterization, the present work is primarily aimed at established trends, i.e., searching for relative magnitudes and their regularities among the isomers. Such an approach is complementary to curve fitting or correlation seeking procedures. It is particularly useful when there are incomplete data which allow trends to be recognized but no quantitative correlation to be established. One proceeds by first ordering structures. One way is to consider molecular graphs and enumerate paths of different length as the basic graph invariant. It can be shown that, for several thermodynamic molecular properties, the number of paths of length two (p 2 ) and length three (p 3 ) are critical. Hence, an ordering based on p 2 and p 3 indicates possible trends and behavior for many molecular properties, some of which relate to others, some which do not. By considering a grid graph derived by attributing to each isomer coordinates (p 2 ,p 3 ) and connecting points along the coordinate axis, one obtains a simple presentation useful for isomer structural interrelations. This skeletal frame is one upon which possible trends for different molecular properties may be conveniently represented. The significance of the results and their conceptual value is discussed. 16 figures, 3 tables

Multi-Dimensional Aggregation for Temporal Data

DEFF Research Database (Denmark)

Böhlen, M. H.; Gamper, J.; Jensen, Christian Søndergaard

2006-01-01

Business Intelligence solutions, encompassing technologies such as multi-dimensional data modeling and aggregate query processing, are being applied increasingly to non-traditional data. This paper extends multi-dimensional aggregation to apply to data with associated interval values that capture...... that the data holds for each point in the interval, as well as the case where the data holds only for the entire interval, but must be adjusted to apply to sub-intervals. The paper reports on an implementation of the new operator and on an empirical study that indicates that the operator scales to large data...

Executive Information Systems' Multidimensional Models

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available Executive Information Systems are design to improve the quality of strategic level of management in organization through a new type of technology and several techniques for extracting, transforming, processing, integrating and presenting data in such a way that the organizational knowledge filters can easily associate with this data and turn it into information for the organization. These technologies are known as Business Intelligence Tools. But in order to build analytic reports for Executive Information Systems (EIS in an organization we need to design a multidimensional model based on the business model from the organization. This paper presents some multidimensional models that can be used in EIS development and propose a new model that is suitable for strategic business requests.

The Tunneling Method for Global Optimization in Multidimensional Scaling.

Science.gov (United States)

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

A study of multidimensional modeling approaches for data warehouse

Science.gov (United States)

Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani

2016-08-01

Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.

Multidimensional traveling waves in the Allen–Cahn cellular automaton

International Nuclear Information System (INIS)

Murata, Mikio

2015-01-01

Ultradiscretization is a limiting procedure transforming a given difference equation into a cellular automaton. The cellular automaton constructed by this procedure preserves the essential properties of the original equation, such as the structure of exact solutions for integrable equations. In this article, a cellular automaton analog of the multidimensional Allen–Cahn equation which is not an integrable system is constructed by the ultradiscretization. Moreover, the traveling wave solutions for the resulting cellular automaton are given. The shape, behavior and stability of the solutions in ultradiscrete systems are similar to those in continuous systems. (paper)

Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning

OpenAIRE

Lai, Rongjie; Li, Jia

2017-01-01

Low-rank structures play important role in recent advances of many problems in image science and data science. As a natural extension of low-rank structures for data with nonlinear structures, the concept of the low-dimensional manifold structure has been considered in many data processing problems. Inspired by this concept, we consider a manifold based low-rank regularization as a linear approximation of manifold dimension. This regularization is less restricted than the global low-rank regu...

Fatigue and multidimensional disease severity in chronic obstructive pulmonary disease

Directory of Open Access Journals (Sweden)

Inal-Ince Deniz

2010-06-01

Full Text Available Abstract Background and aims Fatigue is associated with longitudinal ratings of health in patients with chronic obstructive pulmonary disease (COPD. Although the degree of airflow obstruction is often used to grade disease severity in patients with COPD, multidimensional grading systems have recently been developed. The aim of this study was to investigate the relationship between perceived and actual fatigue level and multidimensional disease severity in patients with COPD. Materials and methods Twenty-two patients with COPD (aged 52-74 years took part in the study. Multidimensional disease severity was measured using the SAFE and BODE indices. Perceived fatigue was assessed using the Fatigue Severity Scale (FSS and the Fatigue Impact Scale (FIS. Peripheral muscle endurance was evaluated using the number of sit-ups, squats, and modified push-ups that each patient could do. Results Thirteen patients (59% had severe fatigue, and their St George's Respiratory Questionnaire scores were significantly higher (p Conclusions Peripheral muscle endurance and fatigue perception in patients with COPD was related to multidimensional disease severity measured with both the SAFE and BODE indices. Improvements in perceived and actual fatigue levels may positively affect multidimensional disease severity and health status in COPD patients. Further research is needed to investigate the effects of fatigue perception and exercise training on patients with different stages of multidimensional COPD severity.

Multidimensional nonlinear descriptive analysis

CERN Document Server

Nishisato, Shizuhiko

2006-01-01

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations. This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for futu...

Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball

Directory of Open Access Journals (Sweden)

Zh.L. Kozina

2017-10-01

Full Text Available Purpose: to determine main laws of determination of athletes’ fitness structure’s individual characteristics with the help of multidimensional analysis (on example of basketball. Material: in the research elite basketball players (n=54 participated. Pedagogic testing included 12 tests, applied in combined teams of Ukraine and Russia. For every test three attempts were given and the best result was registered. The tests were passed during 2-3 training sessions. Results: we worked out general scheme of ways of athletes’ training individualization. For every athlete we determined the groups of leading and secondary factors in individual structure of fitness. The process of athletes’ training shall contain basic and variable components. Basic component was 70% of means in general system of athletes' training. Variable component was 30% of means and implies application of individual training means. Percentage of means in individual programs varies depending on the following: leading factors in fitness individual structure; period of individual dynamic of competition efficiency. In every micro-cycle 30% is assigned for athletes’ individual training: athletes received individual tasks; groups on the base of cluster analysis data were formed, if necessary. Conclusions: when working out individual training programs, development of leading factors in individual factorial structure of athletes’ fitness shall be accented. Application of individual programs, combined with universal individualization methods creates preconditions for rising competition activities’ efficiency.

HYBRID APPROACHES TO THE FORMALISATION OF EXPERT KNOWLEDGE CONCERNING TEMPORAL REGULARITIES IN THE TIME SERIES GROUP OF A SYSTEM MONITORING DATABASE

Directory of Open Access Journals (Sweden)

E. S. Staricov

2016-01-01

Full Text Available Objectives. The presented research problem concerns data regularities for an unspecified time series based on an approach to the expert formalisation of knowledge integrated into a decision-making mechanism. Method. A context-free grammar, consisting of a modification of universal temporal grammar, is used to describe regularities. Using the rules of the developed grammar, an expert can describe patterns in the group of time series. A multi-dimensional matrix pattern of the behaviour of a group of time series is used in a real-time decision-making regime in the expert system to implements a universal approach to the description of the dynamics of these changes in the expert system. The multidimensional matrix pattern is specifically intended for decision-making in an expert system; the modified temporal grammar is used to identify patterns in the data. Results. It is proposed to use the temporal relations of the series and fix observation values in the time interval as ―From-To‖, ―Before‖, ―After‖, ―Simultaneously‖ and ―Duration‖. A syntactically oriented converter of descriptions is developed. A schema for the creation and application of matrix patterns in expert systems is drawn up. Conclusion. The advantage of the implementation of the proposed hybrid approaches consists in a reduction of the time taken for identifying temporal patterns and an automation of the matrix pattern of the decision-making system based on expert descriptions verified using live data derived from relationships in the monitoring data. 

A DYNAMIC INDEXING SCHEME FOR MULTIDIMENSIONAL DATA

Directory of Open Access Journals (Sweden)

Manuk G. Manukyan

2018-03-01

Full Text Available We present a new dynamic index structure for multidimensional data. The considered index structure is based on an extended grid file concept. Strengths and weaknesses of the grid files were analyzed. Based on that analysis we proposed to strengthen the concept of grid files by considering their stripes as linear hash tables, introducing the concept of chunk and representing the grid file structure as a graph. As a result we significantly reduced the amount of disk operations. Efficient algorithms for storage and access of index directory are proposed, in order to minimize memory usage and lookup operations complexities. Estimations of complexities for these algorithms are presented. A comparison of our approach to support effective grid file structure with other known approaches is presented. This comparison shows effectiveness of suggested metadata storage environment. An estimation of directory size is presented. A prototype to support of our grid file concept has been created and experimentally compared with MongoDB (a renowned NoSQL database. Comparison results show effectiveness of our approach in the cases of given point lookup, lookup by wide ranges and closest objects lookup when considering more than one dimension, and also better memory usage.

Multidimensional Physical Self-Concept of Athletes with Physical Disabilities

Science.gov (United States)

Shapiro, Deborah R.; Martin, Jeffrey J.

2010-01-01

The purposes of this investigation were first to predict reported PA (physical activity) behavior and self-esteem using a multidimensional physical self-concept model and second to describe perceptions of multidimensional physical self-concept (e.g., strength, endurance, sport competence) among athletes with physical disabilities. Athletes (N =…

Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

KAUST Repository

Cannistraci, Carlo Vittorio

2015-01-26

Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet\\'s performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

KAUST Repository

Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

2015-01-01

Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

The Multidimensional Loss Scale: validating a cross-cultural instrument for measuring loss.

Science.gov (United States)

Vromans, Lyn; Schweitzer, Robert D; Brough, Mark

2012-04-01

The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to index Experience of Loss Events and Loss Distress across multiple domains (cultural, social, material, and intrapersonal) relevant to refugee settlement. Recently settled Burmese adult refugees (N = 70) completed a questionnaire battery, including MLS items. Analyses explored MLS internal consistency, convergent and divergent validity, and factor structure. Cronbach alphas indicated satisfactory internal consistency for Experience of Loss Events (0.85) and Loss Distress (0.92), reflecting a unitary construct of multidimensional loss. Loss Distress did not correlate with depression or anxiety symptoms and correlated moderately with interpersonal grief and trauma symptoms, supporting divergent and convergent validity. Factor analysis provided preliminary support for a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Received well by participants, the new scale shows promise for application in future research and practice.

Development of Multidimensional Gap Conductance model using Virtual Link Gap Element

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyo Chan; Yang, Yong Sik; Kim, Dae Ho; Bang, Je Geon; Kim, Sun Ki; Koo, Yang Hyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-10-15

The gap conductance that determines temperature gradient between pellet and cladding can be quite sensitive to gap thickness. For instance, once the gap size increases up to several micrometers in certain region, difference of pellet surface temperatures increases up to 100 Kelvin. Therefore, iterative thermo-mechanical coupled analysis is required to solve temperature distribution throughout pellet and cladding. Recently, multidimensional fuel performance codes have been being developed in the advanced countries to evaluate thermal behavior of fuel for off normal conditions and DBA(design based accident) conditions using the Finite Element Method (FEM). FRAPCON-FRAPTRAN code system, which is well known as the verified and reliable code, incorporates 1D thermal module and multidimensional mechanical module. In this code, multidimensional gap conductance model is not applied. ALCYONE developed by CEA introduces equivalent heat convection coefficient that represents multidimensional gap conductance as a function of gap thickness. BISON, which is multidimensional fuel performance code developed by INL, owns multidimensional gap conductance model using projected thermal contact. In general, thermal contact algorithm is nonlinear calculation which is expensive approach numerically. The gap conductance model for multi-dimension is difficult issue in terms of convergence and nonlinearity because gap conductance is function of gap thickness which depends on mechanical analysis at each iteration step. In this paper, virtual link gap (VLG) element has been proposed to resolve convergence issue and nonlinear characteristic of multidimensional gap conductance. In terms of calculation accuracy and convergence efficiency, the proposed VLG model was evaluated. LWR fuel performance codes should incorporate thermo-mechanical loop to solve gap conductance problem, iteratively. However, gap conductance in multidimensional model is difficult issue owing to its nonlinearity and

Conservative Initial Mapping For Multidimensional Simulations of Stellar Explosions

International Nuclear Information System (INIS)

Chen, Ke-Jung; Heger, Alexander; Almgren, Ann

2012-01-01

Mapping one-dimensional stellar profiles onto multidimensional grids as initial conditions for hydrodynamics calculations can lead to numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities such as energy and mass. Here we introduce a numerical scheme for mapping one-dimensional spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We validate our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping.

Bounded Perturbation Regularization for Linear Least Squares Estimation

KAUST Repository

Ballal, Tarig

2017-10-18

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is allowed into the linear transformation matrix to improve the singular-value structure. Following this, the problem is formulated as a min-max optimization problem. Next, the min-max problem is converted to an equivalent minimization problem to estimate the unknown vector quantity. The solution of the minimization problem is shown to converge to that of the ℓ2 -regularized least squares problem, with the unknown regularizer related to the norm bound of the introduced perturbation through a nonlinear constraint. A procedure is proposed that combines the constraint equation with the mean squared error (MSE) criterion to develop an approximately optimal regularization parameter selection algorithm. Both direct and indirect applications of the proposed method are considered. Comparisons with different Tikhonov regularization parameter selection methods, as well as with other relevant methods, are carried out. Numerical results demonstrate that the proposed method provides significant improvement over state-of-the-art methods.

A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem

DEFF Research Database (Denmark)

Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Pontil, Massimiliano

2014-01-01

We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy electroencephalographic (EEG) measurements, commonly named as the EEG inverse problem. We propose a new method to induce neurophysiological meaningful solutions, which takes into account the smoothness, structured...... sparsity, and low rank of the BES matrix. The method is based on the factorization of the BES matrix as a product of a sparse coding matrix and a dense latent source matrix. The structured sparse-low-rank structure is enforced by minimizing a regularized functional that includes the ℓ21-norm of the coding...... matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We analyze the convergence of the optimization procedure, and we compare, under different synthetic scenarios...

Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

Directory of Open Access Journals (Sweden)

Mohammad Nur Shodiq

2016-03-01

Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

Multidimensional filter banks and wavelets research developments and applications

CERN Document Server

Levy, Bernard

1997-01-01

Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.

On new physics searches with multidimensional differential shapes

Science.gov (United States)

Ferreira, Felipe; Fichet, Sylvain; Sanz, Veronica

2018-03-01

In the context of upcoming new physics searches at the LHC, we investigate the impact of multidimensional differential rates in typical LHC analyses. We discuss the properties of shape information, and argue that multidimensional rates bring limited information in the scope of a discovery, but can have a large impact on model discrimination. We also point out subtleties about systematic uncertainties cancellations and the Cauchy-Schwarz bound on interference terms.

Multidimensional human dynamics in mobile phone communications.

Science.gov (United States)

Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo

2014-01-01

In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

Multidimensional human dynamics in mobile phone communications.

Directory of Open Access Journals (Sweden)

Christian Quadri

Full Text Available In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages. Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

Image matrix processor for fast multi-dimensional computations

Science.gov (United States)

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Multidimensional Assessment of Spirituality/Religion in Patients with HIV: Conceptual Framework and Empirical Refinement

Science.gov (United States)

Kudel, Ian; Cotton, Sian; Leonard, Anthony C.; Tsevat, Joel; Ritchey, P. Neal

2011-01-01

A decade ago, an expert panel developed a framework for measuring spirituality/religion in health research (Brief Multidimensional Measure of Religiousness/Spirituality), but empirical testing of this framework has been limited. The purpose of this study was to determine whether responses to items across multiple measures assessing spirituality/religion by 450 patients with HIV replicate this model. We hypothesized a six-factor model underlying a collective of 56 items, but results of confirmatory factor analyses suggested eight dimensions: Meaning/Peace, Tangible Connection to the Divine, Positive Religious Coping, Love/Appreciation, Negative Religious Coping, Positive Congregational Support, Negative Congregational Support, and Cultural Practices. This study corroborates parts of the factor structure underlying the Brief Multidimensional Measure of Religiousness/Spirituality and some recent refinements of the original framework. PMID:21136166

Spinor structures on homogeneous spaces

International Nuclear Information System (INIS)

Lyakhovskii, V.D.; Mudrov, A.I.

1993-01-01

For multidimensional models of the interaction of elementary particles, the problem of constructing and classifying spinor fields on homogeneous spaces is exceptionally important. An algebraic criterion for the existence of spinor structures on homogeneous spaces used in multidimensional models is developed. A method of explicit construction of spinor structures is proposed, and its effectiveness is demonstrated in examples. The results are of particular importance for harmonic decomposition of spinor fields

Two multi-dimensional uncertainty relations

International Nuclear Information System (INIS)

Skala, L; Kapsa, V

2008-01-01

Two multi-dimensional uncertainty relations, one related to the probability density and the other one related to the probability density current, are derived and discussed. Both relations are stronger than the usual uncertainty relations for the coordinates and momentum

Benefits of Multidimensional Measures of Child Well Being in China.

Science.gov (United States)

Gatenio Gabel, Shirley; Zhang, Yiwei

2017-11-06

In recent decades, measures of child well-being have evolved from single dimension to multidimensional measures. Multi-dimensional measures deepen and broaden our understanding of child well-being and inform us of areas of neglect. Child well-being in China today is measured through proxy measures of household need. This paper discusses the evolution of child well-being measures more generally, explores the benefits of positive indicators and multiple dimensions in formulating policy, and then reviews efforts to date by the Chinese government, researchers, and non-governmental and intergovernmental organizations to develop comprehensive multidimensional measures of child well-being in China. The domains and their potential interactions, as well as data sources and availability, are presented. The authors believe that child well-being in China would benefit from the development of a multidimensional index and that there is sufficient data to develop such an index.

Multidimensional analysis algebras and systems for science and engineering

CERN Document Server

Hart, George W

1995-01-01

This book deals with the mathematical properties of dimensioned quantities, such as length, mass, voltage, and viscosity. Beginning with a careful examination of how one expresses the numerical results of a measurement and uses these results in subsequent manipulations, the author rigorously constructs the notion of dimensioned numbers and discusses their algebraic structure. The result is a unification of linear algebra and traditional dimensional analysis that can be extended from the scalars to which the traditional analysis is perforce restricted to multidimensional vectors of the sort frequently encountered in engineering, systems theory, economics, and other applications.

Best-estimated multi-dimensional calculation during LB LOCA for APR1400

International Nuclear Information System (INIS)

Oh, D. Y.; Bang, Y. S.; Cheong, A. J.; Woong, S.; Korea, W.

2010-01-01

Best-estimated (BE) calculation with uncertainty quantification for the emergency core cooling system (ECCS) performance analysis during Loss of Coolant Accident (LOCA) is more broadly used in nuclear industries and regulations. In Korea, demand on regulatory audit calculation is continuously increasing to support the safety review for life extension, power up-rating and advanced nuclear reactor design. The thermal-hydraulic system code, MARS (Multi-dimensional Analysis of Reactor Safety), with multi-dimensional capability is used for audit calculation. It achieves to describe the complicated phenomena in reactor coolant system by very effectively consolidating the one dimensional RELAP5/MOD3 with the multidimensional COBRA-TF codes. The advanced power reactors (APR1400) to be evaluated has four separated hydraulic trains of the high pressure injection system (HPSI) with direct vessel injection (DVI) which is different from the existing commercial PWRs. Also, the therma-hydraulic behavior of DVI plant would be considerably different from that of a cold-leg safety injection since the low pressure safety injection system are eliminated and the high pressure safety flow are injected into the specific elevation of reactor vessel downcomer. The ECCS bypass induced by the downcomer boiling due to hot wall heating of reactor vessel during reflooding phase is one of the important phenomena which should be considered in DVI plants. Therefore, in this study, BE calculation with one-dimensional (1-D) and multi-dimensional (multi-D) MARS models during LBLOCA are performed for APR1400 plant. In the multi-D evaluation, the reactor vessel is modeled by multi-D components and the specific treatment of flow path inside reactor vessel, e.g., upper guide structure, is essential. The concept of hot zone is adopted to simulate the limiting thermal-hydraulic conditions surrounding hot rod, which is similar to hot channel in 1-D. Also, alternative treatment of the hot rods in multi-D is

Joint mapping of genes and conditions via multidimensional unfolding analysis

Directory of Open Access Journals (Sweden)

Engelen Kristof

2007-06-01

Full Text Available Abstract Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data.

Manifold regularized multitask learning for semi-supervised multilabel image classification.

Science.gov (United States)

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Total variation regularization for fMRI-based prediction of behavior

Science.gov (United States)

Michel, Vincent; Gramfort, Alexandre; Varoquaux, Gaël; Eger, Evelyn; Thirion, Bertrand

2011-01-01

While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI (fMRI) data, that provide an indirect measure of task-related or spontaneous neuronal activity, are classically analyzed in a mass-univariate procedure yielding statistical parametric maps. This analysis framework disregards some important principles of brain organization: population coding, distributed and overlapping representations. Multivariate pattern analysis, i.e., the prediction of behavioural variables from brain activation patterns better captures this structure. To cope with the high dimensionality of the data, the learning method has to be regularized. However, the spatial structure of the image is not taken into account in standard regularization methods, so that the extracted features are often hard to interpret. More informative and interpretable results can be obtained with the ℓ1 norm of the image gradient, a.k.a. its Total Variation (TV), as regularization. We apply for the first time this method to fMRI data, and show that TV regularization is well suited to the purpose of brain mapping while being a powerful tool for brain decoding. Moreover, this article presents the first use of TV regularization for classification. PMID:21317080

Visual modeling in an analysis of multidimensional data

Science.gov (United States)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Multidimensional Scaling Localization Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhang Dongyang

2014-02-01

Full Text Available Due to the localization algorithm in large-scale wireless sensor network exists shortcomings both in positioning accuracy and time complexity compared to traditional localization algorithm, this paper presents a fast multidimensional scaling location algorithm. By positioning algorithm for fast multidimensional scaling, fast mapping initialization, fast mapping and coordinate transform can get schematic coordinates of node, coordinates Initialize of MDS algorithm, an accurate estimate of the node coordinates and using the PRORUSTES to analysis alignment of the coordinate and final position coordinates of nodes etc. There are four steps, and the thesis gives specific implementation steps of the algorithm. Finally, compared with stochastic algorithms and classical MDS algorithm experiment, the thesis takes application of specific examples. Experimental results show that: the proposed localization algorithm has fast multidimensional scaling positioning accuracy in ensuring certain circumstances, but also greatly improves the speed of operation.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

Science.gov (United States)

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

On the measurement of the (multidimensional) inequality of health distributions

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Moreno-Ternero, Juan D.; Østerdal, Lars Peter Raahave

2013-01-01

a standard mathematical structure. We single out two families of (absolute and relative) multidimensional health inequality indices, inspired by the classical normative approach to income inequality measurement. We also discuss how to extend the analysis to deal with the related problem of health deprivation......Health outcomes are often described according to two dimensions: quality of life and quantity of life. We analyze the measurement of inequality of health distributions referring to these two dimensions. Our analysis relies on a novel treatment of the quality-of-life dimension, which might not have...

Development of multi-dimensional body image scale for malaysian female adolescents.

Science.gov (United States)

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

Science.gov (United States)

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

Science.gov (United States)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These

New multidimensional partially integrable generalization of S-integrable N-wave equation

International Nuclear Information System (INIS)

Zenchuk, A. I.

2007-01-01

This paper develops a modification of the dressing method based on the inhomogeneous linear integral equation with integral operator having nonempty kernel. The method allows one to construct the systems of multidimensional partial differential equations having differential polynomial structure in any dimension n. The associated solution space is not full, although it is parametrized by certain number of arbitrary functions of (n-1) variables. We consider four-dimensional generalization of the classical (2+1)-dimensional S-integrable N-wave equation as an example

Analysis of Local Dependence and Multidimensionality in Graphical Loglinear Rasch Models

DEFF Research Database (Denmark)

Kreiner, Svend; Christensen, Karl Bang

2004-01-01

Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model......Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model...

Distance-regular graphs

NARCIS (Netherlands)

van Dam, Edwin R.; Koolen, Jack H.; Tanaka, Hajime

2016-01-01

This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN'[Brouwer, A.E., Cohen, A.M., Neumaier,

Regular expressions cookbook

CERN Document Server

Goyvaerts, Jan

2009-01-01

This cookbook provides more than 100 recipes to help you crunch data and manipulate text with regular expressions. Every programmer can find uses for regular expressions, but their power doesn't come worry-free. Even seasoned users often suffer from poor performance, false positives, false negatives, or perplexing bugs. Regular Expressions Cookbook offers step-by-step instructions for some of the most common tasks involving this tool, with recipes for C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. With this book, you will: Understand the basics of regular expressions through a

Multidimensional Databases and Data Warehousing

DEFF Research Database (Denmark)

Jensen, Christian S.; Pedersen, Torben Bach; Thomsen, Christian

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes...

German version of the Multidimensional Body-Self Relations Questionnaire - Appearance Scales (MBSRQ-AS): confirmatory factor analysis and validation.

Science.gov (United States)

Vossbeck-Elsebusch, Anna N; Waldorf, Manuel; Legenbauer, Tanja; Bauer, Anika; Cordes, Martin; Vocks, Silja

2014-06-01

The Multidimensional Body-Self Relations Questionnaire (MBSRQ) is a widely used questionnaire that measures body image as a multidimensional construct. The Appearance Scales (AS) of the MBSRQ (Appearance Evaluation, Appearance Orientation, Body Areas Satisfaction, Overweight Preoccupation and Self-Classified Weight) are subscales which facilitate a parsimonious assessment of appearance-related aspects of body image. The current study tested the psychometric properties and factor structure of a German translation of the MBSRQ-AS. Participants were n=230 female patients with the SCID diagnosis of an eating disorder and n=293 female healthy controls. In a confirmatory factor analysis, convincing goodness-of-fit indices emerged. The subscales of the questionnaire yielded good reliability and convergent and discriminant validity coefficients, with most items showing excellent characteristics. Like the English version, the German adaptation of the questionnaire can be recommended for a multidimensional assessment of appearance-related aspects of body image in both research and clinical practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Background elimination methods for multidimensional coincidence γ-ray spectra

International Nuclear Information System (INIS)

Morhac, M.

1997-01-01

In the paper new methods to separate useful information from background in one, two, three and multidimensional spectra (histograms) measured in large multidetector γ-ray arrays are derived. The sensitive nonlinear peak clipping algorithm is the basis of the methods for estimation of the background in multidimensional spectra. The derived procedures are simple and therefore have a very low cost in terms of computing time. (orig.)

Regularized Statistical Analysis of Anatomy

DEFF Research Database (Denmark)

Sjöstrand, Karl

2007-01-01

This thesis presents the application and development of regularized methods for the statistical analysis of anatomical structures. Focus is on structure-function relationships in the human brain, such as the connection between early onset of Alzheimer’s disease and shape changes of the corpus...... and mind. Statistics represents a quintessential part of such investigations as they are preluded by a clinical hypothesis that must be verified based on observed data. The massive amounts of image data produced in each examination pose an important and interesting statistical challenge...... efficient algorithms which make the analysis of large data sets feasible, and gives examples of applications....

Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2015-12-01

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage. Copyright © 2014 John Wiley & Sons, Ltd.

LL-regular grammars

NARCIS (Netherlands)

Nijholt, Antinus

1980-01-01

Culik II and Cogen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this paper we consider an analogous extension of the LL(k) grammars called the LL-regular grammars. The relation of this class of grammars to other classes of grammars will be shown. Any LL-regular

Periodic vortex pinning by regular structures in Nb thin films: magnetic vs. structural effects

Science.gov (United States)

Montero, Maria Isabel; Jonsson-Akerman, B. Johan; Schuller, Ivan K.

2001-03-01

The defects present in a superconducting material can lead to a great variety of static and dynamic vortex phases. In particular, the interaction of the vortex lattice with regular arrays of pinning centers such as holes or magnetic dots gives rise to commensurability effects. These commensurability effects can be observed in the magnetoresistance and in the critical current dependence with the applied field. In recent years, experimental results have shown that there is a dependence of the periodic pinning effect on the properties of the vortex lattice (i.e. vortex-vortex interactions, elastic energy and vortex velocity) and also on the dots characteristics (i.e. dot size, distance between dots, magnetic character of the dot material, etc). However, there is not still a good understanding of the nature of the main pinning mechanisms by the magnetic dots. To clarify this important issue, we have studied and compared the periodic pinning effects in Nb films with rectangular arrays of Ni, Co and Fe dots, as well as the pinning effects in a Nb film deposited on a hole patterned substrate without any magnetic material. We will discuss the differences on pinning energies arising from magnetic effects as compared to structural effects of the superconducting film. This work was supported by NSF and DOE. M.I. Montero acknowledges postdoctoral fellowship by the Secretaria de Estado de Educacion y Universidades (Spain).

Locus of control and pain: Validity of the Form C of the Multidimensional Health Locus of Control scales when used with adolescents.

Science.gov (United States)

Castarlenas, Elena; Solé, Ester; Racine, Mélanie; Sánchez-Rodríguez, Elisabet; Jensen, Mark P; Miró, Jordi

2016-09-01

The objective of this study was to examine the factor structure, reliability, and validity of the Form C of the Multidimensional Health Locus of Control scales in adolescents. A confirmatory factor analysis indicated that adequate fit of a four-factor model and the internal consistency of the scales were adequate. Criterion validity of the four scales of the Form C of the Multidimensional Health Locus of Control was also supported by significant correlations with measures of pain-related self-efficacy, anxiety, and coping strategies. The results indicate that the four Form C of the Multidimensional Health Locus of Control scale scores are reliable and valid and therefore support their use to assess pain-related locus of control beliefs in adolescents.

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile

Science.gov (United States)

Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun

2016-01-01

The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…

Multidimensional quantum entanglement with large-scale integrated optics

DEFF Research Database (Denmark)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong

2018-01-01

-dimensional entanglement. A programmable bipartite entangled system is realized with dimension up to 15 × 15 on a large-scale silicon-photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality......The ability to control multidimensional quantum systems is key for the investigation of fundamental science and for the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control and analyze high...

A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data.

Science.gov (United States)

Lin, Nan; Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-10-01

Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics.

Path integral approach to multidimensional quantum tunnelling

International Nuclear Information System (INIS)

Balantekin, A.B.; Takigawa, N.

1985-01-01

Path integral formulation of the coupled channel problem in the case of multidimensional quantum tunneling is presented and two-time influence functionals are introduced. The two-time influence functionals are calculated explicitly for the three simplest cases: Harmonic oscillators linearly or quadratically coupled to the translational motion and a system with finite number of equidistant energy levels linearly coupled to the translational motion. The effects of these couplings on the transmission probability are studied for two limiting cases, adiabatic case and when the internal system has a degenerate energy spectrum. The condition for the transmission probability to show a resonant structure is discussed and exemplified. Finally, the properties of the dissipation factor in the adiabatic limit and its correlation with the friction coefficient in the classically accessible region are studied

Simulation of a Multidimensional Input Quantum Perceptron

Science.gov (United States)

Yamamoto, Alexandre Y.; Sundqvist, Kyle M.; Li, Peng; Harris, H. Rusty

2018-06-01

In this work, we demonstrate the improved data separation capabilities of the Multidimensional Input Quantum Perceptron (MDIQP), a fundamental cell for the construction of more complex Quantum Artificial Neural Networks (QANNs). This is done by using input controlled alterations of ancillary qubits in combination with phase estimation and learning algorithms. The MDIQP is capable of processing quantum information and classifying multidimensional data that may not be linearly separable, extending the capabilities of the classical perceptron. With this powerful component, we get much closer to the achievement of a feedforward multilayer QANN, which would be able to represent and classify arbitrary sets of data (both quantum and classical).

An Analysis of Multi-dimensional Gender Inequality in Pakistan

OpenAIRE

Abdul Hamid; Aisha M. Ahmed

2011-01-01

Women make almost half of the population of Pakistan. They also contribute significantly to economic and social growth. However, in developing countries like Pakistan, women usually suffer from multidimensional inequality of opportunities leading to multidimensional poverty. The dimensions of family, women identity, health, education and women access to economic resources and employment contribute significantly to the discrimination of women. The provision of more opportunities to women in th...

Analytic stochastic regularization and gange invariance

International Nuclear Information System (INIS)

Abdalla, E.; Gomes, M.; Lima-Santos, A.

1986-05-01

A proof that analytic stochastic regularization breaks gauge invariance is presented. This is done by an explicit one loop calculation of the vaccum polarization tensor in scalar electrodynamics, which turns out not to be transversal. The counterterm structure, Langevin equations and the construction of composite operators in the general framework of stochastic quantization, are also analysed. (Author) [pt

A Multidimensional Software Engineering Course

Science.gov (United States)

Barzilay, O.; Hazzan, O.; Yehudai, A.

2009-01-01

Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a…

Entropy-based viscous regularization for the multi-dimensional Euler equations in low-Mach and transonic flows

Energy Technology Data Exchange (ETDEWEB)

Marc O Delchini; Jean E. Ragusa; Ray A. Berry

2015-07-01

We present a new version of the entropy viscosity method, a viscous regularization technique for hyperbolic conservation laws, that is well-suited for low-Mach flows. By means of a low-Mach asymptotic study, new expressions for the entropy viscosity coefficients are derived. These definitions are valid for a wide range of Mach numbers, from subsonic flows (with very low Mach numbers) to supersonic flows, and no longer depend on an analytical expression for the entropy function. In addition, the entropy viscosity method is extended to Euler equations with variable area for nozzle flow problems. The effectiveness of the method is demonstrated using various 1-D and 2-D benchmark tests: flow in a converging–diverging nozzle; Leblanc shock tube; slow moving shock; strong shock for liquid phase; low-Mach flows around a cylinder and over a circular hump; and supersonic flow in a compression corner. Convergence studies are performed for smooth solutions and solutions with shocks present.

A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

Energy Technology Data Exchange (ETDEWEB)

Gao, Liang, E-mail: gaol@illinois.edu [Department of Electrical and Computer Engineering, University of Illinois at Urbana–Champaign, 306 N. Wright St., Urbana, IL 61801 (United States); Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, 405 North Mathews Avenue, Urbana, IL 61801 (United States); Wang, Lihong V., E-mail: lhwang@wustl.edu [Optical imaging laboratory, Department of Biomedical Engineering, Washington University in St. Louis, One Brookings Dr., MO, 63130 (United States)

2016-02-29

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition–also dubbed snapshot imaging–has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications.

Examining the evolution towards turbulence through spatio-temporal analysis of multi-dimensional structures formed by instability growth along a shear layer

Science.gov (United States)

Merritt, Elizabeth; Doss, Forrest; Loomis, Eric; Flippo, Kirk; Devolder, Barbara; Welser-Sherrill, Leslie; Fincke, James; Kline, John

2014-10-01

The counter-propagating shear campaign is examining instability growth and its transition to turbulence relevant to mix in ICF capsules. Experimental platforms on both OMEGA and NIF use anti-symmetric flows about a shear interface to examine isolated Kelvin-Helmholtz instability growth. Measurements of interface (an Al or Ti tracer layer) dynamics are used to benchmark the LANL RAGE hydrocode with BHR turbulence model. The tracer layer does not expand uniformly, but breaks up into multi-dimensional structures that are initially quasi-2D due to the target geometry. We are developing techniques to analyze the multi-D structure growth along the tracer surface with a focus on characterizing the time-dependent structures' spectrum of scales in order to appraise a transition to turbulence in the system and potentially provide tighter constraints on initialization schemes for the BHR model. To this end, we use a wavelet based analysis to diagnose single-time radiographs of the tracer layer surface (w/low and amplified roughness for random noise seeding) with observed spatially non-repetitive features, in order to identify spatial and temporal trends in radiographs taken at different times across several experimental shots. This work conducted under the auspices of the U.S. Department of Energy by LANL under Contract DE-AC52-06NA25396.

Further investigation on "A multiplicative regularization for force reconstruction"

Science.gov (United States)

Aucejo, M.; De Smet, O.

2018-05-01

We have recently proposed a multiplicative regularization to reconstruct mechanical forces acting on a structure from vibration measurements. This method does not require any selection procedure for choosing the regularization parameter, since the amount of regularization is automatically adjusted throughout an iterative resolution process. The proposed iterative algorithm has been developed with performance and efficiency in mind, but it is actually a simplified version of a full iterative procedure not described in the original paper. The present paper aims at introducing the full resolution algorithm and comparing it with its simplified version in terms of computational efficiency and solution accuracy. In particular, it is shown that both algorithms lead to very similar identified solutions.

Convex nonnegative matrix factorization with manifold regularization.

Science.gov (United States)

Hu, Wenjun; Choi, Kup-Sze; Wang, Peiliang; Jiang, Yunliang; Wang, Shitong

2015-03-01

Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including computer vision, pattern recognition, text mining, and signal processing. However, nonnegative entries are usually required for the data matrix in NMF, which limits its application. Besides, while the basis and encoding vectors obtained by NMF can represent the original data in low dimension, the representations do not always reflect the intrinsic geometric structure embedded in the data. Motivated by manifold learning and Convex NMF (CNMF), we propose a novel matrix factorization method called Graph Regularized and Convex Nonnegative Matrix Factorization (GCNMF) by introducing a graph regularized term into CNMF. The proposed matrix factorization technique not only inherits the intrinsic low-dimensional manifold structure, but also allows the processing of mixed-sign data matrix. Clustering experiments on nonnegative and mixed-sign real-world data sets are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

Science.gov (United States)

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

An iterative method for Tikhonov regularization with a general linear regularization operator

NARCIS (Netherlands)

Hochstenbach, M.E.; Reichel, L.

2010-01-01

Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems with error-contaminated data. A regularization operator and a suitable value of a regularization parameter have to be chosen. This paper describes an iterative method, based on Golub-Kahan

Regular Topographic Patterning of Karst Depressions Suggests Landscape Self-Organization

Science.gov (United States)

Quintero, C.; Cohen, M. J.

2017-12-01

Thousands of wetland depressions that are commonly host to cypress domes dot the sub-tropical limestone landscape of South Florida. The origin of these depression features has been the topic of debate. Here we build upon the work of previous surveyors of this landscape to analyze the morphology and spatial distribution of depressions on the Big Cypress landscape. We took advantage of the emergence and availability of high resolution Light Direction and Ranging (LiDAR) technology and ArcMap GIS software to analyze the structure and regularity of landscape features with methods unavailable to past surveyors. Six 2.25 km2 LiDAR plots within the preserve were selected for remote analysis and one depression feature within each plot was selected for more intensive sediment and water depth surveying. Depression features on the Big Cypress landscape were found to show strong evidence of regular spatial patterning. Periodicity, a feature of regularly patterned landscapes, is apparent in both Variograms and Radial Spectrum Analyses. Size class distributions of the identified features indicate constrained feature sizes while Average Nearest Neighbor analyses support the inference of dispersed features with non-random spacing. The presence of regular patterning on this landscape strongly implies biotic reinforcement of spatial structure by way of the scale dependent feedback. In characterizing the structure of this wetland landscape we add to the growing body of work dedicated to documenting how water, life and geology may interact to shape the natural landscapes we see today.

Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country

Science.gov (United States)

Nilsson, Therese

2010-01-01

Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…

Regular Expression Pocket Reference

CERN Document Server

Stubblebine, Tony

2007-01-01

This handy little book offers programmers a complete overview of the syntax and semantics of regular expressions that are at the heart of every text-processing application. Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular exp

Recycling Behavior: A Multidimensional Approach

Science.gov (United States)

Meneses, Gonzalo Diaz; Palacio, Asuncion Beerli

2005-01-01

This work centers on the study of consumer recycling roles to examine the sociodemographic and psychographic profile of the distribution of recycling tasks and roles within the household. With this aim in mind, an empirical work was carried out, the results of which suggest that recycling behavior is multidimensional and comprises the undertaking…

Structures of Life: The Role of Molecular Structures in Scientists' Work

NARCIS (Netherlands)

Vyas, Dhaval; Kulyk, Olga Anatoliyivna; van der Vet, P.E.; Nijholt, Antinus; van der Veer, Gerrit C.; Jorge, J

2008-01-01

The visual and multidimensional representations like images and graphical structures related to biology provide great insights into understanding the complexities of different organisms. Especially, life scientists use different representations of molecular structures to answer biological questions

Total variation regularization in measurement and image space for PET reconstruction

KAUST Repository

Burger, M

2014-09-18

© 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.

A MULTIDIMENSIONAL AND MULTIPHYSICS APPROACH TO NUCLEAR FUEL BEHAVIOR SIMULATION

Energy Technology Data Exchange (ETDEWEB)

R. L. Williamson; J. D. Hales; S. R. Novascone; M. R. Tonks; D. R. Gaston; C. J. Permann; D. Andrs; R. C. Martineau

2012-04-01

Important aspects of fuel rod behavior, for example pellet-clad mechanical interaction (PCMI), fuel fracture, oxide formation, non-axisymmetric cooling, and response to fuel manufacturing defects, are inherently multidimensional in addition to being complicated multiphysics problems. Many current modeling tools are strictly 2D axisymmetric or even 1.5D. This paper outlines the capabilities of a new fuel modeling tool able to analyze either 2D axisymmetric or fully 3D models. These capabilities include temperature-dependent thermal conductivity of fuel; swelling and densification; fuel creep; pellet fracture; fission gas release; cladding creep; irradiation growth; and gap mechanics (contact and gap heat transfer). The need for multiphysics, multidimensional modeling is then demonstrated through a discussion of results for a set of example problems. The first, a 10-pellet rodlet, demonstrates the viability of the solution method employed. This example highlights the effect of our smeared cracking model and also shows the multidimensional nature of discrete fuel pellet modeling. The second example relies on our the multidimensional, multiphysics approach to analyze a missing pellet surface problem. As a final example, we show a lower-length-scale simulation coupled to a continuum-scale simulation.

Wavelet domain image restoration with adaptive edge-preserving regularization.

Science.gov (United States)

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

Multiple graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2013-10-01

Non-negative matrix factorization (NMF) has been widely used as a data representation method based on components. To overcome the disadvantage of NMF in failing to consider the manifold structure of a data set, graph regularized NMF (GrNMF) has been proposed by Cai et al. by constructing an affinity graph and searching for a matrix factorization that respects graph structure. Selecting a graph model and its corresponding parameters is critical for this strategy. This process is usually carried out by cross-validation or discrete grid search, which are time consuming and prone to overfitting. In this paper, we propose a GrNMF, called MultiGrNMF, in which the intrinsic manifold is approximated by a linear combination of several graphs with different models and parameters inspired by ensemble manifold regularization. Factorization metrics and linear combination coefficients of graphs are determined simultaneously within a unified object function. They are alternately optimized in an iterative algorithm, thus resulting in a novel data representation algorithm. Extensive experiments on a protein subcellular localization task and an Alzheimer\\'s disease diagnosis task demonstrate the effectiveness of the proposed algorithm. © 2013 Elsevier Ltd. All rights reserved.

Multidimensional poverty: an alternative measurement approach for the United States?

Science.gov (United States)

Waglé, Udaya R

2008-06-01

International poverty research has increasingly underscored the need to use multidimensional approaches to measure poverty. Largely embraced in Europe and elsewhere, this has not had much impact on the way poverty is measured in the United States. In this paper, I use a comprehensive multidimensional framework including economic well-being, capability, and social inclusion to examine poverty in the US. Data from the 2004 General Social Survey support the interconnectedness among these poverty dimensions, indicating that the multidimensional framework utilizing a comprehensive set of information provides a compelling value added to poverty measurement. The suggested demographic characteristics of the various categories of the poor are somewhat similar between this approach and other traditional approaches. But the more comprehensive and accurate measurement outcomes from this approach help policymakers target resources at the specific groups.

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

Science.gov (United States)

Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.

2018-04-01

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.

Multi-dimensional quasitoeplitz Markov chains

Directory of Open Access Journals (Sweden)

Alexander N. Dudin

1999-01-01

Full Text Available This paper deals with multi-dimensional quasitoeplitz Markov chains. We establish a sufficient equilibrium condition and derive a functional matrix equation for the corresponding vector-generating function, whose solution is given algorithmically. The results are demonstrated in the form of examples and applications in queues with BMAP-input, which operate in synchronous random environment.

Multidimensional integral representations problems of analytic continuation

CERN Document Server

Kytmanov, Alexander M

2015-01-01

The monograph is devoted to integral representations for holomorphic functions in several complex variables, such as Bochner-Martinelli, Cauchy-Fantappiè, Koppelman, multidimensional logarithmic residue etc., and their boundary properties. The applications considered are problems of analytic continuation of functions from the boundary of a bounded domain in C^n. In contrast to the well-known Hartogs-Bochner theorem, this book investigates functions with the one-dimensional property of holomorphic extension along complex lines, and includes the problems of receiving multidimensional boundary analogs of the Morera theorem.   This book is a valuable resource for specialists in complex analysis, theoretical physics, as well as graduate and postgraduate students with an understanding of standard university courses in complex, real and functional analysis, as well as algebra and geometry.

Analytic stochastic regularization and gauge theories

International Nuclear Information System (INIS)

Abdalla, E.; Gomes, M.; Lima-Santos, A.

1987-04-01

We prove that analytic stochatic regularization braks gauge invariance. This is done by an explicit one loop calculation of the two three and four point vertex functions of the gluon field in scalar chromodynamics, which turns out not to be geuge invariant. We analyse the counter term structure, Langevin equations and the construction of composite operators in the general framework of stochastic quantization. (author) [pt

Low-Complexity Regularization Algorithms for Image Deblurring

KAUST Repository

Alanazi, Abdulrahman

2016-11-01

Image restoration problems deal with images in which information has been degraded by blur or noise. In practice, the blur is usually caused by atmospheric turbulence, motion, camera shake, and several other mechanical or physical processes. In this study, we present two regularization algorithms for the image deblurring problem. We first present a new method based on solving a regularized least-squares (RLS) problem. This method is proposed to find a near-optimal value of the regularization parameter in the RLS problems. Experimental results on the non-blind image deblurring problem are presented. In all experiments, comparisons are made with three benchmark methods. The results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and structural similarity, as well as the visual quality of the deblurred images. To reduce the complexity of the proposed algorithm, we propose a technique based on the bootstrap method to estimate the regularization parameter in low and high-resolution images. Numerical results show that the proposed technique can effectively reduce the computational complexity of the proposed algorithms. In addition, for some cases where the point spread function (PSF) is separable, we propose using a Kronecker product so as to reduce the computations. Furthermore, in the case where the image is smooth, it is always desirable to replace the regularization term in the RLS problems by a total variation term. Therefore, we propose a novel method for adaptively selecting the regularization parameter in a so-called square root regularized total variation (SRTV). Experimental results demonstrate that our proposed method outperforms the other benchmark methods when applied to smooth images in terms of PSNR, SSIM and the restored image quality. In this thesis, we focus on the non-blind image deblurring problem, where the blur kernel is assumed to be known. However, we developed algorithms that also work

Measuring Perceived Social Support in Mexican American Youth: Psychometric Properties of the Multidimensional Scale of Perceived Social Support

Science.gov (United States)

Edwards, Lisa M.

2004-01-01

The utility of the Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet, Dahlem, Zimet,& Farley, 1988) was investigated within a sample of 290 Mexican American adolescents. Results suggested that the three-subscale structure (Family, Friends, and Significant Other) of the MSPSS was confirmed, and adequate internal reliability for the…

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

Directory of Open Access Journals (Sweden)

S. V. Groshev

2015-01-01

Full Text Available Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional data of various kinds. The paper analyses a diversity of various mathematical apparatus for Andrews plotting to visualize multi-dimensional data.The first section provides basic information about the Andrews plots, as well as about a test set of multidimensional data in Iris Fischer’s literature. Analysis of the Andrews plot properties shows that they provide a limitlessly many one-dimensional projections on the vectors and, furthermore, the plots, which are nearer to each other, correspond to nearly points. All this makes it possible to use the plots under consideration for multi-dimensional data representation. The paper considers the Andrews plot formation based on Fourier transform functions, and from the analysis results of plotting based on a set of the test, it draws a conclusion that in this way it is possible to provide clustering of multidimensional data.The second section of the work deals with research of different ways to modify the Andrews plots in order to improve the perception of the graphical representation of multidimensional data. Different variants of the Andrews plot projections on the coordinate planes and arbitrary subspaces are considered. In addition, the paper studies an effect of the Andrews plot scaling on the visual perception of multidimensional data.The paper’s third section describes Andrews plotting based on different polynomials, in particular, Chebyshev and Legendre polynomials. It is shown that the resulting image is

Relevance in the science classroom: A multidimensional analysis

Science.gov (United States)

Hartwell, Matthew F.

While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different

Development and application of computer codes for multidimensional thermalhydraulic analyses of nuclear reactor components

International Nuclear Information System (INIS)

Carver, M.B.

1983-01-01

Components of reactor systems and related equipment are identified in which multidimensional computational thermal hydraulics can be used to advantage to assess and improve design. Models of single- and two-phase flow are reviewed, and the governing equations for multidimensional analysis are discussed. Suitable computational algorithms are introduced, and sample results from the application of particular multidimensional computer codes are given

Pathways into chronic multidimensional poverty amongst older people: a longitudinal study.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2016-03-07

The use of multidimensional poverty measures is becoming more common for measuring the living standards of older people. However, the pathways into poverty are relatively unknown, nor is it known how this affects the length of time people are in poverty for. Using Waves 1 to 12 of the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey, longitudinal analysis was undertaken to identify the order that key forms of disadvantage develop - poor health, low income and insufficient education attainment - amongst Australians aged 65 years and over in multidimensional poverty, and the relationship this has with chronic poverty. Path analysis and linear regression models were used. For all older people with at least a Year 10 level of education attainment earlier mental health was significantly related to later household income (p = 0.001) and wealth (p = 0.017). For all older people with at less than a Year 10 level of education attainment earlier household income was significantly related to later mental health (p = 0.021). When limited to those in multidimensional poverty who were in income poverty and also had poor health, older people generally fell into income poverty first and then developed poor health. The order in which income poverty and poor health were developed had a significant influence on the length of time older people with less than a Year 10 level of education attainment were in multidimensional poverty for. Those who developed poor health first then fell into income poverty spend significantly less time in multidimensional poverty (-4.90, p poverty then developed poor health. Knowing the order that different forms of disadvantage develop, and the influence this has on poverty entrenchment, is of use to policy makers wishing to provide interventions to prevent older people being in long-term multidimensional poverty.

The geometry of continuum regularization

International Nuclear Information System (INIS)

Halpern, M.B.

1987-03-01

This lecture is primarily an introduction to coordinate-invariant regularization, a recent advance in the continuum regularization program. In this context, the program is seen as fundamentally geometric, with all regularization contained in regularized DeWitt superstructures on field deformations

Multi-dimensional indoor location information model

NARCIS (Netherlands)

Xiong, Q.; Zhu, Q.; Zlatanova, S.; Huang, L.; Zhou, Y.; Du, Z.

2013-01-01

Aiming at the increasing requirements of seamless indoor and outdoor navigation and location service, a Chinese standard of Multidimensional Indoor Location Information Model is being developed, which defines ontology of indoor location. The model is complementary to 3D concepts like CityGML and

Regular expression containment

DEFF Research Database (Denmark)

Henglein, Fritz; Nielsen, Lasse

2011-01-01

We present a new sound and complete axiomatization of regular expression containment. It consists of the conventional axiomatiza- tion of concatenation, alternation, empty set and (the singleton set containing) the empty string as an idempotent semiring, the fixed- point rule E* = 1 + E × E......* for Kleene-star, and a general coin- duction rule as the only additional rule. Our axiomatization gives rise to a natural computational inter- pretation of regular expressions as simple types that represent parse trees, and of containment proofs as coercions. This gives the axiom- atization a Curry......-Howard-style constructive interpretation: Con- tainment proofs do not only certify a language-theoretic contain- ment, but, under our computational interpretation, constructively transform a membership proof of a string in one regular expres- sion into a membership proof of the same string in another regular expression. We...

Supersymmetric dimensional regularization

International Nuclear Information System (INIS)

Siegel, W.; Townsend, P.K.; van Nieuwenhuizen, P.

1980-01-01

There is a simple modification of dimension regularization which preserves supersymmetry: dimensional reduction to real D < 4, followed by analytic continuation to complex D. In terms of component fields, this means fixing the ranges of all indices on the fields (and therefore the numbers of Fermi and Bose components). For superfields, it means continuing in the dimensionality of x-space while fixing the dimensionality of theta-space. This regularization procedure allows the simple manipulation of spinor derivatives in supergraph calculations. The resulting rules are: (1) First do all algebra exactly as in D = 4; (2) Then do the momentum integrals as in ordinary dimensional regularization. This regularization procedure needs extra rules before one can say that it is consistent. Such extra rules needed for superconformal anomalies are discussed. Problems associated with renormalizability and higher order loops are also discussed

Multi-dimensional analysis of the ECC behavior in the UPI plant Kori Unit 1

International Nuclear Information System (INIS)

Bae, Sungwon; Chung, Bub-Dong; Bang, Young Seok

2008-01-01

A multi-dimensional transient analysis during the LBLOCA of the Kori Unit 1 has been performed by using the MARS code. Based on 1-D nodalization of the Kori Unit 1, the reactor vessel nodalizations have been replaced by the multi-dimensional component. The multi-dimensional component for the reactor vessel is designed as 5 radial, 8 peripheral, and 21 vertical grids. It is assumed that the fuel assemblies are homogeneously distributed in inner 3 radial grids. The outer 1 radial grid region is modeled as the core bypass. The outer-model 1 radial grid is used for the downcomer region. The corresponding heat structures and fuels are modified to fit for the multi-dimensional reactor vessel model. The form drag coefficients for the upper plenum and the core have been designated as 0.6 and 9.39, respectively. The form drag coefficients for the radial and peripheral directions are assigned to the same on the assumption of homogeneous distribution of the flow obstacles. After obtaining the 102% power steady operation condition, cold leg LOCA simulation is performed during 400 second period. The multi-dimensional steady run results show no severe differences compared to the traditional 1-D nodalization results. After the ECC injection starts, a liquid pool is maintained at the upper plenum because the ECCS water can not overcome the upward gas flow that comes from the reactor core through the upper tie plate. The depth of ECCS water pool is predicted as about 20% of the total height from the upper tie plate and the center line of the hot leg pipe. At the vicinity region of the active ECCS show higher depth of liquid pool. The accumulated water flow rate passing the upper tie plate is calculated by the transient result. Much downward water flow is obtained at the outer-most region of upper plenum space. The downward flow dominant region is about 32.3% of the total upper tie plate area. The accumulated ECCS bypass ratio is predicted as 27.64% at 300 second. It is calculated

Multidimensional Lévy walk and its scaling limits

International Nuclear Information System (INIS)

Teuerle, Marek; Magdziarz, Marcin; Żebrowski, Piotr

2012-01-01

In this paper we obtain the scaling limit of a multidimensional Lévy walk and describe the detailed structure of the limiting process. The scaling limit is a subordinated α-stable Lévy motion with the parent process and subordinator being strongly dependent processes. The corresponding Langevin picture is derived. We also introduce a useful method of simulating Lévy walks with a predefined spectral measure, which controls the direction of each jump. Our approach can be applied in the analysis of real-life data—we are able to recover the spectral measure from the data and obtain the full characterization of a Lévy walk. We also give examples of some useful spectral measures, which cover a large class of possible scenarios in the modeling of real-life phenomena. (paper)

Structural Elucidation and Biological Activity of a Highly Regular Fucosylated Glycosaminoglycan from the Edible Sea Cucumber Stichopus herrmanni.

Science.gov (United States)

Li, Xiaomei; Luo, Lan; Cai, Ying; Yang, Wenjiao; Lin, Lisha; Li, Zi; Gao, Na; Purcell, Steven W; Wu, Mingyi; Zhao, Jinhua

2017-10-25

Edible sea cucumbers are widely used as a health food and medicine. A fucosylated glycosaminoglycan (FG) was purified from the high-value sea cucumber Stichopus herrmanni. Its physicochemical properties and structure were analyzed and characterized by chemical and instrumental methods. Chemical analysis indicated that this FG with a molecular weight of ∼64 kDa is composed of N-acetyl-d-galactosamine, d-glucuronic acid (GlcA), and l-fucose. Structural analysis clarified that the FG contains the chondroitin sulfate E-like backbone, with mostly 2,4-di-O-sulfated (85%) and some 3,4-di-O-sulfated (10%) and 4-O-sulfated (5%) fucose side chains that link to the C3 position of GlcA. This FG is structurally highly regular and homogeneous, differing from the FGs of other sea cucumbers, for its sulfation patterns are simpler. Biological activity assays indicated that it is a strong anticoagulant, inhibiting thrombin and intrinsic factor Xase. Our results expand the knowledge on structural types of FG and illustrate its biological activity as a functional food material.

Multidimensional artificial field embedding with spatial sensitivity

CSIR Research Space (South Africa)

Lunga, D

2013-06-01

Full Text Available Multidimensional embedding is a technique useful for characterizing spectral signature relations in hyperspectral images. However, such images consist of disjoint similar spectral classes that are spatially sensitive, thus presenting challenges...

Assessment of health surveys: fitting a multidimensional graded response model.

Science.gov (United States)

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Regularization by External Variables

DEFF Research Database (Denmark)

Bossolini, Elena; Edwards, R.; Glendinning, P. A.

2016-01-01

Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind of regula......Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind...

Regular Single Valued Neutrosophic Hypergraphs

Directory of Open Access Journals (Sweden)

Muhammad Aslam Malik

2016-12-01

Full Text Available In this paper, we define the regular and totally regular single valued neutrosophic hypergraphs, and discuss the order and size along with properties of regular and totally regular single valued neutrosophic hypergraphs. We also extend work on completeness of single valued neutrosophic hypergraphs.

Guangxi crustal structural evolution and the formation and distribution regularities of U-rich strata

International Nuclear Information System (INIS)

Kang Zili.

1989-01-01

Based on summing up Guangxi geotectonic features and evolutionary regularities, this paper discusses the occurrence features, formation conditions and time-space distribution regularities of various U-rich strata during the development of geosyncline, platform and diwa stages, Especially, during diwa stage all those U-rich strata might be reworked to a certain degree and resulted in the mobilization of uranium, then enriching to form polygenetic composite uranium ore deposits with stratabound features. This study will be helpful for prospecting in the region

MCMC estimation of multidimensional IRT models

NARCIS (Netherlands)

Beguin, Anton; Glas, Cornelis A.W.

1998-01-01

A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will

Implementation of multidimensional databases in column-oriented NoSQL systems

OpenAIRE

Chevalier, Max; El Malki, Mohammed; Kopliku, Arlind; Teste, Olivier; Tournier, Ronan

2015-01-01

International audience; NoSQL (Not Only SQL) systems are becoming popular due to known advantages such as horizontal scalability and elasticity. In this paper, we study the implementation of multidimensional data warehouses with columnoriented NoSQL systems. We define mapping rules that transform the conceptual multidimensional data model to logical column-oriented models. We consider three different logical models and we use them to instantiate data warehouses. We focus on data loading, mode...

Portable laser synthesizer for high-speed multi-dimensional spectroscopy

Science.gov (United States)

Demos, Stavros G [Livermore, CA; Shverdin, Miroslav Y [Sunnyvale, CA; Shirk, Michael D [Brentwood, CA

2012-05-29

Portable, field-deployable laser synthesizer devices designed for multi-dimensional spectrometry and time-resolved and/or hyperspectral imaging include a coherent light source which simultaneously produces a very broad, energetic, discrete spectrum spanning through or within the ultraviolet, visible, and near infrared wavelengths. The light output is spectrally resolved and each wavelength is delayed with respect to each other. A probe enables light delivery to a target. For multidimensional spectroscopy applications, the probe can collect the resulting emission and deliver this radiation to a time gated spectrometer for temporal and spectral analysis.

On generalized de Rham-Hodge complexes, the related characteristic Chern classes and some applications to integrable multi-dimensional differential systems on Riemannian manifolds

International Nuclear Information System (INIS)

Bogolubov, Nikolai N. Jr.; Prykarpatsky, Anatoliy K.

2006-12-01

The differential-geometric aspects of generalized de Rham-Hodge complexes naturally related with integrable multi-dimensional differential systems of M. Gromov type, as well as the geometric structure of Chern characteristic classes are studied. Special differential invariants of the Chern type are constructed, their importance for the integrability of multi-dimensional nonlinear differential systems on Riemannian manifolds is discussed. An example of the three-dimensional Davey-Stewartson type nonlinear strongly integrable differential system is considered, its Cartan type connection mapping and related Chern type differential invariants are analyzed. (author)

Void Structures in Regularly Patterned ZnO Nanorods Grown with the Hydrothermal Method

Directory of Open Access Journals (Sweden)

Yu-Feng Yao

2014-01-01

Full Text Available The void structures and related optical properties after thermal annealing with ambient oxygen in regularly patterned ZnO nanrorod (NR arrays grown with the hydrothermal method are studied. In increasing the thermal annealing temperature, void distribution starts from the bottom and extends to the top of an NR in the vertical (c-axis growth region. When the annealing temperature is higher than 400°C, void distribution spreads into the lateral (m-axis growth region. Photoluminescence measurement shows that the ZnO band-edge emission, in contrast to defect emission in the yellow-red range, is the strongest under the n-ZnO NR process conditions of 0.003 M in Ga-doping concentration and 300°C in thermal annealing temperature with ambient oxygen. Energy dispersive X-ray spectroscopy data indicate that the concentration of hydroxyl groups in the vertical growth region is significantly higher than that in the lateral growth region. During thermal annealing, hydroxyl groups are desorbed from the NR leaving anion vacancies for reacting with cation vacancies to form voids.

Exploring and linking biomedical resources through multidimensional semantic spaces.

Science.gov (United States)

Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

2012-01-25

The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for

Constrained Perturbation Regularization Approach for Signal Estimation Using Random Matrix Theory

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-10-06

In this work, we propose a new regularization approach for linear least-squares problems with random matrices. In the proposed constrained perturbation regularization approach, an artificial perturbation matrix with a bounded norm is forced into the system model matrix. This perturbation is introduced to improve the singular-value structure of the model matrix and, hence, the solution of the estimation problem. Relying on the randomness of the model matrix, a number of deterministic equivalents from random matrix theory are applied to derive the near-optimum regularizer that minimizes the mean-squared error of the estimator. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods for various estimated signal characteristics. In addition, simulations show that our approach is robust in the presence of model uncertainty.

Image deblurring using a perturbation-basec regularization approach

KAUST Repository

Alanazi, Abdulrahman

2017-11-02

The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.

Image deblurring using a perturbation-basec regularization approach

KAUST Repository

Alanazi, Abdulrahman; Ballal, Tarig; Masood, Mudassir; Al-Naffouri, Tareq Y.

2017-01-01

The image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.

A Multidimensional Model of School Dropout from an 8-Year Longitudinal Study in a General High School Population

Science.gov (United States)

Fortin, Laurier; Marcotte, Diane; Diallo, Thierno; Potvin, Pierre; Royer, Egide

2013-01-01

This study tests an empirical multidimensional model of school dropout, using data collected in the first year of an 8-year longitudinal study, with first year high school students aged 12-13 years. Structural equation modeling analyses show that five personal, family, and school latent factors together contribute to school dropout identified at…

Assessing the Multidimensional Relationship Between Medication Beliefs and Adherence in Older Adults With Hypertension Using Polynomial Regression.

Science.gov (United States)

Dillon, Paul; Phillips, L Alison; Gallagher, Paul; Smith, Susan M; Stewart, Derek; Cousins, Gráinne

2018-02-05

The Necessity-Concerns Framework (NCF) is a multidimensional theory describing the relationship between patients' positive and negative evaluations of their medication which interplay to influence adherence. Most studies evaluating the NCF have failed to account for the multidimensional nature of the theory, placing the separate dimensions of medication "necessity beliefs" and "concerns" onto a single dimension (e.g., the Beliefs about Medicines Questionnaire-difference score model). To assess the multidimensional effect of patient medication beliefs (concerns and necessity beliefs) on medication adherence using polynomial regression with response surface analysis. Community-dwelling older adults >65 years (n = 1,211) presenting their own prescription for antihypertensive medication to 106 community pharmacies in the Republic of Ireland rated their concerns and necessity beliefs to antihypertensive medications at baseline and their adherence to antihypertensive medication at 12 months via structured telephone interview. Confirmatory polynomial regression found the difference-score model to be inaccurate; subsequent exploratory analysis identified a quadratic model to be the best-fitting polynomial model. Adherence was lowest among those with strong medication concerns and weak necessity beliefs, and adherence was greatest for those with weak concerns and strong necessity beliefs (slope β = -0.77, pnecessity beliefs had lower adherence than those with simultaneously low concerns and necessity beliefs (slope β = -0.36, p = .004; curvature β = -0.25, p = .003). The difference-score model fails to account for the potential nonreciprocal effects. Results extend evidence supporting the use of polynomial regression to assess the multidimensional effect of medication beliefs on adherence.

Effect Size Measures for Differential Item Functioning in a Multidimensional IRT Model

Science.gov (United States)

Suh, Youngsuk

2016-01-01

This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P-difference and unsigned weighted P-difference. The performance of…

Development and assessment of multi-dimensional flow model in MARS compared with the RPI air-water experiment

International Nuclear Information System (INIS)

Lee, Seok Min; Lee, Un Chul; Bae, Sung Won; Chung, Bub Dong

2004-01-01

The Multi-Dimensional flow models in system code have been developed during the past many years. RELAP5-3D, CATHARE and TRACE has its specific multi-dimensional flow models and successfully applied it to the system safety analysis. In KAERI, also, MARS(Multi-dimensional Analysis of Reactor Safety) code was developed by integrating RELAP5/MOD3 code and COBRA-TF code. Even though COBRA-TF module can analyze three-dimensional flow models, it has a limitation to apply 3D shear stress dominant phenomena or cylindrical geometry. Therefore, Multi-dimensional analysis models are newly developed by implementing three-dimensional momentum flux and diffusion terms. The multi-dimensional model has been assessed compared with multi-dimensional conceptual problems and CFD code results. Although the assessment results were reasonable, the multi-dimensional model has not been validated to two-phase flow using experimental data. In this paper, the multi-dimensional air-water two-phase flow experiment was simulated and analyzed

Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.

SparseBeads data: benchmarking sparsity-regularized computed tomography

DEFF Research Database (Denmark)

Jørgensen, Jakob Sauer; Coban, Sophia B.; Lionheart, William R. B.

2017-01-01

-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels...

On a correspondence between regular and non-regular operator monotone functions

DEFF Research Database (Denmark)

Gibilisco, P.; Hansen, Frank; Isola, T.

2009-01-01

We prove the existence of a bijection between the regular and the non-regular operator monotone functions satisfying a certain functional equation. As an application we give a new proof of the operator monotonicity of certain functions related to the Wigner-Yanase-Dyson skew information....

Multi-dimensional Bin Packing Problems with Guillotine Constraints

DEFF Research Database (Denmark)

Amossen, Rasmus Resen; Pisinger, David

2010-01-01

The problem addressed in this paper is the decision problem of determining if a set of multi-dimensional rectangular boxes can be orthogonally packed into a rectangular bin while satisfying the requirement that the packing should be guillotine cuttable. That is, there should exist a series of face...... parallel straight cuts that can recursively cut the bin into pieces so that each piece contains a box and no box has been intersected by a cut. The unrestricted problem is known to be NP-hard. In this paper we present a generalization of a constructive algorithm for the multi-dimensional bin packing...... problem, with and without the guillotine constraint, based on constraint programming....

The Evolution of Frequency Distributions: Relating Regularization to Inductive Biases through Iterated Learning

Science.gov (United States)

Reali, Florencia; Griffiths, Thomas L.

2009-01-01

The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

Science.gov (United States)

Coromaldi, Manuela; Zoli, Mariangela

2012-01-01

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…

Measures for a multidimensional multiverse

Science.gov (United States)

Chung, Hyeyoun

2015-04-01

We explore the phenomenological implications of generalizing the causal patch and fat geodesic measures to a multidimensional multiverse, where the vacua can have differing numbers of large dimensions. We consider a simple model in which the vacua are nucleated from a D -dimensional parent spacetime through dynamical compactification of the extra dimensions, and compute the geometric contribution to the probability distribution of observations within the multiverse for each measure. We then study how the shape of this probability distribution depends on the time scales for the existence of observers, for vacuum domination, and for curvature domination (tobs,tΛ , and tc, respectively.) In this work we restrict ourselves to bubbles with positive cosmological constant, Λ . We find that in the case of the causal patch cutoff, when the bubble universes have p +1 large spatial dimensions with p ≥2 , the shape of the probability distribution is such that we obtain the coincidence of time scales tobs˜tΛ˜tc . Moreover, the size of the cosmological constant is related to the size of the landscape. However, the exact shape of the probability distribution is different in the case p =2 , compared to p ≥3 . In the case of the fat geodesic measure, the result is even more robust: the shape of the probability distribution is the same for all p ≥2 , and we once again obtain the coincidence tobs˜tΛ˜tc . These results require only very mild conditions on the prior probability of the distribution of vacua in the landscape. Our work shows that the observed double coincidence of time scales is a robust prediction even when the multiverse is generalized to be multidimensional; that this coincidence is not a consequence of our particular Universe being (3 +1 )-dimensional; and that this observable cannot be used to preferentially select one measure over another in a multidimensional multiverse.

Multidimensional HAM-conditions

DEFF Research Database (Denmark)

Hansen, Ernst Jan de Place

Heat, Air and Moisture (HAM) conditions, experimental data are needed. Tests were performed in the large climate simulator at SBi involving full-scale wall elements. The elements were exposed for steady-state conditions, and temperature cycles simulating April and September climate in Denmark....... The effect on the moisture and temperature conditions of the addition of a vapour barrier and an outer cladding on timber frame walls was studied. The report contains comprehensive appendices documenting the full-scale tests. The tests were performed as a part of the project 'Model for Multidimensional Heat......, Air and Moisture Conditions in Building Envelope Components' carried out as a co-project between DTU Byg and SBi....

Image super-resolution reconstruction based on regularization technique and guided filter

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

2017-06-01

In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

Oscillatory regime in the multidimensional homogeneous cosmological models induced by a vector field

International Nuclear Information System (INIS)

Benini, R; Kirillov, A A; Montani, Giovanni

2005-01-01

We show that in multidimensional gravity, vector fields completely determine the structure and properties of singularity. It turns out that in the presence of a vector field the oscillatory regime exists in all spatial dimensions and for all homogeneous models. By analysing the Hamiltonian equations we derive the Poincare return map associated with the Kasner indexes and fix the rules according to which the Kasner vectors rotate. In correspondence to a four-dimensional spacetime, the oscillatory regime here constructed overlaps the usual Belinski-Khalatnikov-Liftshitz one

SparseBeads data: benchmarking sparsity-regularized computed tomography

Science.gov (United States)

Jørgensen, Jakob S.; Coban, Sophia B.; Lionheart, William R. B.; McDonald, Samuel A.; Withers, Philip J.

2017-12-01

Sparsity regularization (SR) such as total variation (TV) minimization allows accurate image reconstruction in x-ray computed tomography (CT) from fewer projections than analytical methods. Exactly how few projections suffice and how this number may depend on the image remain poorly understood. Compressive sensing connects the critical number of projections to the image sparsity, but does not cover CT, however empirical results suggest a similar connection. The present work establishes for real CT data a connection between gradient sparsity and the sufficient number of projections for accurate TV-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels, number of projections and noise levels to allow the systematic assessment of parameters affecting performance of SR reconstruction algorithms6. Using the SparseBeads data, TV-regularized reconstruction quality was assessed as a function of numbers of projections and gradient sparsity. The critical number of projections for satisfactory TV-regularized reconstruction increased almost linearly with the gradient sparsity. This establishes a quantitative guideline from which one may predict how few projections to acquire based on expected sample sparsity level as an aid in planning of dose- or time-critical experiments. The results are expected to hold for samples of similar characteristics, i.e. consisting of few, distinct phases with relatively simple structure. Such cases are plentiful in porous media, composite materials, foams, as well as non-destructive testing and metrology. For samples of other characteristics the proposed methodology may be used to investigate similar relations.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

Science.gov (United States)

Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert

2010-03-01

We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 10(6) × 10(6) incomplete matrix with 10(5) observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques.

Selective confinement of vibrations in composite systems with alternate quasi-regular sequences

International Nuclear Information System (INIS)

Montalban, A.; Velasco, V.R.; Tutor, J.; Fernandez-Velicia, F.J.

2007-01-01

We have studied the atom displacements and the vibrational frequencies of 1D systems formed by combinations of Fibonacci, Thue-Morse and Rudin-Shapiro quasi-regular stacks and their alternate ones. The materials are described by nearest-neighbor force constants and the corresponding atom masses, particularized to the Al, Ag systems. These structures exhibit differences in the frequency spectrum as compared to the original simple quasi-regular generations but the most important feature is the presence of separate confinement of the atom displacements in one of the sequences forming the total composite structure for different frequency ranges

Selective confinement of vibrations in composite systems with alternate quasi-regular sequences

Energy Technology Data Exchange (ETDEWEB)

Montalban, A. [Departamento de Ciencia y Tecnologia de Materiales, Division de Optica, Universidad Miguel Hernandez, 03202 Elche (Spain); Velasco, V.R. [Instituto de Ciencia de Materiales de Madrid, CSIC, Sor Juana Ines de la Cruz 3, 28049 Madrid (Spain)]. E-mail: vrvr@icmm.csic.es; Tutor, J. [Departamento de Fisica Aplicada, Universidad Autonoma de Madrid, Cantoblanco, 28049 Madrid (Spain); Fernandez-Velicia, F.J. [Departamento de Fisica de los Materiales, Facultad de Ciencias, Universidad Nacional de Educacion a Distancia, Senda del Rey 9, 28080 Madrid (Spain)

2007-01-01

We have studied the atom displacements and the vibrational frequencies of 1D systems formed by combinations of Fibonacci, Thue-Morse and Rudin-Shapiro quasi-regular stacks and their alternate ones. The materials are described by nearest-neighbor force constants and the corresponding atom masses, particularized to the Al, Ag systems. These structures exhibit differences in the frequency spectrum as compared to the original simple quasi-regular generations but the most important feature is the presence of separate confinement of the atom displacements in one of the sequences forming the total composite structure for different frequency ranges.

Regularization of Hamilton-Lagrangian guiding center theories

International Nuclear Information System (INIS)

Correa-Restrepo, D.; Wimmel, H.K.

1985-04-01

The Hamilton-Lagrangian guiding-center (G.C.) theories of Littlejohn, Wimmel, and Pfirsch show a singularity for B-fields with non-vanishing parallel curl at a critical value of vsub(parallel), which complicates applications. The singularity is related to a sudden breakdown, at a critical vsub(parallel), of gyration in the exact particle mechanics. While the latter is a real effect, the G.C. singularity can be removed. To this end a regularization method is defined that preserves the Hamilton-Lagrangian structure and the conservation theorems. For demonstration this method is applied to the standard G.C. theory (without polarization drift). Liouville's theorem and G.C. kinetic equations are also derived in regularized form. The method could equally well be applied to the case with polarization drift and to relativistic G.C. theory. (orig.)

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...

Boosting Maintenance in Working Memory with Temporal Regularities

Science.gov (United States)

Plancher, Gaën; Lévêque, Yohana; Fanuel, Lison; Piquandet, Gaëlle; Tillmann, Barbara

2018-01-01

Music cognition research has provided evidence for the benefit of temporally regular structures guiding attention over time. The present study investigated whether maintenance in working memory can benefit from an isochronous rhythm. Participants were asked to remember series of 6 letters for serial recall. In the rhythm condition of Experiment…

Modelling of multidimensional quantum systems by the numerical functional integration

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.; Zhidkov, E.P.

1990-01-01

The employment of the numerical functional integration for the description of multidimensional systems in quantum and statistical physics is considered. For the multiple functional integrals with respect to Gaussian measures in the full separable metric spaces the new approximation formulas exact on a class of polynomial functionals of a given summary degree are constructed. The use of the formulas is demonstrated on example of computation of the Green function and the ground state energy in multidimensional Calogero model. 15 refs.; 2 tabs

A Framework for Semi-Automated Implementation of Multidimensional Data Models

Directory of Open Access Journals (Sweden)

Ilona Mariana NAGY

2012-08-01

Full Text Available Data warehousing solution development represents a challenging task which requires the employment of considerable resources on behalf of enterprises and sustained commitment from the stakeholders. Costs derive mostly from the amount of time invested in the design and physical implementation of these large projects, time that we consider, may be decreased through the automation of several processes. Thus, we present a framework for semi-automated implementation of multidimensional data models and introduce an automation prototype intended to reduce the time of data structures generation in the warehousing environment. Our research is focused on the design of an automation component and the development of a corresponding prototype from technical metadata.

A new approach to nonlinear constrained Tikhonov regularization

KAUST Repository

Ito, Kazufumi

2011-09-16

We present a novel approach to nonlinear constrained Tikhonov regularization from the viewpoint of optimization theory. A second-order sufficient optimality condition is suggested as a nonlinearity condition to handle the nonlinearity of the forward operator. The approach is exploited to derive convergence rate results for a priori as well as a posteriori choice rules, e.g., discrepancy principle and balancing principle, for selecting the regularization parameter. The idea is further illustrated on a general class of parameter identification problems, for which (new) source and nonlinearity conditions are derived and the structural property of the nonlinearity term is revealed. A number of examples including identifying distributed parameters in elliptic differential equations are presented. © 2011 IOP Publishing Ltd.

Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India.

Science.gov (United States)

Mohanty, Sanjay K; Agrawal, Nand Kishor; Mahapatra, Bidhubhusan; Choudhury, Dhrupad; Tuladhar, Sabarnee; Holmgren, E Valdemar

2017-01-18

Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is

Quantum and Multidimensional Explanations in a Neurobiological Context of Mind.

Science.gov (United States)

Korf, Jakob

2015-08-01

This article examines the possible relevance of physical-mathematical multidimensional or quantum concepts aiming at understanding the (human) mind in a neurobiological context. Some typical features of the quantum and multidimensional concepts are briefly introduced, including entanglement, superposition, holonomic, and quantum field theories. Next, we consider neurobiological principles, such as the brain and its emerging (physical) mind, evolutionary and ontological origins, entropy, syntropy/neg-entropy, causation, and brain energy metabolism. In many biological processes, including biochemical conversions, protein folding, and sensory perception, the ubiquitous involvement of quantum mechanisms is well recognized. Quantum and multidimensional approaches might be expected to help describe and model both brain and mental processes, but an understanding of their direct involvement in mental activity, that is, without mediation by molecular processes, remains elusive. More work has to be done to bridge the gap between current neurobiological and physical-mathematical concepts with their associated quantum-mind theories. © The Author(s) 2014.

Almost-sure identifiability of multidimensional harmonic retrieval

NARCIS (Netherlands)

Jiang, T; Sidiropoulos, ND; ten Berge, JMF

Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the

Multi-view clustering via multi-manifold regularized non-negative matrix factorization.

Science.gov (United States)

Zong, Linlin; Zhang, Xianchao; Zhao, Long; Yu, Hong; Zhao, Qianli

2017-04-01

Non-negative matrix factorization based multi-view clustering algorithms have shown their competitiveness among different multi-view clustering algorithms. However, non-negative matrix factorization fails to preserve the locally geometrical structure of the data space. In this paper, we propose a multi-manifold regularized non-negative matrix factorization framework (MMNMF) which can preserve the locally geometrical structure of the manifolds for multi-view clustering. MMNMF incorporates consensus manifold and consensus coefficient matrix with multi-manifold regularization to preserve the locally geometrical structure of the multi-view data space. We use two methods to construct the consensus manifold and two methods to find the consensus coefficient matrix, which leads to four instances of the framework. Experimental results show that the proposed algorithms outperform existing non-negative matrix factorization based algorithms for multi-view clustering. Copyright © 2017 Elsevier Ltd. All rights reserved.

EU's external energy governance: A multidimensional analysis of the southern gas corridor

International Nuclear Information System (INIS)

Abbasov, Faig Galib

2014-01-01

The major objective of this paper is to apply a multidimensional lens to the European Union's (EU's) vision to the yet to be establish Southern Gas Corridor. I will argue that, the EU's natural gas vision towards the Caspian basin is based not only on bringing additional gas volumes to the EU markets in order to ensure physical security of supply. It is rather multidimensional external governance geared, firstly, towards absorbing all the actors along the whole value chain in to the EU's common energy regulatory framework and shifting energy provision from a bilateral political domain onto a multilateral market domain. Secondly, it is a process of diffusion of norms and values into the governance system of the energy partners. - Highlights: • EU's Southern Gas Corridor strategy is structurally embedded in its external governance. • The counterpart of the EU's energy imports is its attempt to export its acquis. • EU's energy security necessitates diffusion of norms and values to producers

MODELO MULTIDIMENSIONAL

Directory of Open Access Journals (Sweden)

Alexis Cedeño Trujillo

2006-04-01

Full Text Available

Data Warehousing, es una tecnología para el almacenamiento de grandes volúmenes de datos en una amplia perspectiva de tiempo para el soporte a la toma de decisiones. Debido a su orientación analítica, impone un procesamiento distinto al de los sistemas operacionales y requiere de un diseño de base de datos más cercano a la visión de los usuarios finales, permitiendo que sea más fácil la recuperación de información y la navegación. Este diseño de base de datos se conoce como modelo multidimensional, este artículo, abordará sus características principales.

A human rights-consistent approach to multidimensional welfare measurement applied to sub-Saharan Africa

DEFF Research Database (Denmark)

Arndt, Channing; Mahrt, Kristi; Hussain, Azhar

2017-01-01

is in reality inconsistent with the Universal Declaration of Human Rights principles of indivisibility, inalienability, and equality. We show that a first-order dominance methodology maintains consistency with basic principles, discuss the properties of the multidimensional poverty index and first......The rights-based approach to development targets progress towards the realization of 30 articles set forth in the Universal Declaration of Human Rights. Progress is frequently measured using the multidimensional poverty index. While elegant and useful, the multidimensional poverty index...

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

Energy Technology Data Exchange (ETDEWEB)

Fang, X.; Xia, C.; Keppens, R. [Centre for mathematical Plasma Astrophysics, Department of Mathematics, KU Leuven, B-3001 Leuven (Belgium)

2013-07-10

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

International Nuclear Information System (INIS)

Fang, X.; Xia, C.; Keppens, R.

2013-01-01

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

A Multidimensional Theory of Suicide.

Science.gov (United States)

Leenaars, Antoon A; Dieserud, Gudrun; Wenckstern, Susanne; Dyregrov, Kari; Lester, David; Lyke, Jennifer

2018-04-05

Theory is the foundation of science; this is true in suicidology. Over decades of studies of suicide notes, Leenaars developed a multidimensional model of suicide, with international (crosscultural) studies and independent verification. To corroborate Leenaars's theory with a psychological autopsy (PA) study, examining age and sex of the decedent, and survivor's relationship to deceased. A PA study in Norway, with 120 survivors/informants was undertaken. Leenaars' theoretical-conceptual (protocol) analysis was undertaken of the survivors' narratives and in-depth interviews combined. Substantial interjudge reliability was noted (κ = .632). Overall, there was considerable confirmatory evidence of Leenaars's intrapsychic and interpersonal factors in suicide survivors' narratives. Differences were found in the age of the decedent, but not in sex, nor in the survivor's closeness of the relationship. Older deceased people were perceived to exhibit more heightened unbearable intrapsychic pain, associated with the suicide. Leenaars's theory has corroborative verification, through the decedents' suicide notes and the survivors' narratives. However, the multidimensional model needs further testing to develop a better evidence-based way of understanding suicide.

Development and Validation of Multi-Dimensional Personality ...

African Journals Online (AJOL)

This study was carried out to establish the scientific processes for the development and validation of Multi-dimensional Personality Inventory (MPI). The process of development and validation occurred in three phases with five components of Agreeableness, Conscientiousness, Emotional stability, Extroversion, and ...

Multi-omic data integration enables discovery of hidden biological regularities

DEFF Research Database (Denmark)

Ebrahim, Ali; Brunk, Elizabeth; Tan, Justin

2016-01-01

Rapid growth in size and complexity of biological data sets has led to the 'Big Data to Knowledge' challenge. We develop advanced data integration methods for multi- level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration...... of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome- scale models, based on genomic and bibliomic data......, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can...

Analysis of Multidimensional Poverty: Theory and Case Studies ...

International Development Research Centre (IDRC) Digital Library (Canada)

2009-08-18

Aug 18, 2009 ... ... of applying a factorial technique, Multiple Correspondence Analysis, to poverty analysis. ... Analysis of Multidimensional Poverty: Theory and Case Studies ... agreement to support joint research projects in December 2017.

MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation.

Science.gov (United States)

Li, Xutao; Ng, Michael K; Cong, Gao; Ye, Yunming; Wu, Qingyao

2017-08-01

With the advancement of data acquisition techniques, tensor (multidimensional data) objects are increasingly accumulated and generated, for example, multichannel electroencephalographies, multiview images, and videos. In these applications, the tensor objects are usually nonnegative, since the physical signals are recorded. As the dimensionality of tensor objects is often very high, a dimension reduction technique becomes an important research topic of tensor data. From the perspective of geometry, high-dimensional objects often reside in a low-dimensional submanifold of the ambient space. In this paper, we propose a new approach to perform the dimension reduction for nonnegative tensor objects. Our idea is to use nonnegative Tucker decomposition (NTD) to obtain a set of core tensors of smaller sizes by finding a common set of projection matrices for tensor objects. To preserve geometric information in tensor data, we employ a manifold regularization term for the core tensors constructed in the Tucker decomposition. An algorithm called manifold regularization NTD (MR-NTD) is developed to solve the common projection matrices and core tensors in an alternating least squares manner. The convergence of the proposed algorithm is shown, and the computational complexity of the proposed method scales linearly with respect to the number of tensor objects and the size of the tensor objects, respectively. These theoretical results show that the proposed algorithm can be efficient. Extensive experimental results have been provided to further demonstrate the effectiveness and efficiency of the proposed MR-NTD algorithm.

Translation and Validation of the Multidimensional Dyspnea-12 Questionnaire.

Science.gov (United States)

Amado Diago, Carlos Antonio; Puente Maestu, Luis; Abascal Bolado, Beatriz; Agüero Calvo, Juan; Hernando Hernando, Mercedes; Puente Bats, Irene; Agüero Balbín, Ramón

2018-02-01

Dyspnea is a multidimensional symptom, but this multidimensionality is not considered in most dyspnea questionnaires. The Dyspnea-12 takes a multidimensional approach to the assessment of dyspnea, specifically the sensory and the affective response. The objective of this study was to translate into Spanish and validate the Dyspnea-12 questionnaire. The original English version of the Dyspnea-12 questionnaire was translated into Spanish and backtranslated to analyze its equivalence. Comprehension of the text was verified by analyzing the responses of 10 patients. Reliability and validation of the questionnaire were studied in an independent group of COPD patients attending the pulmonology clinics of Hospital Universitario Marqués de Valdecilla, diagnosed and categorized according to GOLD guidelines. The mean age of the group (n=51) was 65 years and mean FEV1 was 50%. All patients understood all questions of the translated version of Dyspnea-12. Internal consistency of the questionnaire was α=0.937 and intraclass correlation coefficient was=.969; P<.001. Statistically significant correlations were found with HADS (anxiety r=.608 and depression r=.615), mMRC dyspnea (r=.592), 6MWT (r=-0.445), FEV1 (r=-0.312), all dimensions of CRQ-SAS (dyspnea r=-0.626; fatigue r=-0.718; emotional function r=-0.663; mastery r=-0.740), CAT (r=0.669), and baseline dyspnea index (r=-0.615). Dyspnea-12 scores were 10.32 points higher in symptomatic GOLD groups (B and D) (P<.001). The Spanish version of Dyspnea-12 is a valid and reliable instrument to study the multidimensional nature of dyspnea. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

On simplified application of multidimensional Savitzky-Golay filters and differentiators

Science.gov (United States)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

Improvement of multi-dimensional realistic thermal-hydraulic system analysis code, MARS 1.3

International Nuclear Information System (INIS)

Lee, Won Jae; Chung, Bub Dong; Jeong, Jae Jun; Ha, Kwi Seok

1998-09-01

The MARS (Multi-dimensional Analysis of Reactor Safety) code is a multi-dimensional, best-estimate thermal-hydraulic system analysis code. This report describes the new features that have been improved in the MARS 1.3 code since the release of MARS 1.3 in July 1998. The new features include: - implementation of point kinetics model into the 3D module - unification of the heat structure model - extension of the control function to the 3D module variables - improvement of the 3D module input check function. Each of the items has been implemented in the developmental version of the MARS 1.3.1 code and, then, independently verified and assessed. The effectiveness of the new features is well verified and it is shown that these improvements greatly extend the code capability and enhance the user friendliness. Relevant input data changes are also described. In addition to the improvements, this report briefly summarizes the future code developmental activities that are being carried out or planned, such as coupling of MARS 1.3 with the containment code CONTEMPT and the three-dimensional reactor kinetics code MASTER 2.0. (author). 8 refs

Improvement of multi-dimensional realistic thermal-hydraulic system analysis code, MARS 1.3

Energy Technology Data Exchange (ETDEWEB)

Lee, Won Jae; Chung, Bub Dong; Jeong, Jae Jun; Ha, Kwi Seok

1998-09-01

The MARS (Multi-dimensional Analysis of Reactor Safety) code is a multi-dimensional, best-estimate thermal-hydraulic system analysis code. This report describes the new features that have been improved in the MARS 1.3 code since the release of MARS 1.3 in July 1998. The new features include: - implementation of point kinetics model into the 3D module - unification of the heat structure model - extension of the control function to the 3D module variables - improvement of the 3D module input check function. Each of the items has been implemented in the developmental version of the MARS 1.3.1 code and, then, independently verified and assessed. The effectiveness of the new features is well verified and it is shown that these improvements greatly extend the code capability and enhance the user friendliness. Relevant input data changes are also described. In addition to the improvements, this report briefly summarizes the future code developmental activities that are being carried out or planned, such as coupling of MARS 1.3 with the containment code CONTEMPT and the three-dimensional reactor kinetics code MASTER 2.0. (author). 8 refs.

Lagrangian multiforms and multidimensional consistency

Energy Technology Data Exchange (ETDEWEB)

Lobb, Sarah; Nijhoff, Frank [Department of Applied Mathematics, University of Leeds, Leeds LS2 9JT (United Kingdom)

2009-10-30

We show that well-chosen Lagrangians for a class of two-dimensional integrable lattice equations obey a closure relation when embedded in a higher dimensional lattice. On the basis of this property we formulate a Lagrangian description for such systems in terms of Lagrangian multiforms. We discuss the connection of this formalism with the notion of multidimensional consistency, and the role of the lattice from the point of view of the relevant variational principle.

The 'thousand words' problem: Summarizing multi-dimensional data

International Nuclear Information System (INIS)

Scott, David M.

2011-01-01

Research highlights: → Sophisticated process sensors produce large multi-dimensional data sets. → Plant control systems cannot handle images or large amounts of data. → Various techniques reduce the dimensionality, extracting information from raw data. → Simple 1D and 2D methods can often be extended to 3D and 4D applications. - Abstract: An inherent difficulty in the application of multi-dimensional sensing to process monitoring and control is the extraction and interpretation of useful information. Ultimately the measured data must be collapsed into a relatively small number of values that capture the salient characteristics of the process. Although multiple dimensions are frequently necessary to isolate a particular physical attribute (such as the distribution of a particular chemical species in a reactor), plant control systems are not equipped to use such data directly. The production of a multi-dimensional data set (often displayed as an image) is not the final step of the measurement process, because information must still be extracted from the raw data. In the metaphor of one picture being equal to a thousand words, the problem becomes one of paraphrasing a lengthy description of the image with one or two well-chosen words. Various approaches to solving this problem are discussed using examples from the fields of particle characterization, image processing, and process tomography.

Multidimensional building objects in a Danish geo-information infrastructure perspective

DEFF Research Database (Denmark)

Schrøder, Lise

2002-01-01

The emerging multidimensional GI- and VR-technologies within the professional disciplines dealing with design, planning and management processes is leading to a demand for four-dimensional building objects as part of the public geo-information infrastructure. The other way around the recognition...... of the building as a four-dimensional geo-phenomenon will provide a reference between different data sets whether representing buildings in two, three or four dimensions. Finally a central issue is the potential in using frameworks of multidimensional representations as interfaces to the available data sets...

Regular Network Class Features Enhancement Using an Evolutionary Synthesis Algorithm

Directory of Open Access Journals (Sweden)

O. G. Monahov

2014-01-01

Full Text Available This paper investigates a solution of the optimization problem concerning the construction of diameter-optimal regular networks (graphs. Regular networks are of practical interest as the graph-theoretical models of reliable communication networks of parallel supercomputer systems, as a basis of the structure in a model of small world in optical and neural networks. It presents a new class of parametrically described regular networks - hypercirculant networks (graphs. An approach that uses evolutionary algorithms for the automatic generation of parametric descriptions of optimal hypercirculant networks is developed. Synthesis of optimal hypercirculant networks is based on the optimal circulant networks with smaller degree of nodes. To construct optimal hypercirculant networks is used a template of circulant network from the known optimal families of circulant networks with desired number of nodes and with smaller degree of nodes. Thus, a generating set of the circulant network is used as a generating subset of the hypercirculant network, and the missing generators are synthesized by means of the evolutionary algorithm, which is carrying out minimization of diameter (average diameter of networks. A comparative analysis of the structural characteristics of hypercirculant, toroidal, and circulant networks is conducted. The advantage hypercirculant networks under such structural characteristics, as diameter, average diameter, and the width of bisection, with comparable costs of the number of nodes and the number of connections is demonstrated. It should be noted the advantage of hypercirculant networks of dimension three over four higher-dimensional tori. Thus, the optimization of hypercirculant networks of dimension three is more efficient than the introduction of an additional dimension for the corresponding toroidal structures. The paper also notes the best structural parameters of hypercirculant networks in comparison with iBT-networks previously

Multidimensional social support is associated with healthcare utilization among older Mexican adults.

Science.gov (United States)

Salinas-Rodríguez, Aarón; Moreno-Tamayo, Karla; Hernández-Serrato, María; Enríquez-Rosas, María Del Rocío; Manrique-Espinoza, Betty Soledad

2018-03-01

In this study, we aimed to estimate the association between social support and healthcare utilization among older Mexican adults. We conducted a prospective study with 4027 older adults aged 65-74 in rural areas in seven Mexican states. Data were collected at baseline (2007) and 14 months later (2009). Healthcare utilization was defined as number of visits to a physician for preventive or curative purposes in the last 6 months. Multidimensional social support was operationalized into two components: structural (living arrangements, marital status and network size) and functional (perceived availability of support; and perceived support across emotional, instrumental, economic and information domains). Mixed-effects regression models were used to estimate the probability of healthcare use and to examine the association between social support and the number of visits to a physician. Results showed that perceived availability of social support was associated with the probability of visits to a physician (OR 1.44; p  social support were associated with the probability of visits to a physician: instrumental (OR 1.55; p  social support, measured from a multidimensional viewpoint, and healthcare utilization, in which greater social support was related to a greater extent of use of health services.

Hierarchical regular small-world networks

International Nuclear Information System (INIS)

Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

2008-01-01

Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

Validation Study in the Educational Context of the Portuguese Version of the Multidimensional Work Motivation Scale

Directory of Open Access Journals (Sweden)

Lurdes Neves

2018-06-01

Full Text Available Abstrac The self-determination theory proposes a multidimensional concept of motivation and distinguishes how different types of motivation can be promoted or discouraged. For the application of the theory of self-determination to the educational context, this study aimed to adapt and validate the Multidimensional Work Motivation Scale (MWMS in the educational context. The scale was answered by 419 teachers from 30 schools from the North and Center of Portugal. Factor analysis indicated that the 19-item scale has the same factor structure as that obtained in the original study. In this study, it was possible to identify that the items that constitute the MWMS are good indicators of constructs to be measured in an educational context and the factors are properly individualized. The scale showed five robust dimensions that permit a broad understanding of motivation, similar to the studies of the original scale. The dimension with the best internal consistency is demotivation, while introjected regulation obtained the lowest coefficient.

Regularization Techniques for Linear Least-Squares Problems

KAUST Repository

Suliman, Mohamed

2016-04-01

Linear estimation is a fundamental branch of signal processing that deals with estimating the values of parameters from a corrupted measured data. Throughout the years, several optimization criteria have been used to achieve this task. The most astonishing attempt among theses is the linear least-squares. Although this criterion enjoyed a wide popularity in many areas due to its attractive properties, it appeared to suffer from some shortcomings. Alternative optimization criteria, as a result, have been proposed. These new criteria allowed, in one way or another, the incorporation of further prior information to the desired problem. Among theses alternative criteria is the regularized least-squares (RLS). In this thesis, we propose two new algorithms to find the regularization parameter for linear least-squares problems. In the constrained perturbation regularization algorithm (COPRA) for random matrices and COPRA for linear discrete ill-posed problems, an artificial perturbation matrix with a bounded norm is forced into the model matrix. This perturbation is introduced to enhance the singular value structure of the matrix. As a result, the new modified model is expected to provide a better stabilize substantial solution when used to estimate the original signal through minimizing the worst-case residual error function. Unlike many other regularization algorithms that go in search of minimizing the estimated data error, the two new proposed algorithms are developed mainly to select the artifcial perturbation bound and the regularization parameter in a way that approximately minimizes the mean-squared error (MSE) between the original signal and its estimate under various conditions. The first proposed COPRA method is developed mainly to estimate the regularization parameter when the measurement matrix is complex Gaussian, with centered unit variance (standard), and independent and identically distributed (i.i.d.) entries. Furthermore, the second proposed COPRA

75 FR 76006 - Regular Meeting

Science.gov (United States)

2010-12-07

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. ACTION: Regular meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the Board will be held...

Effects of Irregular Bridge Columns and Feasibility of Seismic Regularity

Science.gov (United States)

Thomas, Abey E.

2018-05-01

Bridges with unequal column height is one of the main irregularities in bridge design particularly while negotiating steep valleys, making the bridges vulnerable to seismic action. The desirable behaviour of bridge columns towards seismic loading is that, they should perform in a regular fashion, i.e. the capacity of each column should be utilized evenly. But, this type of behaviour is often missing when the column heights are unequal along the length of the bridge, allowing short columns to bear the maximum lateral load. In the present study, the effects of unequal column height on the global seismic performance of bridges are studied using pushover analysis. Codes such as CalTrans (Engineering service center, earthquake engineering branch, 2013) and EC-8 (EN 1998-2: design of structures for earthquake resistance. Part 2: bridges, European Committee for Standardization, Brussels, 2005) suggests seismic regularity criterion for achieving regular seismic performance level at all the bridge columns. The feasibility of adopting these seismic regularity criterions along with those mentioned in literatures will be assessed for bridges designed as per the Indian Standards in the present study.

Sparse regularization for force identification using dictionaries

Science.gov (United States)

Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng

2016-04-01

The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.

Nested element method in multidimensional neutron diffusion calculations

International Nuclear Information System (INIS)

Altiparmakov, D.V.

1983-01-01

A new numerical method is developed that is particularly efficient in solving the multidimensional neutron diffusion equation in geometrically complex systems. The needs for a generally applicable and fast running computer code have stimulated the inroad of a nonclassical (R-function) numerical method into the nuclear field. By using the R-functions, the geometrical components of the diffusion problem are a priori analytically implemented into the approximate solution. The class of functions, to which the approximate solution belongs, is chosen as close to the exact solution class as practically acceptable from the time consumption point of view. That implies a drastic reduction of the number of degrees of freedom, compared to the other methods. Furthermore, the reduced number of degrees of freedom enables calculation of large multidimensional problems on small computers

Optimal multi-dimensional poverty lines: The state of poverty in Iraq

Science.gov (United States)

Ameen, Jamal R. M.

2017-09-01

Poverty estimation based on calories intake is unrealistic. The established concept of multidimensional poverty has methodological weaknesses in the treatment of different dimensions and there is disagreement in methods of combining them into a single poverty line. This paper introduces a methodology to estimate optimal multidimensional poverty lines and uses the Iraqi household socio-economic survey data of 2012 to demonstrate the idea. The optimal poverty line for Iraq is found to be 170.5 Thousand Iraqi Dinars (TID).

Subcortical processing of speech regularities underlies reading and music aptitude in children

Science.gov (United States)

2011-01-01

Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input

Subcortical processing of speech regularities underlies reading and music aptitude in children.

Science.gov (United States)

Strait, Dana L; Hornickel, Jane; Kraus, Nina

2011-10-17

Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings

Subcortical processing of speech regularities underlies reading and music aptitude in children

Directory of Open Access Journals (Sweden)

Strait Dana L

2011-10-01

Full Text Available Abstract Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to

Multidimensional Screening as a Pharmacology Laboratory Experience.

Science.gov (United States)

Malone, Marvin H.; And Others

1979-01-01

A multidimensional pharmacodynamic screening experiment that addresses drug interaction is included in the pharmacology-toxicology laboratory experience of pharmacy students at the University of the Pacific. The student handout with directions for the procedure is reproduced, drug compounds tested are listed, and laboratory evaluation results are…

Salt-body Inversion with Minimum Gradient Support and Sobolev Space Norm Regularizations

KAUST Repository

Kazei, Vladimir

2017-05-26

Full-waveform inversion (FWI) is a technique which solves the ill-posed seismic inversion problem of fitting our model data to the measured ones from the field. FWI is capable of providing high-resolution estimates of the model, and of handling wave propagation of arbitrary complexity (visco-elastic, anisotropic); yet, it often fails to retrieve high-contrast geological structures, such as salt. One of the reasons for the FWI failure is that the updates at earlier iterations are too smooth to capture the sharp edges of the salt boundary. We compare several regularization approaches, which promote sharpness of the edges. Minimum gradient support (MGS) regularization focuses the inversion on blocky models, even more than the total variation (TV) does. However, both approaches try to invert undesirable high wavenumbers in the model too early for a model of complex structure. Therefore, we apply the Sobolev space norm as a regularizing term in order to maintain a balance between sharp and smooth updates in FWI. We demonstrate the application of these regularizations on a Marmousi model, enriched by a chunk of salt. The model turns out to be too complex in some parts to retrieve its full velocity distribution, yet the salt shape and contrast are retrieved.

A PCA-Based Change Detection Framework for Multidimensional Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2015-08-10

Detecting changes in multidimensional data streams is an important and challenging task. In unsupervised change detection, changes are usually detected by comparing the distribution in a current (test) window with a reference window. It is thus essential to design divergence metrics and density estimators for comparing the data distributions, which are mostly done for univariate data. Detecting changes in multidimensional data streams brings difficulties to the density estimation and comparisons. In this paper, we propose a framework for detecting changes in multidimensional data streams based on principal component analysis, which is used for projecting data into a lower dimensional space, thus facilitating density estimation and change-score calculations. The proposed framework also has advantages over existing approaches by reducing computational costs with an efficient density estimator, promoting the change-score calculation by introducing effective divergence metrics, and by minimizing the efforts required from users on the threshold parameter setting by using the Page-Hinkley test. The evaluation results on synthetic and real data show that our framework outperforms two baseline methods in terms of both detection accuracy and computational costs.

Cuba: Multidimensional numerical integration library

Science.gov (United States)

Hahn, Thomas

2016-08-01

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

Continuum-regularized quantum gravity

International Nuclear Information System (INIS)

Chan Huesum; Halpern, M.B.

1987-01-01

The recent continuum regularization of d-dimensional Euclidean gravity is generalized to arbitrary power-law measure and studied in some detail as a representative example of coordinate-invariant regularization. The weak-coupling expansion of the theory illustrates a generic geometrization of regularized Schwinger-Dyson rules, generalizing previous rules in flat space and flat superspace. The rules are applied in a non-trivial explicit check of Einstein invariance at one loop: the cosmological counterterm is computed and its contribution is included in a verification that the graviton mass is zero. (orig.)

Online co-regularized algorithms

NARCIS (Netherlands)

Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

2012-01-01

We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

Geometric continuum regularization of quantum field theory

International Nuclear Information System (INIS)

Halpern, M.B.

1989-01-01

An overview of the continuum regularization program is given. The program is traced from its roots in stochastic quantization, with emphasis on the examples of regularized gauge theory, the regularized general nonlinear sigma model and regularized quantum gravity. In its coordinate-invariant form, the regularization is seen as entirely geometric: only the supermetric on field deformations is regularized, and the prescription provides universal nonperturbative invariant continuum regularization across all quantum field theory. 54 refs

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

Science.gov (United States)

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Continued validation of the Multidimensional Perfectionism Scale.

Science.gov (United States)

Clavin, S L; Clavin, R H; Gayton, W F; Broida, J

1996-06-01

Scores on the Multidimensional Perfectionism Scale have been correlated with measures of obsessive-compulsive tendencies for women, so the validity of scores on this scale for 41 men was examined. Scores on the Perfectionism Scale were significantly correlated (.47-.03) with scores on the Maudsley Obsessive-Compulsive Inventory.

Multidimensional stochastic approximation using locally contractive functions

Science.gov (United States)

Lawton, W. M.

1975-01-01

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

3D first-arrival traveltime tomography with modified total variation regularization

Science.gov (United States)

Jiang, Wenbin; Zhang, Jie

2018-02-01

Three-dimensional (3D) seismic surveys have become a major tool in the exploration and exploitation of hydrocarbons. 3D seismic first-arrival traveltime tomography is a robust method for near-surface velocity estimation. A common approach for stabilizing the ill-posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a 3D first-arrival traveltime tomography method with modified total variation (MTV) regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L2 total variation problem. We apply the conjugate gradient method and split-Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization. We apply the technique to field data. The stacking section shows significant improvements with static corrections from the MTV traveltime tomography.

Imaging a multidimensional multichannel potential energy surface: Photodetachment of H(-)(NH3) and NH4 (.).

Science.gov (United States)

Hu, Qichi; Song, Hongwei; Johnson, Christopher J; Li, Jun; Guo, Hua; Continetti, Robert E

2016-06-28

Probes of the Born-Oppenheimer potential energy surfaces governing polyatomic molecules often rely on spectroscopy for the bound regions or collision experiments in the continuum. A combined spectroscopic and half-collision approach to image nuclear dynamics in a multidimensional and multichannel system is reported here. The Rydberg radical NH4 and the double Rydberg anion NH4 (-) represent a polyatomic system for benchmarking electronic structure and nine-dimensional quantum dynamics calculations. Photodetachment of the H(-)(NH3) ion-dipole complex and the NH4 (-) DRA probes different regions on the neutral NH4 PES. Photoelectron energy and angular distributions at photon energies of 1.17, 1.60, and 2.33 eV compare well with quantum dynamics. Photoelectron-photofragment coincidence experiments indicate dissociation of the nascent NH4 Rydberg radical occurs to H + NH3 with a peak kinetic energy of 0.13 eV, showing the ground state of NH4 to be unstable, decaying by tunneling-induced dissociation on a time scale beyond the present scope of multidimensional quantum dynamics.

SQoS based Planning using 4-regular Grid for Optical Fiber Metworks

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Pedersen, Jens Myrup; Madsen, Ole Brun

optical fiber based network infrastructures. In the first step of SQoS based planning, this paper describes how 4-regular Grid structures can be implemented in the physical level of optical fiber network infrastructures. A systematic approach for implementing the Grid structure is presented. We used...

SQoS based Planning using 4-regular Grid for Optical Fiber Networks

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Pedersen, Jens Myrup; Madsen, Ole Brun

2005-01-01

optical fiber based network infrastructures. In the first step of SQoS based planning, this paper describes how 4-regular Grid structures can be implemented in the physical level of optical fiber network infrastructures. A systematic approach for implementing the Grid structure is presented. We used...

Development of a multi-dimensional realistic thermal-hydraulic system analysis code, MARS 1.3 and its verification

Energy Technology Data Exchange (ETDEWEB)

Lee, Won Jae; Chung, Bub Dong; Jeong, Jae Jun; Ha, Kwi Seok [Korea Atomic Energy Research Institute, Taejon (Korea)

1998-06-01

A multi-dimensional realistic thermal-hydraulic system analysis code, MARS version 1.3 has been developed. Main purpose of MARS 1.3 development is to have the realistic analysis capability of transient two-phase thermal-hydraulics of Pressurized Water Reactors (PWRs) especially during Large Break Loss of Coolant Accidents (LBLOCAs) where the multi-dimensional phenomena domain the transients. MARS code is a unified version of USNRC developed COBRA-TF, domain the transients. MARS code is a unified version of USNRC developed COBRA-TF, three-dimensional (3D) reactor vessel analysis code, and RELAP5/MOD3.2.1.2, one-dimensional (1D) reactor system analysis code., Developmental requirements for MARS are chosen not only to best utilize the existing capability of the codes but also to have the enhanced capability in code maintenance, user accessibility, user friendliness, code portability, code readability, and code flexibility. For the maintenance of existing codes capability and the enhancement of code maintenance capability, user accessibility and user friendliness, MARS has been unified to be a single code consisting of 1D module (RELAP5) and 3D module (COBRA-TF). This is realized by implicitly integrating the system pressure matrix equations of hydrodynamic models and solving them simultaneously, by modifying the 1D/3D calculation sequence operable under a single Central Processor Unit (CPU) and by unifying the input structure and the light water property routines of both modules. In addition, the code structure of 1D module is completely restructured using the modular data structure of standard FORTRAN 90, which greatly improves the code maintenance capability, readability and portability. For the code flexibility, a dynamic memory management scheme is applied in both modules. MARS 1.3 now runs on PC/Windows and HP/UNIX platforms having a single CPU, and users have the options to select the 3D module to model the 3D thermal-hydraulics in the reactor vessel or other

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

Science.gov (United States)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

Science.gov (United States)

Save, H.; Bettadpur, S. V.

2013-12-01

It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yunji; Jing, Bing-Yi; Gao, Xin

2015-01-01

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan

2015-02-12

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Discrete nodal integral transport-theory method for multidimensional reactor physics and shielding calculations

International Nuclear Information System (INIS)

Lawrence, R.D.; Dorning, J.J.

1980-01-01

A coarse-mesh discrete nodal integral transport theory method has been developed for the efficient numerical solution of multidimensional transport problems of interest in reactor physics and shielding applications. The method, which is the discrete transport theory analogue and logical extension of the nodal Green's function method previously developed for multidimensional neutron diffusion problems, utilizes the same transverse integration procedure to reduce the multidimensional equations to coupled one-dimensional equations. This is followed by the conversion of the differential equations to local, one-dimensional, in-node integral equations by integrating back along neutron flight paths. One-dimensional and two-dimensional transport theory test problems have been systematically studied to verify the superior computational efficiency of the new method

The multidimensional nature of ageism: construct validity and group differences.

Science.gov (United States)

Rupp, Deborah E; Vodanovich, Stephen J; Credé, Marcus

2005-06-01

The authors investigated the factor structure and construct validity of the Fraboni Scale of Ageism and the age and gender differences in ageism scores. Confirmatory factor analyses supported the multidimensional nature of FSA scores and generally corroborated the initial factor structure reported by M. Fraboni, with some notable exceptions. Essentially, the present findings were aligned with theoretical models of ageism that emphasize both cognitive facets and affective facets. That is, on the basis of their factor analytic findings, the authors redefined Fraboni's original factors of Antilocution, Avoidance, and Discrimination as Stereotypes, Separation, and Affective Attitudes, respectively, because of the clustering of items within factors. The revised 3-factor structure accounted for 36.4% of the variance in FSA scores. FSA factor scores significantly related to other scores from other measures of age-related attitudes, with higher correlations among factors that were similar in terms of their cognitive nature versus their affective nature. Finally, younger individuals and men had significantly higher ageism scores on the FSA than older individuals and women. The authors discussed the importance of adequately assessing ageism, with particular emphasis devoted to the understanding of age bias.

Code Coupling for Multi-Dimensional Core Transient Analysis

International Nuclear Information System (INIS)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il

2015-01-01

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident

Code Coupling for Multi-Dimensional Core Transient Analysis

Energy Technology Data Exchange (ETDEWEB)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il [KEPCO NF, Daejeon (Korea, Republic of)

2015-05-15

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident.

Minimal length uncertainty relation and ultraviolet regularization

Science.gov (United States)

Kempf, Achim; Mangano, Gianpiero

1997-06-01

Studies in string theory and quantum gravity suggest the existence of a finite lower limit Δx0 to the possible resolution of distances, at the latest on the scale of the Planck length of 10-35 m. Within the framework of the Euclidean path integral we explicitly show ultraviolet regularization in field theory through this short distance structure. Both rotation and translation invariance can be preserved. An example is studied in detail.

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, Augustas; Pedersen, Torben Bach

2004-01-01

and requests of their users in multidimensional databases, i.e., data warehouses, and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, A.; Pedersen, Torben Bach

2003-01-01

and requests of their users in multidimensional databases, i.e., data warehouses; and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

Fast acquisition of multidimensional NMR spectra of solids and mesophases using alternative sampling methods.

Science.gov (United States)

Lesot, Philippe; Kazimierczuk, Krzysztof; Trébosc, Julien; Amoureux, Jean-Paul; Lafon, Olivier

2015-11-01

Unique information about the atom-level structure and dynamics of solids and mesophases can be obtained by the use of multidimensional nuclear magnetic resonance (NMR) experiments. Nevertheless, the acquisition of these experiments often requires long acquisition times. We review here alternative sampling methods, which have been proposed to circumvent this issue in the case of solids and mesophases. Compared to the spectra of solutions, those of solids and mesophases present some specificities because they usually display lower signal-to-noise ratios, non-Lorentzian line shapes, lower spectral resolutions and wider spectral widths. We highlight herein the advantages and limitations of these alternative sampling methods. A first route to accelerate the acquisition time of multidimensional NMR spectra consists in the use of sparse sampling schemes, such as truncated, radial or random sampling ones. These sparsely sampled datasets are generally processed by reconstruction methods differing from the Discrete Fourier Transform (DFT). A host of non-DFT methods have been applied for solids and mesophases, including the G-matrix Fourier transform, the linear least-square procedures, the covariance transform, the maximum entropy and the compressed sensing. A second class of alternative sampling consists in departing from the Jeener paradigm for multidimensional NMR experiments. These non-Jeener methods include Hadamard spectroscopy as well as spatial or orientational encoding of the evolution frequencies. The increasing number of high field NMR magnets and the development of techniques to enhance NMR sensitivity will contribute to widen the use of these alternative sampling methods for the study of solids and mesophases in the coming years. Copyright © 2015 John Wiley & Sons, Ltd.

The Synthesis Map Is a Multidimensional Educational Tool That Provides Insight into Students' Mental Models and Promotes Students' Synthetic Knowledge Generation

Science.gov (United States)

Ortega, Ryan A.; Brame, Cynthia J.

2015-01-01

Concept mapping was developed as a method of displaying and organizing hierarchical knowledge structures. Using the new, multidimensional presentation software Prezi, we have developed a new teaching technique designed to engage higher-level skills in the cognitive domain. This tool, synthesis mapping, is a natural evolution of concept mapping,…

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.

2016-01-01

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-11-29

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Structural and biochemical analysis of nuclease domain of clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 3 (Cas3).

Science.gov (United States)

Mulepati, Sabin; Bailey, Scott

2011-09-09

RNA transcribed from clustered regularly interspaced short palindromic repeats (CRISPRs) protects many prokaryotes from invasion by foreign DNA such as viruses, conjugative plasmids, and transposable elements. Cas3 (CRISPR-associated protein 3) is essential for this CRISPR protection and is thought to mediate cleavage of the foreign DNA through its N-terminal histidine-aspartate (HD) domain. We report here the 1.8 Å crystal structure of the HD domain of Cas3 from Thermus thermophilus HB8. Structural and biochemical studies predict that this enzyme binds two metal ions at its active site. We also demonstrate that the single-stranded DNA endonuclease activity of this T. thermophilus domain is activated not by magnesium but by transition metal ions such as manganese and nickel. Structure-guided mutagenesis confirms the importance of the metal-binding residues for the nuclease activity and identifies other active site residues. Overall, these results provide a framework for understanding the role of Cas3 in the CRISPR system.

ComVisMD - compact visualization of multidimensional data: experimenting with cricket players data

Science.gov (United States)

Dandin, Shridhar B.; Ducassé, Mireille

2018-03-01

Database information is multidimensional and often displayed in tabular format (row/column display). Presented in aggregated form, multidimensional data can be used to analyze the records or objects. Online Analytical database Processing (OLAP) proposes mechanisms to display multidimensional data in aggregated forms. A choropleth map is a thematic map in which areas are colored in proportion to the measurement of a statistical variable being displayed, such as population density. They are used mostly for compact graphical representation of geographical information. We propose a system, ComVisMD inspired by choropleth map and the OLAP cube to visualize multidimensional data in a compact way. ComVisMD displays multidimensional data like OLAP Cube, where we are mapping an attribute a (first dimension, e.g. year started playing cricket) in vertical direction, object coloring based on b (second dimension, e.g. batting average), mapping varying-size circles based on attribute c (third dimension, e.g. highest score), mapping numbers based on attribute d (fourth dimension, e.g. matches played). We illustrate our approach on cricket players data, namely on two tables Country and Player. They have a large number of rows and columns: 246 rows and 17 columns for players of one country. ComVisMD’s visualization reduces the size of the tabular display by a factor of about 4, allowing users to grasp more information at a time than the bare table display.

Testing the multidimensionality of the inventory of school motivation in a Dutch student sample.

Science.gov (United States)

Korpershoek, Hanke; Xu, Kun; Mok, Magdalena Mo Ching; McInerney, Dennis M; van der Werf, Greetje

2015-01-01

A factor analytic and a Rasch measurement approach were applied to evaluate the multidimensional nature of the school motivation construct among more than 7,000 Dutch secondary school students. The Inventory of School Motivation (McInerney and Ali, 2006) was used, which intends to measure four motivation dimensions (mastery, performance, social, and extrinsic motivation), each comprising of two first-order factors. One unidimensional model and three multidimensional models (4-factor, 8-factor, higher order) were fit to the data. Results of both approaches showed that the multidimensional models validly represented the school motivation among Dutch secondary school pupils, whereas model fit of the unidimensional model was poor. The differences in model fit between the three multidimensional models were small, although a different model was favoured by the two approaches. The need for improvement of some of the items and the need to increase measurement precision of several first-order factors are discussed.

Theory and application of deterministic multidimensional pointwise energy lattice physics methods

International Nuclear Information System (INIS)

Zerkle, M.L.

1999-01-01

The theory and application of deterministic, multidimensional, pointwise energy lattice physics methods are discussed. These methods may be used to solve the neutron transport equation in multidimensional geometries using near-continuous energy detail to calculate equivalent few-group diffusion theory constants that rigorously account for spatial and spectral self-shielding effects. A dual energy resolution slowing down algorithm is described which reduces the computer memory and disk storage requirements for the slowing down calculation. Results are presented for a 2D BWR pin cell depletion benchmark problem

Goodness-of-fit tests for multi-dimensional copulas: Expanding application to historical drought data

Directory of Open Access Journals (Sweden)

Ming-wei Ma

2013-01-01

Full Text Available The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.

On fully multidimensional and high order non oscillatory finite volume methods, I

International Nuclear Information System (INIS)

Lafon, F.

1992-11-01

A fully multidimensional flux formulation for solving nonlinear conservation laws of hyperbolic type is introduced to perform calculations on unstructured grids made of triangular or quadrangular cells. Fluxes are computed across dual median cells with a multidimensional 2D Riemann Solver (R2D Solver) whose intermediate states depend on either a three (on triangle R2DT solver) of four (on quadrangle, R2DQ solver) state solutions prescribed on the three or four sides of a gravity cell. Approximate Riemann solutions are computed via a linearization process of Roe's type involving multidimensional effects. Moreover, a monotonous scheme using stencil and central Lax-Friedrichs corrections on sonic curves are built in. Finally, high order accurate ENO-like (Essentially Non Oscillatory) reconstructions using plane and higher degree polynomial limitations are defined in the set up of finite element Lagrange spaces P k and Q k for k≥0, on triangles and quadrangles, respectively. Numerical experiments involving both linear and nonlinear conservation laws to be solved on unstructured grids indicate the ability of our techniques when dealing with strong multidimensional effects. An application to Euler's equations for the Mach three step problem illustrates the robustness and usefulness of our techniques using triangular and quadrangular grids. (Author). 33 refs., 13 figs

DaqProVis, a toolkit for acquisition, interactive analysis, processing and visualization of multidimensional data

Energy Technology Data Exchange (ETDEWEB)

Morhac, M. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)]. E-mail: fyzimiro@savba.sk; Matousek, V. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Turzo, I. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Kliman, J. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)

2006-04-01

Multidimensional data acquisition, processing and visualization system to analyze experimental data in nuclear physics is described. It includes a large number of sophisticated algorithms of the multidimensional spectra processing, including background elimination, deconvolution, peak searching and fitting.

Properties of regular polygons of coupled microring resonators.

Science.gov (United States)

Chremmos, Ioannis; Uzunoglu, Nikolaos

2007-11-01

The resonant properties of a closed and symmetric cyclic array of N coupled microring resonators (coupled-microring resonator regular N-gon) are for the first time determined analytically by applying the transfer matrix approach and Floquet theorem for periodic propagation in cylindrically symmetric structures. By solving the corresponding eigenvalue problem with the field amplitudes in the rings as eigenvectors, it is shown that, for even or odd N, this photonic molecule possesses 1 + N/2 or 1+N resonant frequencies, respectively. The condition for resonances is found to be identical to the familiar dispersion equation of the infinite coupled-microring resonator waveguide with a discrete wave vector. This result reveals the so far latent connection between the two optical structures and is based on the fact that, for a regular polygon, the field transfer matrix over two successive rings is independent of the polygon vertex angle. The properties of the resonant modes are discussed in detail using the illustration of Brillouin band diagrams. Finally, the practical application of a channel-dropping filter based on polygons with an even number of rings is also analyzed.

Multidimensional first-order dominance comparisons of population wellbeing

DEFF Research Database (Denmark)

Arndt, Thomas Channing; Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave

In this paper, we convey the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. We give an account of the fundamental equivalent definitions of FOD, illustrated with simple numerical examples. An implementable method...

Equating Multidimensional Tests under a Random Groups Design: A Comparison of Various Equating Procedures

Science.gov (United States)

Lee, Eunjung

2013-01-01

The purpose of this research was to compare the equating performance of various equating procedures for the multidimensional tests. To examine the various equating procedures, simulated data sets were used that were generated based on a multidimensional item response theory (MIRT) framework. Various equating procedures were examined, including…

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

OpenAIRE

S. V. Groshev; N. V. Pivovarova

2015-01-01

Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional ...

Zinc oxide modified with benzylphosphonic acids as transparent electrodes in regular and inverted organic solar cell structures

Energy Technology Data Exchange (ETDEWEB)

Lange, Ilja; Reiter, Sina; Kniepert, Juliane; Piersimoni, Fortunato; Brenner, Thomas; Neher, Dieter, E-mail: neher@uni-potsdam.de [Institute of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Strasse 24-25, 14476 Potsdam (Germany); Pätzel, Michael; Hildebrandt, Jana; Hecht, Stefan [Department of Chemistry and IRIS Adlershof, Humboldt-Universität zu Berlin, Brook-Taylor-Str. 2, 12489 Berlin (Germany)

2015-03-16

An approach is presented to modify the work function of solution-processed sol-gel derived zinc oxide (ZnO) over an exceptionally wide range of more than 2.3 eV. This approach relies on the formation of dense and homogeneous self-assembled monolayers based on phosphonic acids with different dipole moments. This allows us to apply ZnO as charge selective bottom electrodes in either regular or inverted solar cell structures, using poly(3-hexylthiophene):phenyl-C71-butyric acid methyl ester as the active layer. These devices compete with or even surpass the performance of the reference on indium tin oxide/poly(3,4-ethylenedioxythiophene) polystyrene sulfonate. Our findings highlight the potential of properly modified ZnO as electron or hole extracting electrodes in hybrid optoelectronic devices.

Multi-dimensional design window search system using neural networks in reactor core design

International Nuclear Information System (INIS)

Kugo, Teruhiko; Nakagawa, Masayuki

2000-02-01

In the reactor core design, many parametric survey calculations should be carried out to decide an optimal set of basic design parameter values. They consume a large amount of computation time and labor in the conventional way. To support directly design work, we investigate a procedure to search efficiently a design window, which is defined as feasible design parameter ranges satisfying design criteria and requirements, in a multi-dimensional space composed of several basic design parameters. We apply the present method to the neutronics and thermal hydraulics fields and develop the multi-dimensional design window search system using it. The principle of the present method is to construct the multilayer neural network to simulate quickly a response of an analysis code through a training process, and to reduce computation time using the neural network without parametric study using analysis codes. The system works on an engineering workstation (EWS) with efficient man-machine interface for pre- and post-processing. This report describes the principle of the present method, the structure of the system, the guidance of the usages of the system, the guideline for the efficient training of neural networks, the instructions of the input data for analysis calculation and so on. (author)

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

Science.gov (United States)

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regularities of Multifractal Measures

Indian Academy of Sciences (India)

First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in R R d . This decomposition theorem enables us to split a set into regular and irregular parts, so that we can analyze each separately, and recombine them without affecting density properties. Next, we ...

Ordinal Comparison of Multidimensional Deprivation

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter

This paper develops an ordinal method of comparison of multidimensional inequality. In our model, population distribution g is more unequal than f when the distributions have common median and can be obtained from f  by one or more shifts in population density that increase inequality. For our be...... benchmark 2x2 case (i.e. the case of two binary outcome variables), we derive an empirical method for making inequality comparisons. As an illustration, we apply the model to childhood poverty in Mozambique....

MODA: a new algorithm to compute optical depths in multidimensional hydrodynamic simulations

Science.gov (United States)

Perego, Albino; Gafton, Emanuel; Cabezón, Rubén; Rosswog, Stephan; Liebendörfer, Matthias

2014-08-01

Aims: We introduce the multidimensional optical depth algorithm (MODA) for the calculation of optical depths in approximate multidimensional radiative transport schemes, equally applicable to neutrinos and photons. Motivated by (but not limited to) neutrino transport in three-dimensional simulations of core-collapse supernovae and neutron star mergers, our method makes no assumptions about the geometry of the matter distribution, apart from expecting optically transparent boundaries. Methods: Based on local information about opacities, the algorithm figures out an escape route that tends to minimize the optical depth without assuming any predefined paths for radiation. Its adaptivity makes it suitable for a variety of astrophysical settings with complicated geometry (e.g., core-collapse supernovae, compact binary mergers, tidal disruptions, star formation, etc.). We implement the MODA algorithm into both a Eulerian hydrodynamics code with a fixed, uniform grid and into an SPH code where we use a tree structure that is otherwise used for searching neighbors and calculating gravity. Results: In a series of numerical experiments, we compare the MODA results with analytically known solutions. We also use snapshots from actual 3D simulations and compare the results of MODA with those obtained with other methods, such as the global and local ray-by-ray method. It turns out that MODA achieves excellent accuracy at a moderate computational cost. In appendix we also discuss implementation details and parallelization strategies.

Adaptive Regularization of Neural Classifiers

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Larsen, Jan; Hansen, Lars Kai

1997-01-01

We present a regularization scheme which iteratively adapts the regularization parameters by minimizing the validation error. It is suggested to use the adaptive regularization scheme in conjunction with optimal brain damage pruning to optimize the architecture and to avoid overfitting. Furthermo......, we propose an improved neural classification architecture eliminating an inherent redundancy in the widely used SoftMax classification network. Numerical results demonstrate the viability of the method...

Processes of Integration and Fragmentation of Economic Space: The Structure of Settlement Systems

Directory of Open Access Journals (Sweden)

Alexander Pavlovich Goryunov

2017-12-01

Full Text Available This work presents a study of processes of integration and fragmentation caused by the polarization of economic space. Under integration in economic space the authors understand the formation of new and transformation of existing settlement systems, while fragmentation is the dissolution of settlement systems and their transformation into loosely connected settlement networks. The study focuses on the structure of settlement systems. Authors propose a new method for studying the structure of settlement systems, which combines the use of factor analysis, multidimensional scaling, and cluster analysis. The proposed method utilizes the maximum of available information about the social-economic status of settlements to reveal regularities in their spatial organization. The authors test the proposed method on 35 large cities of the Central and Volga federal districts of Russia, which comprise the spatial surroundings of Moscow. The authors find four groups of cities forming the core of the settlement system centered around Moscow, a group of four cities forming a buffer zone around that system, as well as four cities in the studied sample which do not participate in the settlement system

Psychometric properties of the Multidimensional Anxiety Scale for ...

African Journals Online (AJOL)

Aim: To determine the psychometric properties of the Multidimensional Anxiety Scale for Children (MASC) in Nairobi public secondary school children, Kenya. Method: Concurrent self-administration of the MASC and Children's Depression Inventory (CDI) to students in Nairobi public secondary schools. Results: The MASC ...

Application of regularization technique in image super-resolution algorithm via sparse representation

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Huang, Hui; Zheng, Li-xin

2017-11-01

To make use of the prior knowledge of the image more effectively and restore more details of the edges and structures, a novel sparse coding objective function is proposed by applying the principle of the non-local similarity and manifold learning on the basis of super-resolution algorithm via sparse representation. Firstly, the non-local similarity regularization term is constructed by using the similar image patches to preserve the edge information. Then, the manifold learning regularization term is constructed by utilizing the locally linear embedding approach to enhance the structural information. The experimental results validate that the proposed algorithm has a significant improvement compared with several super-resolution algorithms in terms of the subjective visual effect and objective evaluation indices.

Multidimensional and Multimodal Separations by HPTLC in Phytochemistry

Science.gov (United States)

Ciesla, Lukasz; Waksmundzka-Hajnos, Monika

HPTLC is one of the most widely applied methods in phytochemical analysis. It is due to its numerous advantages, e.g., it is the only chromatographic method offering the option of presenting the results as an image. Other advantages include simplicity, low costs, parallel analysis of samples, high sample capacity, rapidly obtained results, and possibility of multiple detection. HPTLC provides identification as well as quantitative results. It also enables the identification of adulterants. In case of complex samples, the resolving power of traditional one-dimensional chromatography is usually inadequate, hence special modes of development are required. Multidimensional and multimodal HPTLC techniques include those realized in one direction (UMD, IMD, GMD, BMD, AMD) as well as typical two-dimensional methods realized on mono- or bi-layers. In this manuscript, an overview on variable multidimensional and multimodal methods, applied in the analysis of phytochemical samples, is presented.

A Multidimensional Data Warehouse for Community Health Centers.

Science.gov (United States)

Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N

2015-01-01

Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise.

Multidimensional biochemical information processing of dynamical patterns.

Science.gov (United States)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Progressive image denoising through hybrid graph Laplacian regularization: a unified framework.

Science.gov (United States)

Liu, Xianming; Zhai, Deming; Zhao, Debin; Zhai, Guangtao; Gao, Wen

2014-04-01

Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned, which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space. In this procedure, the intrinsic manifold structure is explicitly considered using both measured and unmeasured samples, and the nonlocal self-similarity property is utilized as a fruitful resource for abstracting a priori knowledge of the images. On the other hand, between two successive scales, the proposed model is extended to a projected high-dimensional feature space through explicit kernel mapping to describe the interscale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. In this way, the proposed algorithm gradually recovers more and more image details and edges, which could not been recovered in previous scale. We test our algorithm on one typical image recovery task: impulse noise removal. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art algorithms.

Condition Number Regularized Covariance Estimation.

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2013-06-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.

Research on Geometric Positioning Algorithm of License Plate in Multidimensional Parameter Space

Directory of Open Access Journals (Sweden)

Yinhua Huan

2014-05-01

Full Text Available Considering features of vehicle license plate location method which commonly used, in order to search a consistent location for reference images with license plates feature in multidimensional parameter space, a new algorithm of geometric location is proposed. Geometric location algorithm main include model training and real time search. Which not only adapt the gray-scale linearity and the gray non-linear changes, but also support changes of scale and angle. Compared with the mainstream locating software, numerical results shows under the same test conditions that the position deviation of geometric positioning algorithm is less than 0.5 pixel. Without taking into account the multidimensional parameter space, Geometric positioning algorithm position deviation is less than 1.0 pixel and angle deviation is less than 1.0 degree taking into account the multidimensional parameter space. This algorithm is robust, simple, practical and is better than the traditional method.

The reality of disability: Multidimensional poverty of people with disability and their families in Latin America.

Science.gov (United States)

Pinilla-Roncancio, Mónica

2017-12-30

Disability and poverty are interconnected and although this relationship has been recognised, there is a lack of empirical evidence to support any possible causal relationship in this topic, particularly in the context of Latin America (LA). This study tests the hypothesis "Disability increases the risk of multidimensional poverty of people living with disabilities and their families". Using national census data from Brazil, Chile, Colombia, Costa Rica and Mexico, the Global Multidimensional Poverty Index (Global MPI) was calculated with the aim of measuring and comparing the levels of multidimensional poverty of people living in households with and without disabled members in the five countries. We found that in the five countries people with disabilities and their families had higher incidence, intensity and levels of multidimensional poverty compared with people living in other households. Their levels of deprivation were also higher for all the indicators included in the Global MPI and the contribution of this group to the national MPI was higher than their share of the population, thus people with disabilities and their families are overrepresented in those living in multidimensional poverty. People with disabilities and their families are in worse conditions than poor households without disabled members and social policies should aim to reduce their high levels of multidimensional poverty and deprivation. Copyright © 2017 Elsevier Inc. All rights reserved.

An Overview of Multi-Dimensional Models of the Sacramento–San Joaquin Delta

Directory of Open Access Journals (Sweden)

Michael L. MacWilliams

2016-12-01

Full Text Available doi: https://doi.org/10.15447/sfews.2016v14iss4art2Over the past 15 years, the development and application of multi-dimensional hydrodynamic models in San Francisco Bay and the Sacramento–San Joaquin Delta has transformed our ability to analyze and understand the underlying physics of the system. Initial applications of three-dimensional models focused primarily on salt intrusion, and provided a valuable resource for investigating how sea level rise and levee failures in the Delta could influence water quality in the Delta under future conditions. However, multi-dimensional models have also provided significant insights into some of the fundamental biological relationships that have shaped our thinking about the system by exploring the relationship among X2, flow, fish abundance, and the low salinity zone. Through the coupling of multi-dimensional models with wind wave and sediment transport models, it has been possible to move beyond salinity to understand how large-scale changes to the system are likely to affect sediment dynamics, and to assess the potential effects on species that rely on turbidity for habitat. Lastly, the coupling of multi-dimensional hydrodynamic models with particle tracking models has led to advances in our thinking about residence time, the retention of food organisms in the estuary, the effect of south Delta exports on larval entrainment, and the pathways and behaviors of salmonids that travel through the Delta. This paper provides an overview of these recent advances and how they have increased our understanding of the distribution and movement of fish and food organisms. The applications presented serve as a guide to the current state of the science of Delta modeling and provide examples of how we can use multi-dimensional models to predict how future Delta conditions will affect both fish and water supply.

ANALYSIS OF MULTIDIMENSIONAL MEDICAL DATA USING PICTOGRAPHICS «CHERNOFF FACES»

Directory of Open Access Journals (Sweden)

I. A. Osadchaya

2014-01-01

Full Text Available The use of graphics in research works not only increases the speed of information transmission and increases the level of its understanding, but also contributes to the development of such important for professionals in any industry qualities of intuition and creative thinking. Methods of cognitive graphics significantly extend the capabilities of specialists any field of knowledge to identify the most informative parameters when processing the extensive data base and solving specific problems; detect sometimes radically new facts, radically changing their views known. A separate direction of cognitive graphics forms in medicine. Visualization of the current state of the object and the characteristic features provide continuous control over the condition of groups of persons or individual.This work focuses on the identification of psychological and physiological characteristics of patients with various forms of bronchial asthma using the methods of visualization of multidimensional data.Thus, the object of study are the physiological data of patients with bronchial asthma. Subject of research are the methods of cognitive graphics, namely, the methods of information presentation in the form of graphic images.The aim of this work is to study the possibilities of applying the methods of cognitive graphics in the study of the physiological characteristics of patients with various forms of bronchial asthma. In the end, work has revealed a number of regularities for various forms of bronchial asthma using the methods of data visualization.

Development of realistic thermal-hydraulic system analysis codes ; development of thermal hydraulic test requirements for multidimensional flow modeling

Energy Technology Data Exchange (ETDEWEB)

Suh, Kune Yull; Yoon, Sang Hyuk; Noh, Sang Woo; Lee, Il Suk [Seoul National University, Seoul (Korea)

2002-03-01

This study is concerned with developing a multidimensional flow model required for the system analysis code MARS to more mechanistically simulate a variety of thermal hydraulic phenomena in the nuclear stem supply system. The capability of the MARS code as a thermal hydraulic analysis tool for optimized system design can be expanded by improving the current calculational methods and adding new models. In this study the relevant literature was surveyed on the multidimensional flow models that may potentially be applied to the multidimensional analysis code. Research items were critically reviewed and suggested to better predict the multidimensional thermal hydraulic behavior and to identify test requirements. A small-scale preliminary test was performed in the downcomer formed by two vertical plates to analyze multidimensional flow pattern in a simple geometry. The experimental result may be applied to the code for analysis of the fluid impingement to the reactor downcomer wall. Also, data were collected to find out the controlling parameters for the one-dimensional and multidimensional flow behavior. 22 refs., 40 figs., 7 tabs. (Author)

Transforming community services through the use of a multidimensional model of clinical leadership.

Science.gov (United States)

Leigh, Jacqueline Anne; Wild, Jill; Hynes, Celia; Wells, Stuart; Kurien, Anish; Rutherford, June; Rosen, Lyn; Ashcroft, Tim; Hartley, Victoria

2015-03-01

To evaluate the application of a Multidimensional Model of Clinical Leadership on the community healthcare leader and on transforming community services. Healthcare policy advocates clinical leadership as the vehicle to transform community and healthcare services. Few studies have identified the key components of an effective clinical leadership development model. The first two stages of Kirkpatrick's (Personnel Administrator 28, 1983, 62) Four/Five Levels of Evaluation were used to evaluate the application of the multidimensional model of clinical leadership. Eighty community healthcare leaders were exposed to this multidimensional clinical leadership development model through attendance of a community clinical leadership development programme. Twenty five leaders participated in focus group interviews. Data from the interviews were analysed utilising thematic content analysis. Three key themes emerged that influenced the development of best practice principles for clinical leadership development: 1. Personal leadership development 2. Organisational leadership 3. The importance of multiprofessional action learning/reflective groups Emergent best practice principles for clinical leadership development include adopting a multidimensional development approach. This approach encompasses: preparing the individual leader in the role and seeking organisational leadership development that promotes the vision and corporate values of the organisation and delivers on service improvement and innovation. Moreover, application of the Multidimensional Model of Clinical Leadership could offer the best platform for embedding the Six C's of Nursing (Compassion in Practice - Our Culture of Compassionate Care, Department of Health, Crown Copyright, 2012) within the culture of the healthcare organisation: care, compassion, courage, commitment, communication, and competency. This is achieved in part through the application of emotional intelligence to understand self and to develop the

A sub-structure method for multidimensional integral transport calculations

International Nuclear Information System (INIS)

Kavenoky, A.; Stankovski, Z.

1983-03-01

A new method has been developed for fine structure burn-up calculations of very heterogeneous large size media. It is a generalization of the well-known surface-source method, allowing coupling actual two-dimensional heterogeneous assemblies, called sub-structures. The method has been applied to a rectangular medium, divided into sub-structures, containing rectangular and/or cylindrical fuel, moderator and structure elements. The sub-structures are divided into homogeneous zones. A zone-wise flux expansion is used to formulate a direct collision probability problem within it (linear or flat flux expansion in the rectangular zones, flat flux in the others). The coupling of the sub-structures is performed by making extra assumptions on the currents entering and leaving the interfaces. The accuracies and computing times achieved are illustrated by numerical results on two benchmark problems

Development of subchannel void measurement sensor and multidimensional two-phase flow dynamics in rod bundle

International Nuclear Information System (INIS)

Arai, T.; Furuya, M.; Kanai, T.; Shirakawa, K.

2011-01-01

An accurate subchannel database is crucial for modeling the multidimensional two-phase flow in a rod bundle and for validating subchannel analysis codes. Based on available reference, it can be said that a point-measurement sensor for acquiring void fractions and bubble velocity distributions do not infer interactions of the subchannel flow dynamics, such as a cross flow and flow distribution, etc. In order to acquire multidimensional two-phase flow in a 10×10 rod bundle with an o.d. of 10 mm and 3110 mm length, a new sensor consisting of 11-wire by 11-wire and 10-rod by 10-rod electrodes was developed. Electric potential in the proximity region between two wires creates a void fraction in the center subchannel region, like a so-called wire mesh sensor. A unique aspect of the devised sensor is that the void fraction near the rod surface can be estimated from the electric potential in the proximity region between one wire and one rod. The additional 400 points of void fraction and phasic velocity in 10×10 bundle can therefore be acquired. The devised sensor exhibits the quasi three-dimensional flow structures, i.e. void fraction, phasic velocity and bubble chord length distributions. These quasi three-dimensional structures exhibit the complexity of two-phase flow dynamics, such as coalescence and the breakup of bubbles in transient phasic velocity distributions. (author)

Validation of a multidimensional evaluation scale for use in elderly cancer patients.

Science.gov (United States)

Monfardini, S; Ferrucci, L; Fratino, L; del Lungo, I; Serraino, D; Zagonel, V

1996-01-15

Although aging is one of the most important risk factors for cancer, elderly patients tend to be excluded from cancer clinical trials, only on the basis of chronologic age. Performance Status (PS) has been used widely to select adult patients for entry into clinical trials, but it does not include a comprehensive evaluation of various age-related factors in the elderly. This study was designed to assess the reliability and validity of a multidimensional geriatric assessment protocol for elderly patients with cancer. Thirty consecutive elderly patients (> or = 65 years), diagnosed with hematologic neoplasia or solid tumors and undergoing chemotherapy or radiotherapy, were given a specifically structured multidimensional questionnaire (MACE) three times during one week by two different physicians. MACE was intended to collect information on demographics, socioeconomic status, cognitive status, depression, physical performance, disability, and tumor characteristics. In parallel with MACE, information was collected by means of the Sickness Impact Profile (SIP). Both for inter-rater and test-retest reliability, the values of the intraclass correlation coefficient (ICC) were generally higher than 0.7. Disability, cognitive status, depressive symptoms, and the number of days spent in bed sick in the last two weeks were markedly correlated with the global, physical, and social SIP score. Disability alone explained 70% of the variance in the SIP global score, 83% of the variance in the SIP physical score, and 45% of the variance in the SIP psychosocial score. MACE proved to be applicable in a reasonable amount of time (around 30 minutes) for a medical oncology ward. These data indicate that this structured evaluation of functional status is feasible and reliable. MACE is therefore proposed as a clinical research tool to avoid arbitrary decisions on patient selection for enrollment in clinical trials, to favor uniform monitoring of treatment, and to allow a better comparison

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

Science.gov (United States)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Assessment of wall friction model in multi-dimensional component of MARS with air–water cross flow experiment

Energy Technology Data Exchange (ETDEWEB)

Yang, Jin-Hwa [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Choi, Chi-Jin [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Cho, Hyoung-Kyu, E-mail: chohk@snu.ac.kr [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Euh, Dong-Jin [Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Park, Goon-Cherl [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

2017-02-15

Recently, high precision and high accuracy analysis on multi-dimensional thermal hydraulic phenomena in a nuclear power plant has been considered as state-of-the-art issues. System analysis code, MARS, also adopted a multi-dimensional module to simulate them more accurately. Even though it was applied to represent the multi-dimensional phenomena, but implemented models and correlations in that are one-dimensional empirical ones based on one-dimensional pipe experimental results. Prior to the application of the multi-dimensional simulation tools, however, the constitutive models for a two-phase flow need to be carefully validated, such as the wall friction model. Especially, in a Direct Vessel Injection (DVI) system, the injected emergency core coolant (ECC) on the upper part of the downcomer interacts with the lateral steam flow during the reflood phase in the Large-Break Loss-Of-Coolant-Accident (LBLOCA). The interaction between the falling film and lateral steam flow induces a multi-dimensional two-phase flow. The prediction of ECC flow behavior plays a key role in determining the amount of coolant that can be used as core cooling. Therefore, the wall friction model which is implemented to simulate the multi-dimensional phenomena should be assessed by multidimensional experimental results. In this paper, the air–water cross film flow experiments simulating the multi-dimensional phenomenon in upper part of downcomer as a conceptual problem will be introduced. The two-dimensional local liquid film velocity and thickness data were used as benchmark data for code assessment. And then the previous wall friction model of the MARS-MultiD in the annular flow regime was modified. As a result, the modified MARS-MultiD produced improved calculation result than previous one.

Multi-dimensional Code Development for Safety Analysis of LMR

International Nuclear Information System (INIS)

Ha, K. S.; Jeong, H. Y.; Kwon, Y. M.; Lee, Y. B.

2006-08-01

A liquid metal reactor loaded a metallic fuel has the inherent safety mechanism due to the several negative reactivity feedback. Although this feature demonstrated through experiments in the EBR-II, any of the computer programs until now did not exactly analyze it because of the complexity of the reactivity feedback mechanism. A multi-dimensional detail program was developed through the International Nuclear Energy Research Initiative(INERI) from 2003 to 2005. This report includes the numerical coupling the multi-dimensional program and SSC-K code which is used to the safety analysis of liquid metal reactors in KAERI. The coupled code has been proved by comparing the analysis results using the code with the results using SAS-SASSYS code of ANL for the UTOP, ULOF, and ULOHS applied to the safety analysis for KALIMER-150

Multidimensional gray-wavelet processing in interferometric fiber-optic gyroscopes

International Nuclear Information System (INIS)

Yang, Yi; Wang, Zinan; Peng, Chao; Li, Zhengbin

2013-01-01

A multidimensional signal processing method for a single interferometric fiber-optic gyroscope (IFOG) is proposed, to the best of our knowledge, for the first time. The proposed method, based on a novel IFOG structure with quadrature demodulation, combines a multidimensional gray model (GM) and a wavelet compression technique for noise suppression and sensitivity enhancement. In the IFOG, two series of measured rotation rates are obtained simultaneously: an in-phase component and a quadrature component. Together with the traditionally measured rate, the three measured rates are processed by the combined gray-wavelet method. Simulations show that the intensity noise and non-reciprocal phase fluctuations are effectively suppressed by this method. Experimental comparisons with a one-dimensional GM(1, 1) model show that the proposed three-dimensional method achieves much better denoising performance. This advantage is validated by the Allan variance analysis: in a low-SNR (signal-to-noise ratio) experiment, our method reduces the angle random walk (ARW) and the bias instability (BI) from 1 × 10 −2  deg h −1/2 and 3 × 10 −2  deg h −1 to 1 × 10 −3  deg h −1/2 and 3 × 10 −3  deg h −1 , respectively; in a high-SNR experiment, our method reduces the ARW and the BI from 9 × 10 −4  deg h −1/2 and 5 × 10 −3  deg h −1 to 4 × 10 −4  deg h −1/2 and 3 × 10 −3  deg h −1 , respectively. Further, our method increases the dimension of the state-of-the-art IFOG technique from one to three, thus obtaining higher IFOG sensitivity and stability by exploiting the increase in available information. (paper)

Multidimensional gray-wavelet processing in interferometric fiber-optic gyroscopes

Science.gov (United States)

Yang, Yi; Wang, Zinan; Peng, Chao; Li, Zhengbin

2013-11-01

A multidimensional signal processing method for a single interferometric fiber-optic gyroscope (IFOG) is proposed, to the best of our knowledge, for the first time. The proposed method, based on a novel IFOG structure with quadrature demodulation, combines a multidimensional gray model (GM) and a wavelet compression technique for noise suppression and sensitivity enhancement. In the IFOG, two series of measured rotation rates are obtained simultaneously: an in-phase component and a quadrature component. Together with the traditionally measured rate, the three measured rates are processed by the combined gray-wavelet method. Simulations show that the intensity noise and non-reciprocal phase fluctuations are effectively suppressed by this method. Experimental comparisons with a one-dimensional GM(1, 1) model show that the proposed three-dimensional method achieves much better denoising performance. This advantage is validated by the Allan variance analysis: in a low-SNR (signal-to-noise ratio) experiment, our method reduces the angle random walk (ARW) and the bias instability (BI) from 1 × 10-2 deg h-1/2 and 3 × 10-2 deg h-1 to 1 × 10-3 deg h-1/2 and 3 × 10-3 deg h-1, respectively; in a high-SNR experiment, our method reduces the ARW and the BI from 9 × 10-4 deg h-1/2 and 5 × 10-3 deg h-1 to 4 × 10-4 deg h-1/2 and 3 × 10-3 deg h-1, respectively. Further, our method increases the dimension of the state-of-the-art IFOG technique from one to three, thus obtaining higher IFOG sensitivity and stability by exploiting the increase in available information.

Condition Number Regularized Covariance Estimation*

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2012-01-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197

Dynamics of coherent states in regular and chaotic regimes of the non-integrable Dicke model

Science.gov (United States)

Lerma-Hernández, S.; Chávez-Carlos, J.; Bastarrachea-Magnani, M. A.; López-del-Carpio, B.; Hirsch, J. G.

2018-04-01

The quantum dynamics of initial coherent states is studied in the Dicke model and correlated with the dynamics, regular or chaotic, of their classical limit. Analytical expressions for the survival probability, i.e. the probability of finding the system in its initial state at time t, are provided in the regular regions of the model. The results for regular regimes are compared with those of the chaotic ones. It is found that initial coherent states in regular regions have a much longer equilibration time than those located in chaotic regions. The properties of the distributions for the initial coherent states in the Hamiltonian eigenbasis are also studied. It is found that for regular states the components with no negligible contribution are organized in sequences of energy levels distributed according to Gaussian functions. In the case of chaotic coherent states, the energy components do not have a simple structure and the number of participating energy levels is larger than in the regular cases.

The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

KAUST Repository

Schillinger, Dominik

2013-07-01

The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.

Nonparametric Bayesian inference for multidimensional compound Poisson processes

NARCIS (Netherlands)

Gugushvili, S.; van der Meulen, F.; Spreij, P.

2015-01-01

Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,

Loglinear multidimensional IRT models for polytomously scired Items

NARCIS (Netherlands)

Kelderman, Henk

1988-01-01

A loglinear item response theory (IRT) model is proposed that relates polytomously scored item responses to a multidimensional latent space. Each item may have a different response function where each item response may be explained by one or more latent traits. Item response functions may follow a

Loglinear multidimensional IRT models for polytomously scored items

NARCIS (Netherlands)

Kelderman, Henk; Rijkes, Carl P.M.; Rijkes, Carl

1994-01-01

A loglinear IRT model is proposed that relates polytomously scored item responses to a multidimensional latent space. The analyst may specify a response function for each response, indicating which latent abilities are necessary to arrive at that response. Each item may have a different number of

Efficient algorithms of multidimensional γ-ray spectra compression

International Nuclear Information System (INIS)

Morhac, M.; Matousek, V.

2006-01-01

The efficient algorithms to compress multidimensional γ-ray events are presented. Two alternative kinds of compression algorithms based on both the adaptive orthogonal and randomizing transforms are proposed. In both algorithms we employ the reduction of data volume due to the symmetry of the γ-ray spectra

An individual-centered approach to multidimensional poverty: The cases of Chile, Colombia, Ecuador and Peru

NARCIS (Netherlands)

Franco-Correa, A.

2014-01-01

This paper deals with the problem of selecting the unit of analysis in multidimensional poverty analyses, which is a central decision to take, both from academic and normative points of view. The paper compares the results of an individual-level Multidimensional Poverty Index for Chile, Colombia,

Low-diffusion rotated upwind schemes, multigrid and defect correction for steady, multi-dimensional Euler flows

NARCIS (Netherlands)

Koren, B.; Hackbusch, W.; Trottenberg, U.

1991-01-01

Two simple, multi-dimensional upwind discretizations for the steady Euler equations are derived, with the emphasis Iying on bath a good accuracy and a good solvability. The multi-dimensional upwinding consists of applying a one-dimensional Riemann solver with a locally rotated left and right state,

Multidimensional simulations of core-collapse supernovae with CHIMERA

Science.gov (United States)

Lentz, Eric J.; Bruenn, S. W.; Yakunin, K.; Endeve, E.; Blondin, J. M.; Harris, J. A.; Hix, W. R.; Marronetti, P.; Messer, O. B.; Mezzacappa, A.

2014-01-01

Core-collapse supernovae are driven by a multidimensional neutrino radiation hydrodynamic (RHD) engine, and full simulation requires at least axisymmetric (2D) and ultimately symmetry-free 3D RHD simulation. We present recent and ongoing work with our multidimensional RHD supernova code CHIMERA to understand the nature of the core-collapse explosion mechanism and its consequences. Recently completed simulations of 12-25 solar mass progenitors(Woosley & Heger 2007) in well resolved (0.7 degrees in latitude) 2D simulations exhibit robust explosions meeting the observationally expected explosion energy. We examine the role of hydrodynamic instabilities (standing accretion shock instability, neutrino driven convection, etc.) on the explosion dynamics and the development of the explosion energy. Ongoing 3D and 2D simulations examine the role that simulation resolution and the removal of the imposed axisymmetry have in the triggering and development of an explosion from stellar core collapse. Companion posters will explore the gravitational wave signals (Yakunin et al.) and nucleosynthesis (Harris et al.) of our simulations.

The West Haven-Yale Multidimensional Pain Inventory (WHYMPI).

Science.gov (United States)

Kerns, R D; Turk, D C; Rudy, T E

1985-12-01

The complexity of chronic pain has represented a major dilemma for clinical researchers interested in the reliable and valid assessment of the problem and the evaluation of treatment approaches. The West Haven-Yale Multidimensional Pain Inventory (WHYMPI) was developed in order to fill a widely recognized void in the assessment of clinical pain. Assets of the inventory are its brevity and clarity, its foundation in contemporary psychological theory, its multidimensional focus, and its strong psychometric properties. Three parts of the inventory, comprised of 12 scales, examine the impact of pain on the patients' lives, the responses of others to the patients' communications of pain, and the extent to which patients participate in common daily activities. The instrument is recommended for use in conjunction with behavioral and psychophysiological assessment strategies in the evaluation of chronic pain patients in clinical settings. The utility of the WHYMPI in empirical investigations of chronic pain is also discussed.

Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing.

Science.gov (United States)

Elmoataz, Abderrahim; Lezoray, Olivier; Bougleux, Sébastien

2008-07-01

We introduce a nonlocal discrete regularization framework on weighted graphs of the arbitrary topologies for image and manifold processing. The approach considers the problem as a variational one, which consists of minimizing a weighted sum of two energy terms: a regularization one that uses a discrete weighted p-Dirichlet energy and an approximation one. This is the discrete analogue of recent continuous Euclidean nonlocal regularization functionals. The proposed formulation leads to a family of simple and fast nonlinear processing methods based on the weighted p-Laplace operator, parameterized by the degree p of regularity, the graph structure and the graph weight function. These discrete processing methods provide a graph-based version of recently proposed semi-local or nonlocal processing methods used in image and mesh processing, such as the bilateral filter, the TV digital filter or the nonlocal means filter. It works with equal ease on regular 2-D and 3-D images, manifolds or any data. We illustrate the abilities of the approach by applying it to various types of images, meshes, manifolds, and data represented as graphs.

Multidimensional scaling technique for analysis of magnetic storms ...

Indian Academy of Sciences (India)

R.Narasimhan(krishtel emaging) 1461 1996 Oct 15 13:05:22

Multidimensional Scaling (MDS) comprises a set of models and associated methods for construct- ing a geometrical representation of proximity and dominance relationship between elements in one or more sets of entities. MDS can be applied to data that express two types of relationships: proxim- ity relations and ...

Integral and Multidimensional Linear Distinguishers with Correlation Zero

DEFF Research Database (Denmark)

Bogdanov, Andrey; Leander, Gregor; Nyberg, Kaisa

2012-01-01

Zero-correlation cryptanalysis uses linear approximations holding with probability exactly 1/2. In this paper, we reveal fundamental links of zero-correlation distinguishers to integral distinguishers and multidimensional linear distinguishers. We show that an integral implies zero-correlation li...... weak key assumptions. © International Association for Cryptologic Research 2012....

Regular-, irregular-, and pseudo-character processing in Chinese: The regularity effect in normal adult readers

Directory of Open Access Journals (Sweden)

Dustin Kai Yan Lau

2014-03-01

Full Text Available Background Unlike alphabetic languages, Chinese uses a logographic script. However, the pronunciation of many character’s phonetic radical has the same pronunciation as the character as a whole. These are considered regular characters and can be read through a lexical non-semantic route (Weekes & Chen, 1999. Pseudocharacters are another way to study this non-semantic route. A pseudocharacter is the combination of existing semantic and phonetic radicals in their legal positions resulting in a non-existing character (Ho, Chan, Chung, Lee, & Tsang, 2007. Pseudocharacters can be pronounced by direct derivation from the sound of its phonetic radical. Conversely, if the pronunciation of a character does not follow that of the phonetic radical, it is considered as irregular and can only be correctly read through the lexical-semantic route. The aim of the current investigation was to examine reading aloud in normal adults. We hypothesized that the regularity effect, previously described for alphabetical scripts and acquired dyslexic patients of Chinese (Weekes & Chen, 1999; Wu, Liu, Sun, Chromik, & Zhang, 2014, would also be present in normal adult Chinese readers. Method Participants. Thirty (50% female native Hong Kong Cantonese speakers with a mean age of 19.6 years and a mean education of 12.9 years. Stimuli. Sixty regular-, 60 irregular-, and 60 pseudo-characters (with at least 75% of name agreement in Chinese were matched by initial phoneme, number of strokes and family size. Additionally, regular- and irregular-characters were matched by frequency (low and consistency. Procedure. Each participant was asked to read aloud the stimuli presented on a laptop using the DMDX software. The order of stimuli presentation was randomized. Data analysis. ANOVAs were carried out by participants and items with RTs and errors as dependent variables and type of stimuli (regular-, irregular- and pseudo-character as repeated measures (F1 or between subject�

Bayesian Dimensionality Assessment for the Multidimensional Nominal Response Model

Directory of Open Access Journals (Sweden)

Javier Revuelta

2017-06-01

Full Text Available This article introduces Bayesian estimation and evaluation procedures for the multidimensional nominal response model. The utility of this model is to perform a nominal factor analysis of items that consist of a finite number of unordered response categories. The key aspect of the model, in comparison with traditional factorial model, is that there is a slope for each response category on the latent dimensions, instead of having slopes associated to the items. The extended parameterization of the multidimensional nominal response model requires large samples for estimation. When sample size is of a moderate or small size, some of these parameters may be weakly empirically identifiable and the estimation algorithm may run into difficulties. We propose a Bayesian MCMC inferential algorithm to estimate the parameters and the number of dimensions underlying the multidimensional nominal response model. Two Bayesian approaches to model evaluation were compared: discrepancy statistics (DIC, WAICC, and LOO that provide an indication of the relative merit of different models, and the standardized generalized discrepancy measure that requires resampling data and is computationally more involved. A simulation study was conducted to compare these two approaches, and the results show that the standardized generalized discrepancy measure can be used to reliably estimate the dimensionality of the model whereas the discrepancy statistics are questionable. The paper also includes an example with real data in the context of learning styles, in which the model is used to conduct an exploratory factor analysis of nominal data.

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity

DEFF Research Database (Denmark)

Naeem, S.; Prager, Case; Weeks, Brian

2016-01-01

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity...... on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional...

Racial-ethnic self-schemas: Multi-dimensional identity-based motivation

Science.gov (United States)

Oyserman, Daphna

2008-01-01

Prior self-schema research focuses on benefits of being schematic vs. aschematic in stereotyped domains. The current studies build on this work, examining racial-ethnic self-schemas as multi-dimensional, containing multiple, conflicting, and non-integrated images. A multidimensional perspective captures complexity; examining net effects of dimensions predicts within-group differences in academic engagement and well-being. When racial-ethnicity self-schemas focus attention on membership in both in-group and broader society, engagement with school should increase since school is not seen as out-group defining. When racial-ethnicity self-schemas focus attention on inclusion (not obstacles to inclusion) in broader society, risk of depressive symptoms should decrease. Support for these hypotheses was found in two separate samples (8th graders, n = 213, 9th graders followed to 12th grade n = 141). PMID:19122837

An empirical study of multidimensional fidelity of COMPASS consultation.

Science.gov (United States)

Wong, Venus; Ruble, Lisa A; McGrew, John H; Yu, Yue

2018-06-01

Consultation is essential to the daily practice of school psychologists (National Association of School Psychologist, 2010). Successful consultation requires fidelity at both the consultant (implementation) and consultee (intervention) levels. We applied a multidimensional, multilevel conception of fidelity (Dunst, Trivette, & Raab, 2013) to a consultative intervention called the Collaborative Model for Promoting Competence and Success (COMPASS) for students with autism. The study provided 3 main findings. First, multidimensional, multilevel fidelity is a stable construct and increases over time with consultation support. Second, mediation analyses revealed that implementation-level fidelity components had distant, indirect effects on student Individualized Education Program (IEP) outcomes. Third, 3 fidelity components correlated with IEP outcomes: teacher coaching responsiveness at the implementation level, and teacher quality of delivery and student responsiveness at the intervention levels. Implications and future directions are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Reduction of Nambu-Poisson Manifolds by Regular Distributions

Science.gov (United States)

Das, Apurba

2018-03-01

The version of Marsden-Ratiu reduction theorem for Nambu-Poisson manifolds by a regular distribution has been studied by Ibáñez et al. In this paper we show that the reduction is always ensured unless the distribution is zero. Next we extend the more general Falceto-Zambon Poisson reduction theorem for Nambu-Poisson manifolds. Finally, we define gauge transformations of Nambu-Poisson structures and show that these transformations commute with the reduction procedure.

Regularity effect in prospective memory during aging

Directory of Open Access Journals (Sweden)

Geoffrey Blondelle

2016-10-01

Full Text Available Background: Regularity effect can affect performance in prospective memory (PM, but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults. Objective and design: Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30, 16 intermediate adults (40–55, and 25 older adults (65–80. The task, adapted from the Virtual Week, was designed to manipulate the regularity of the various activities of daily life that were to be recalled (regular repeated activities vs. irregular non-repeated activities. We examine the role of several cognitive functions including certain dimensions of executive functions (planning, inhibition, shifting, and binding, short-term memory, and retrospective episodic memory to identify those involved in PM, according to regularity and age. Results: A mixed-design ANOVA showed a main effect of task regularity and an interaction between age and regularity: an age-related difference in PM performances was found for irregular activities (older < young, but not for regular activities. All participants recalled more regular activities than irregular ones with no age effect. It appeared that recalling of regular activities only involved planning for both intermediate and older adults, while recalling of irregular ones were linked to planning, inhibition, short-term memory, binding, and retrospective episodic memory. Conclusion: Taken together, our data suggest that planning capacities seem to play a major role in remembering to perform intended actions with advancing age. Furthermore, the age-PM-paradox may be attenuated when the experimental design is adapted by implementing a familiar context through the use of activities of daily living. The clinical

J-regular rings with injectivities

OpenAIRE

Shen, Liang

2010-01-01

A ring $R$ is called a J-regular ring if R/J(R) is von Neumann regular, where J(R) is the Jacobson radical of R. It is proved that if R is J-regular, then (i) R is right n-injective if and only if every homomorphism from an $n$-generated small right ideal of $R$ to $R_{R}$ can be extended to one from $R_{R}$ to $R_{R}$; (ii) R is right FP-injective if and only if R is right (J, R)-FP-injective. Some known results are improved.

Numerical response analysis of a large mat-type floating structure in regular waves; Matogata choogata futai kozobutsu no haro oto kaiseki

Energy Technology Data Exchange (ETDEWEB)

Yasuzawa, Y.; Kagawa, K.; Kitabayashi, K. [Kyushu University, Fukuoka (Japan); Kawano, D. [Mitsubishi Heavy Industries, Ltd., Tokyo (Japan)

1997-08-01

The theory and formulation for the numerical response analysis of a large floating structure in regular waves were given. This paper also reports the comparison between the experiment in the Shipping Research Institute in the Minitry of Transport and the result calculated using numerical analytic codes in this study. The effect of the bending rigidity of a floating structure and the wave direction on the dynamic response of a structure was examined by numerical calculation. When the ratio of structure length and incident wavelength (L/{lambda}) is lower, the response amplitude on the transmission side becomes higher in a wave-based response. The hydrodynamic elasticity exerts a dominant influence when L/{lambda} becomes higher. For incident oblique waves, the maximum response does not necessarily appear on the incidence side. Moreover, the response distribution is also complicated. For example, the portion where any flexible amplitude hardly appears exists. A long structure response can be predicted from a short structure response to some degree. They differ in response properties when the ridigity based on the similarity rule largely differs, irrespective of the same L/{lambda}. For higher L/{lambda}, the wave response can be easily predicted when the diffrection force is replaced by the concentrated exciting force on the incidence side. 13 refs., 14 figs., 3 tabs.

Reconsidering the Roland-Morris Disability Questionnaire: time for a multidimensional framework?

Science.gov (United States)

Magnussen, Liv Heide; Lygren, Hildegunn; Strand, Liv Inger; Hagen, Eli Molde; Breivik, Kyrre

2015-02-15

Cross-sectional design. To explore (1) the factor structure of the Roland-Morris Disability Questionnaire (RMDQ), (2) whether there is a dominant factor, and (3) whether the potential factors are unique predictors of other aspects related to back pain. The RMDQ is one of the most recommended back-specific questionnaires assessing disability. The RMDQ is scored as a unidimensional scale summarizing answers to all 24 questions (Yes/No) regarding daily life functioning. However, there are indications that the scale is multidimensional. Patients (n = 457; age, 18-60 yr) with 8 to 12 weeks of back pain filled in questionnaires assessing subjective health complaints, emotional distress, instrumental and emotion-focused coping, and fear voidance behavior at baseline. A total of 371 patients (81.7%) filled in the RMDQ. Exploratory factor analysis was used to examine the factor structure of RMDQ items. Multiple regression analyses were used to assess whether the derived factors predicted relevant problems in back pain differently. Exploratory factor analysis showed indices of model fit for a 3-factor solution after removing 2 items because of low prevalence (19 and 24). Two items were removed because of cross-loadings and low loadings (2 and 22). No support for a dominant factor was found as the 3 factors were only moderately correlated (r = 0.34-0.40), and the ratio between the first and second eigenvalue was 2.6, not supporting essential unidimensionality. "Symptoms" were the factor that most strongly predicted subjective health complaints, whereas "avoidance of activity and participation" predicted fear avoidance behavior, instrumental and emotional coping. "Limitation in daily activities" did not predict any of these variables. The main findings of our study are that the RMDQ consists of 3 independent factors, and not 1 dominant factor as suggested previously. We think the time is now ripe to start treating and scoring the RMDQ as a multidimensional scale. N/A.

Allocation of spectral and spatial modes in multidimensional metro-access optical networks

Science.gov (United States)

Gao, Wenbo; Cvijetic, Milorad

2018-04-01

Introduction of spatial division multiplexing (SDM) has added a new dimension in an effort to increase optical fiber channel capacity. At the same time, it can also be explored as an advanced optical networking tool. In this paper, we have investigated the resource allocation to end-users in multidimensional networking structure with plurality of spectral and spatial modes actively deployed in different networking segments. This presents a more comprehensive method as compared to the common practice where the segments of optical network are analyzed independently since the interaction between network hierarchies is included into consideration. We explored the possible transparency from the metro/core network to the optical access network, analyzed the potential bottlenecks from the network architecture perspective, and identified an optimized network structure. In our considerations, the viability of optical grooming through the entire hierarchical all-optical network is investigated by evaluating the effective utilization and spectral efficiency of the network architecture.

Manycore Performance-Portability: Kokkos Multidimensional Array Library

Directory of Open Access Journals (Sweden)

H. Carter Edwards

2012-01-01

Full Text Available Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs, and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1 manycore compute devices each with its own memory space, (2 data parallel kernels and (3 multidimensional arrays. Kernel execution performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1 separating data access patterns from computational kernels through a multidimensional array API and (2 introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].

Capturing Complex Multidimensional Data in Location-Based Data Warehouses

DEFF Research Database (Denmark)

Timko, Igor; Pedersen, Torben Bach

2004-01-01

Motivated by the increasing need to handle complex multidimensional data inlocation-based data warehouses, this paper proposes apowerful data model that is able to capture the complexities of such data. The model provides a foundation for handling complex transportationinfrastructures...

The Multidimensionality of Child Poverty: Evidence from Afghanistan

Science.gov (United States)

Trani, Jean-Francois; Biggeri, Mario; Mauro, Vincenzo

2013-01-01

This paper examines multidimensional poverty among children in Afghanistan using the Alkire-Foster method. Several previous studies have underlined the need to separate children from their adult nexus when studying poverty and treat them according to their own specificities. From the capability approach, child poverty is understood to be the lack…

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity

Science.gov (United States)

Naeem, S.; Prager, Case; Weeks, Brian; Varga, Alex; Flynn, Dan F. B.; Griffin, Kevin; Muscarella, Robert; Palmer, Matthew; Wood, Stephen; Schuster, William

2016-01-01

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity's value to ecosystem functions and the services they provide. This oversight means that our current understanding of the ecological and environmental consequences of biodiversity loss is limited primarily to what unidimensional studies have revealed. To address this issue, we review the literature, develop a conceptual framework for multidimensional biodiversity research based on this review and provide a case study to explore the framework. Our case study specifically examines how herbivory by whitetail deer (Odocoileus virginianus) alters the multidimensional influence of biodiversity on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional approach. Although our review, framework and case study illustrate the advantages of multidimensional over unidimensional approaches, they also illustrate the statistical and empirical challenges such work entails. Meeting these challenges, however, where data and resources permit, will be important if we are to better understand and manage the consequences we face as biodiversity continues to decline in the foreseeable future. PMID:27928041

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity.

Science.gov (United States)

Naeem, S; Prager, Case; Weeks, Brian; Varga, Alex; Flynn, Dan F B; Griffin, Kevin; Muscarella, Robert; Palmer, Matthew; Wood, Stephen; Schuster, William

2016-12-14

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity's value to ecosystem functions and the services they provide. This oversight means that our current understanding of the ecological and environmental consequences of biodiversity loss is limited primarily to what unidimensional studies have revealed. To address this issue, we review the literature, develop a conceptual framework for multidimensional biodiversity research based on this review and provide a case study to explore the framework. Our case study specifically examines how herbivory by whitetail deer (Odocoileus virginianus) alters the multidimensional influence of biodiversity on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional approach. Although our review, framework and case study illustrate the advantages of multidimensional over unidimensional approaches, they also illustrate the statistical and empirical challenges such work entails. Meeting these challenges, however, where data and resources permit, will be important if we are to better understand and manage the consequences we face as biodiversity continues to decline in the foreseeable future. © 2016 The Authors.

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

Directory of Open Access Journals (Sweden)

Maria E Pushpanathan

Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

SIDIS transverse spin azimuthal asymmetries at COMPASS: Multidimensional analysis

CERN Document Server

Parsamyan, Bakur

2015-01-01

Exploration of transverse spin structure of the nucleon via study of the spin (in)dependent azimuthal asymmetries in semi-inclusive deep inelastic scattering (SIDIS) and Drell-Yan (DY) reactions is one of the main aspects of the broad physics program of the COMPASS experiment (CERN, Switzerland). In past decade COMPASS has collected a considerable amount of polarized deuteron and proton SIDIS data while 2014 and 2015 runs were dedicated to the Drell-Yan measurements. Results on SIDIS azimuthal effects provided so far by COMPASS play an important role in general understanding of the three-dimensional nature of the nucleon. Giving access to the entire "twist-2" set of transverse momentum dependent (TMD) parton distribution functions (PDFs) and fragmentation functions (FFs) COMPASS data are being widely used in phenomenological analyses and experimental data fits. Recent unique and first ever x-$Q^{2}$-z-pT multidimensional results for transverse spin asymmetries obtained by COMPASS serve as a direct and unprece...

Iterative Regularization with Minimum-Residual Methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2007-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

Iterative regularization with minimum-residual methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2006-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES - their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

Exploding and non-exploding stars: Coupling nuclear reaction networks to multidimensional hydrodynamics

International Nuclear Information System (INIS)

Kifonidis, K.; Mueller, E.; Plewa, T.

2001-01-01

After decades of one-dimensional nucleosynthesis calculations, the growth of computational resources has meanwhile reached a level, which for the first time allows astrophysicists to consider performing routinely realistic multidimensional nucleosynthesis calculations in explosive and, to some extent, also in non-explosive environments. In the present contribution we attempt to give a short overview of the physical and numerical problems which are encountered in these simulations. In addition, we assess the accuracy that can be currently achieved in the computation of nucleosynthetic yields, using multidimensional simulations of core collapse supernovae as an example

Refined Modeling of Flexural Deformation of Layered Plates with a Regular Structure Made from Nonlinear Hereditary Materials

Science.gov (United States)

Yankovskii, A. P.

2018-01-01

On the basis of constitutive equations of the Rabotnov nonlinear hereditary theory of creep, the problem on the rheonomic flexural behavior of layered plates with a regular structure is formu-lated. Equations allowing one to describe, with different degrees of accuracy, the stress-strain state of such plates with account of their weakened resistance to transverse shear were ob-tained. From them, the relations of the nonclassical Reissner- and Reddytype theories can be found. For axially loaded annular plates clamped at one edge and loaded quasistatically on the other edge, a simplified version of the refined theory, whose complexity is comparable to that of the Reissner and Reddy theories, is developed. The flexural strains of such metal-composite annular plates in shortterm and long-term loadings at different levels of heat action are calcu-lated. It is shown that, for plates with a relative thickness of order of 1/10, neither the classical theory, nor the traditional nonclassical Reissner and Reddy theories guarantee reliable results for deflections even with the rough 10% accuracy. The accuracy of these theories decreases at elevated temperatures and with time under long-term loadings of structures. On the basic of relations of the refined theory, it is revealed that, in bending of layered metal-composite heat-sensitive plates under elevated temperatures, marked edge effects arise in the neighborhood of the supported edge, which characterize the shear of these structures in the transverse direction

Multidimensional profiles of health locus of control in Hispanic Americans.

Science.gov (United States)

Champagne, Brian R; Fox, Rina S; Mills, Sarah D; Sadler, Georgia Robins; Malcarne, Vanessa L

2016-10-01

Latent profile analysis identified health locus of control profiles among 436 Hispanic Americans who completed the Multidimensional Health Locus of Control scales. Results revealed four profiles: Internally Oriented-Weak, -Moderate, -Strong, and Externally Oriented. The profile groups were compared on sociocultural and demographic characteristics, health beliefs and behaviors, and physical and mental health outcomes. The Internally Oriented-Strong group had less cancer fatalism, religiosity, and equity health attributions, and more alcohol consumption than the other three groups; the Externally Oriented group had stronger equity health attributions and less alcohol consumption. Deriving multidimensional health locus of control profiles through latent profile analysis allows examination of the relationships of health locus of control subtypes to health variables. © The Author(s) 2015.

Applications of Convex Analysis to Multidimensional Scaling

OpenAIRE

Jan de Leeuw

2011-01-01

In this paper we discuss the convergence of an algorithm for metric and nonmetric multidimensional scaling that is very similar to the C-matrix algorithm of Guttman. The paper improves some earlier results in two respects. In the first place the analysis is extended to cover general Minkovski metrics, in the second place a more elementary proof of convergence based on results of Robert is presented.

Questionário multidimensional para análise da imagem do enfermeiro Cuestionario multidimensional para análisis de la imagen del enfermero A multidimensional questionnaire to evaluate the image of registered nurses

Directory of Open Access Journals (Sweden)

Luciana Barizon Luchesi

2010-01-01

Full Text Available OBJETIVO: Construir um questionário multidimensional para avaliar a percepção de alunos do ensino médio frente sobre a enfermagem e validar o questionário multidimensional em conteúdo, aparência e análise semântica. MÉTODOS: Estudo quanti-qualitativo com fins de instrumentação, utilizando o referencial teórico-metodológico de Pasquali, Silva e Ribeiro-Filho que recomendam as etapas de levantamento do conceito do constructo, geração dos itens do instrumento fundamentado na literatura e aferição das propriedades psicométricas. RESULTADOS: os itens do instrumento são derivados da literatura sobre psicologia social, história da enfermagem e escolha vocacional. Após validação de conteúdo, validação aparente e análise semântica, houve a aplicação do instrumento em uma amostra de 269 alunos. CONCLUSÃO: o instrumento mostrou-se de fácil entendimento e aplicação. Além de análise diagnóstica, o instrumento poderá ser utilizado em estudos experimentais.OBJETIVO: Construir un cuestionario multidimensional para evaluar la percepción de los alumnos de la enseñanza media sobre la enfermería y validar el cuestionario multidimensional en contenido, apariencia y análisis semántico. MÉTODOS: Estudio cuantitativo y cualitativo con fines de instrumentación, utilizando el marco teórico metodológico de Pasquali, Silva y Ribeiro-Filho que recomiendan las etapas de levantamiento del concepto del constructo, generación de los ítems del instrumento fundamentado en la literatura y evaluación de las propiedades psicométricas. RESULTADOS: Los ítems del instrumento son derivados de la literatura sobre psicología social, historia de la enfermería y elección vocacional. Después de la validación de contenido, validación aparente y análisis semántico, se aplicó el instrumento en una muestra de 269 alumnos. CONCLUSIÓN: El instrumento se mostró de fácil entendimiento y aplicación. Además del análisis de diagn

Access to serviced land for the urban poor: the regularization paradox in Mexico

Directory of Open Access Journals (Sweden)

Alfonso Iracheta Cenecorta

2000-01-01

Full Text Available The insufficient supply of serviced land at affordable prices for the urban poor and the need for regularization of the consequent illegal occupations in urban areas are two of the most important issues on the Latin American land policy agenda. Taking a structural/integrated view on the functioning of the urban land market in Latin America, this paper discusses the nexus between the formal and the informal land markets. It thus exposes the perverse feedback effects that curative regularization policies may have on the process by which irregularity is produced in the first place. The paper suggests that a more effective approach to the provision of serviced land for the poor cannot be resolved within the prevailing (curative regularization programs. These programs should have the capacity to mobilize the resources that do exist into a comprehensive program that links regularization with fiscal policy, including the exploration of value capture mechanisms.

Structures in Detonation Waves in Low-Pressure H2–O2–Ar Mixtures: A Summary of Results Obtained with the Adaptive Mesh Refinement Framework AMROC

Directory of Open Access Journals (Sweden)

Ralf Deiterding

2011-01-01

Full Text Available Numerical simulation can be key to the understanding of the multidimensional nature of transient detonation waves. However, the accurate approximation of realistic detonations is demanding as a wide range of scales needs to be resolved. This paper describes a successful solution strategy that utilizes logically rectangular dynamically adaptive meshes. The hydrodynamic transport scheme and the treatment of the nonequilibrium reaction terms are sketched. A ghost fluid approach is integrated into the method to allow for embedded geometrically complex boundaries. Large-scale parallel simulations of unstable detonation structures of Chapman-Jouguet detonations in low-pressure hydrogen-oxygen-argon mixtures demonstrate the efficiency of the described techniques in practice. In particular, computations of regular cellular structures in two and three space dimensions and their development under transient conditions, that is, under diffraction and for propagation through bends are presented. Some of the observed patterns are classified by shock polar analysis, and a diagram of the transition boundaries between possible Mach reflection structures is constructed.

Multi-dimensional medical images compressed and filtered with wavelets

International Nuclear Information System (INIS)

Boyen, H.; Reeth, F. van; Flerackers, E.

2002-01-01

Full text: Using the standard wavelet decomposition methods, multi-dimensional medical images can be compressed and filtered by repeating the wavelet-algorithm on 1D-signals in an extra loop per extra dimension. In the non-standard decomposition for multi-dimensional images the areas that must be zero-filled in case of band- or notch-filters are more complex than geometric areas such as rectangles or cubes. Adding an additional dimension in this algorithm until 4D (e.g. a 3D beating heart) increases the geometric complexity of those areas even more. The aim of our study was to calculate the boundaries of the formed complex geometric areas, so we can use the faster non-standard decomposition to compress and filter multi-dimensional medical images. Because a lot of 3D medical images taken by PET- or SPECT-cameras have only a few layers in the Z-dimension and compressing images in a dimension with a few voxels is usually not worthwhile, we provided a solution in which one can choose which dimensions will be compressed or filtered. With the proposal of non-standard decomposition on Daubechies' wavelets D2 to D20 by Steven Gollmer in 1992, 1D data can be compressed and filtered. Each additional level works only on the smoothed data, so the transformation-time halves per extra level. Zero-filling a well-defined area alter the wavelet-transform and then performing the inverse transform will do the filtering. To be capable to compress and filter up to 4D-Images with the faster non-standard wavelet decomposition method, we have investigated a new method for calculating the boundaries of the areas which must be zero-filled in case of filtering. This is especially true for band- and notch filtering. Contrary to the standard decomposition method, the areas are no longer rectangles in 2D or cubes in 3D or a row of cubes in 4D: they are rectangles expanded with a half-sized rectangle in the other direction for 2D, cubes expanded with half cubes in one and quarter cubes in the

The structure of medical competence and results on an Objective Structured Clinical Examination

NARCIS (Netherlands)

Jacobs, A.; Denessen, E.J.P.G.; Postma, C.

2004-01-01

Background: Medical competence is a central concept in medical education. Educational efforts in medical training are directed at the achievement of a maximal medical competence. The concept of the structure of medical competence (multidimensional or one-dimensional with strongly interrelated

Trust and credibility: measured by multidimensional scaling

International Nuclear Information System (INIS)

Warg, L.E.; Bodin, L.

1998-01-01

Full text of publication follows: in focus of much of today's research interest in risk communication, is the fact that the communities do not trust policy and decision makers such as politicians, government or industry people. This is especially serious in the years to come when we are expecting risk issues concerning for example the nuclear industry, global warming and hazardous waste, to be even higher on the political and social agenda all over the world. Despite the research efforts devoted to trust, society needs an in depth understanding of trust for conducting successful communication regarding environmental hazards. The present abstract is about an experimental study in psychology where focus has been on the possibility to use the multidimensional scaling technique to explore the characteristics people consider to be of importance when they say that certain persons are credible. In the study, a total of 61 students of the University of Oerebro, Sweden, were required to make comparisons of the similarity between 12 well-known swedish persons from politics science, media, industry, 'TV-world' and literature (two persons at a time), regarding their credibility when making statements about risks in society. In addition, the subjects were rating the importance of 19 factors for the credibility of a source. These 61 persons comprised three groups of students: pedagogists, business economists, and chemists. There were 61 % women and 39% men and the mean age was 23 years. The results will be analyzed using multidimensional scaling technique. Differences between the three groups will be analyzed and presented as well as those between men and women. In addition, the 19 factors will be discussed and considered when trying to label the dimensions accounted for by the multidimensional scaling technique. The result from this study will contribute to our understanding of important factors behind human judgments concerning trust and credibility. It will also point to a

Theme section: Multi-dimensional modelling, analysis and visualization

DEFF Research Database (Denmark)

Guilbert, Éric; Coltekin, Arzu; Antón Castro, Francesc/François

2016-01-01

(Biljecki et al., 2015) as well as the temporal, but also the scale dimension (Van Oosterom and Stoter, 2010) or, as mentioned by(Lu et al., 2016), multi-spectral and multi-sensor data. Such a view provides an organisation of multidimensional data around these different axes and it is time to explore each...

Self Esteem, Locus of Control and Multidimensional Perfectionism as the Predictors of Subjective Well Being

Science.gov (United States)

Karatas, Zeynep; Tagay, Ozlem

2012-01-01

The purpose of this study is to determine whether there is a relationship between self-esteem, locus of control and multidimensional perfectionism, and the extent to which the variables of self-esteem, locus of control and multidimensional perfectionism contribute to the prediction of subjective well-being. The study was carried out with 318 final…

Traveling waves of the regularized short pulse equation

International Nuclear Information System (INIS)

Shen, Y; Horikis, T P; Kevrekidis, P G; Frantzeskakis, D J

2014-01-01

The properties of the so-called regularized short pulse equation (RSPE) are explored with a particular focus on the traveling wave solutions of this model. We theoretically analyze and numerically evolve two sets of such solutions. First, using a fixed point iteration scheme, we numerically integrate the equation to find solitary waves. It is found that these solutions are well approximated by a finite sum of hyperbolic secants powers. The dependence of the soliton's parameters (height, width, etc) to the parameters of the equation is also investigated. Second, by developing a multiple scale reduction of the RSPE to the nonlinear Schrödinger equation, we are able to construct (both standing and traveling) envelope wave breather type solutions of the former, based on the solitary wave structures of the latter. Both the regular and the breathing traveling wave solutions identified are found to be robust and should thus be amenable to observations in the form of few optical cycle pulses. (paper)

Teachers' Views about the Education of Gifted Students in Regular Classrooms

Directory of Open Access Journals (Sweden)

Neşe Kutlu Abu

2017-12-01

Full Text Available The purpose of this study was to investigate classroom teachers’ views about the education of gifted students in regular classrooms. The sample of the study is composed of ten primary school teachers working in the city of Amasya and had gifted students in their classes. In the present study, phenomenological research design was used. Data was collected through semi-structured interviews and analyzed descriptively in the QSR N-Vivo package program. The findings showed that teachers did not believe a need for differentiating curriculum for gifted students; rather they expressed that regular curriculum was enough for gifted students. Based on the findings, it is clear that teachers need training both on the need of differentiated education for gifted students and strategies and approaches about how to educate gifted students. Teachers’ attitudes towards gifted students in regular classrooms should be investigated so that teachers’ unsupportive beliefs about differentiation for gifted students also influence their attitudes towards gifted students.

Two-way regularization for MEG source reconstruction via multilevel coordinate descent

KAUST Repository

Siva Tian, Tian

2013-12-01

Magnetoencephalography (MEG) source reconstruction refers to the inverse problem of recovering the neural activity from the MEG time course measurements. A spatiotemporal two-way regularization (TWR) method was recently proposed by Tian et al. to solve this inverse problem and was shown to outperform several one-way regularization methods and spatiotemporal methods. This TWR method is a two-stage procedure that first obtains a raw estimate of the source signals and then refines the raw estimate to ensure spatial focality and temporal smoothness using spatiotemporal regularized matrix decomposition. Although proven to be effective, the performance of two-stage TWR depends on the quality of the raw estimate. In this paper we directly solve the MEG source reconstruction problem using a multivariate penalized regression where the number of variables is much larger than the number of cases. A special feature of this regression is that the regression coefficient matrix has a spatiotemporal two-way structure that naturally invites a two-way penalty. Making use of this structure, we develop a computationally efficient multilevel coordinate descent algorithm to implement the method. This new one-stage TWR method has shown its superiority to the two-stage TWR method in three simulation studies with different levels of complexity and a real-world MEG data analysis. © 2013 Wiley Periodicals, Inc., A Wiley Company.

Local fields for asymptotic matching in multidimensional mode conversion

International Nuclear Information System (INIS)

Tracy, E. R.; Kaufman, A. N.; Jaun, A.

2007-01-01

The problem of resonant mode conversion in multiple spatial dimensions is considered. Using phase space methods, a complete theory is developed for constructing matched asymptotic expansions that fit incoming and outgoing WKB solutions. These results provide, for the first time, a complete and practical method for including multidimensional conversion in ray tracing algorithms. The paper provides a self-contained description of the following topics: (1) how to use eikonal (also known as ray tracing or WKB) methods to solve vector wave equations and how to detect conversion regions while following rays; (2) once conversion is detected, how to fit to a generic saddle structure in ray phase space associated with the most common type of conversion; (3) given the saddle structure, how to carry out a local projection of the full vector wave equation onto a local two-component normal form that governs the two resonantly interacting waves. This determines both the uncoupled dispersion functions and the coupling constant, which in turn determine the uncoupled WKB solutions; (4) given the normal form of the local two-component wave equation, how to find the particular solution that matches the amplitude, phase, and polarization of the incoming ray, to the amplitude, phase, and polarization of the two outgoing rays: the transmitted and converted rays

Long-Time Behaviour of Solutions for Autonomous Evolution Hemivariational Inequality with Multidimensional “Reaction-Displacement” Law

Directory of Open Access Journals (Sweden)

Pavlo O. Kasyanov

2012-01-01

Full Text Available We consider autonomous evolution inclusions and hemivariational inequalities with nonsmooth dependence between determinative parameters of a problem. The dynamics of all weak solutions defined on the positive semiaxis of time is studied. We prove the existence of trajectory and global attractors and investigate their structure. New properties of complete trajectories are justified. We study classes of mathematical models for geophysical processes and fields containing the multidimensional “reaction-displacement” law as one of possible application. The pointwise behavior of such problem solutions on attractor is described.

Higher derivative regularization and chiral anomaly

International Nuclear Information System (INIS)

Nagahama, Yoshinori.

1985-02-01

A higher derivative regularization which automatically leads to the consistent chiral anomaly is analyzed in detail. It explicitly breaks all the local gauge symmetry but preserves global chiral symmetry and leads to the chirally symmetric consistent anomaly. This regularization thus clarifies the physics content contained in the consistent anomaly. We also briefly comment on the application of this higher derivative regularization to massless QED. (author)

Effective action in multidimensional quantum gravity, and spontaneous compactification

International Nuclear Information System (INIS)

Bagrov, V.G.; Bukhbinder, I.L.; Odintsov, S.D.

1987-01-01

The one-loop effective action (Casimir energy) is obtained for a special form of model of multidimensional quantum gravity and for several variants of d-dimensional quantum R 2 -gravity on the space M 4 x T/sub d//sub -4/, where M 4 is Minkowski space and T/sub d//sub -4/ is the (d-4)-dimensional torus. It is shown that the effective action of the model of multidimensional quantum gravity and R 2 -gravity without the cosmological term and Einstein term leads to instability of the classical compactification. By a numerical calculation it is demonstrated that the effective action of five-dimensional R 2 -gravity with the cosmological term admits a self-consistent spontaneous compactification. The one-loop effective action is also found for five-dimensional Einstein gravity with antisymmetric torsion on the space M 4 x S 1 (S 1 is the one-dimensional sphere)

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

metadata artifacts (e.g., queries) to assist users with the analysis. However, modeling and sharing of most of these artifacts are typically overlooked. Thus, in this paper we focus on the query metadata artifact in the Exploratory OLAP context and propose an RDF-based vocabulary for its representation......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...... the method to a use case of transforming queries from SM4MQ to a vector representation. For the use case, we developed the prototype and performed an evaluation that shows how our approach can significantly ease and support user assistance such as query recommendation....

Multidimensional epidemic thresholds in diffusion processes over interdependent networks

International Nuclear Information System (INIS)

Salehi, Mostafa; Siyari, Payam; Magnani, Matteo; Montesi, Danilo

2015-01-01

Highlights: •We propose a new concept of multidimensional epidemic threshold for interdependent networks. •We analytically derive and numerically illustrate the conditions for multilayer epidemics. •We study the evolution of infection density and diffusion dynamics. -- Abstract: Several systems can be modeled as sets of interdependent networks where each network contains distinct nodes. Diffusion processes like the spreading of a disease or the propagation of information constitute fundamental phenomena occurring over such coupled networks. In this paper we propose a new concept of multidimensional epidemic threshold characterizing diffusion processes over interdependent networks, allowing different diffusion rates on the different networks and arbitrary degree distributions. We analytically derive and numerically illustrate the conditions for multilayer epidemics, i.e., the appearance of a giant connected component spanning all the networks. Furthermore, we study the evolution of infection density and diffusion dynamics with extensive simulation experiments on synthetic and real networks

Structural Analysis and Anticoagulant Activities of the Novel Sulfated Fucan Possessing a Regular Well-Defined Repeating Unit from Sea Cucumber

Directory of Open Access Journals (Sweden)

Mingyi Wu

2015-04-01

Full Text Available Sulfated fucans, the complex polysaccharides, exhibit various biological activities. Herein, we purified two fucans from the sea cucumbers Holothuria edulis and Ludwigothurea grisea. Their structures were verified by means of HPGPC, FT-IR, GC–MS and NMR. As a result, a novel structural motif for this type of polymers is reported. The fucans have a unique structure composed of a central core of regular (1→2 and (1→3-linked tetrasaccharide repeating units. Approximately 50% of the units from L. grisea (100% for H. edulis fucan contain sides of oligosaccharides formed by nonsulfated fucose units linked to the O-4 position of the central core. Anticoagulant activity assays indicate that the sea cucumber fucans strongly inhibit human blood clotting through the intrinsic pathways of the coagulation cascade. Moreover, the mechanism of anticoagulant action of the fucans is selective inhibition of thrombin activity by heparin cofactor II. The distinctive tetrasaccharide repeating units contribute to the anticoagulant action. Additionally, unlike the fucans from marine alga, although the sea cucumber fucans have great molecular weights and affluent sulfates, they do not induce platelet aggregation. Overall, our results may be helpful in understanding the structure-function relationships of the well-defined polysaccharides from invertebrate as new types of safer anticoagulants.

Race and gender matter: a multidimensional approach to conceptualizing and measuring stress in African American women.

Science.gov (United States)

Woods-Giscombé, Cheryl L; Lobel, Marci

2008-07-01

Based on prior research and theory, the authors constructed a multidimensional model of stress in African American women comprised of race-related, gender-related, and generic stress. Exposure to and appraisal of these three types of stress were combined into a higher-order global stress factor. Using structural equation modeling, the fit of this stress factor and its ability to predict distress symptoms were examined in 189 socioeconomically diverse African American women aged 21 to 78. Results support the multidimensional conceptualization and operationalization of stress. Race-related, gender-related, and generic stress contributed equally to the global stress factor, and global stress predicted a significant amount of variance in distress symptoms and intensity. This model exhibited better fit than a model without a global stress factor, in which each stress component predicted distress directly. Furthermore, race-related, gender-related, and generic stress did not contribute to distress beyond their representation in the global stress factor. These findings illustrate that stress related to central elements of identity, namely race and gender, cohere with generic stress to define the stress experience of African American women. Copyright (c) 2008 APA, all rights reserved.

Coexistence of Two Singularities in Dewetting Flows: Regularizing the Corner Tip

NARCIS (Netherlands)

Peters, I.R.; Snoeijer, Jacobus Hendrikus; Daerr, Adrian; Limat, Laurent

2009-01-01

Entrainment in wetting and dewetting flows often occurs through the formation of a corner with a very sharp tip. This corner singularity comes on top of the divergence of viscous stress near the contact line, which is only regularized at molecular scales. We investigate the fine structure of corners

Temporally Regular Musical Primes Facilitate Subsequent Syntax Processing in Children with Specific Language Impairment.

Science.gov (United States)

Bedoin, Nathalie; Brisseau, Lucie; Molinier, Pauline; Roch, Didier; Tillmann, Barbara

2016-01-01

Children with developmental language disorders have been shown to be also impaired in rhythm and meter perception. Temporal processing and its link to language processing can be understood within the dynamic attending theory. An external stimulus can stimulate internal oscillators, which orient attention over time and drive speech signal segmentation to provide benefits for syntax processing, which is impaired in various patient populations. For children with Specific Language Impairment (SLI) and dyslexia, previous research has shown the influence of an external rhythmic stimulation on subsequent language processing by comparing the influence of a temporally regular musical prime to that of a temporally irregular prime. Here we tested whether the observed rhythmic stimulation effect is indeed due to a benefit provided by the regular musical prime (rather than a cost subsequent to the temporally irregular prime). Sixteen children with SLI and 16 age-matched controls listened to either a regular musical prime sequence or an environmental sound scene (without temporal regularities in event occurrence; i.e., referred to as "baseline condition") followed by grammatically correct and incorrect sentences. They were required to perform grammaticality judgments for each auditorily presented sentence. Results revealed that performance for the grammaticality judgments was better after the regular prime sequences than after the baseline sequences. Our findings are interpreted in the theoretical framework of the dynamic attending theory (Jones, 1976) and the temporal sampling (oscillatory) framework for developmental language disorders (Goswami, 2011). Furthermore, they encourage the use of rhythmic structures (even in non-verbal materials) to boost linguistic structure processing and outline perspectives for rehabilitation.

Experimental observation of a multi-dimensional mixing behavior of steam-water flow in the MIDAS test facility

International Nuclear Information System (INIS)

Kweon, T. S.; Yun, B. J.; Ah, D. J.; Ju, I. C.; Song, C. H.; Park, J. K.

2001-01-01

Multi-dimensional thermal-hydraulic hehavior, such as ECC (Emergency Core Cooling) bypass, ECC penetration, steam-water condensation and accumulated water level, in an annular downcomer of a PWR (Pressurized Water Reactor) reactor vessel with a DVI(Direct Vessel Injection) injection mode is presented based on the experimental observations in the MIDAS (Multi-dimensional Investigation in Downcomer Annulus Simulation) steam-water facility. From the steady-state tests to similate a late reflood phase of LBLOCA (Large Break Loss-of-Coolant Accidents), major thermal-hydraulic phenomena in the downcomer are quantified under a wide range of test conditions. Especially, isothermal lines show well multi-dimensional phenomena of phase interaction between steam and water in the annulus downcomer. Overall test results show that multi-dimensional thermal-hydraulic behaviors occur in the downcomer annulus region as expected. The MIDAS test facility is a steam-water separate effect test facility, which is 1/4.93 linearly scaled-down of a 1400 MWe PWR type of nuclear reactor, with focusing on understanding multi-dimensional thermal-hydraulic phenomena in annulus downcomer with various types of safety injection location during refill or reflood phase of a LBLOCA in PWR

75 FR 53966 - Regular Meeting

Science.gov (United States)

2010-09-02

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of the Farm...

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.

Work and family life of childrearing women workers in Japan: comparison of non-regular employees with short working hours, non-regular employees with long working hours, and regular employees.

Science.gov (United States)

Seto, Masako; Morimoto, Kanehisa; Maruyama, Soichiro

2006-05-01

This study assessed the working and family life characteristics, and the degree of domestic and work strain of female workers with different employment statuses and weekly working hours who are rearing children. Participants were the mothers of preschoolers in a large Japanese city. We classified the women into three groups according to the hours they worked and their employment conditions. The three groups were: non-regular employees working less than 30 h a week (n=136); non-regular employees working 30 h or more per week (n=141); and regular employees working 30 h or more a week (n=184). We compared among the groups the subjective values of work, financial difficulties, childcare and housework burdens, psychological effects, and strains such as work and family strain, work-family conflict, and work dissatisfaction. Regular employees were more likely to report job pressures and inflexible work schedules and to experience more strain related to work and family than non-regular employees. Non-regular employees were more likely to be facing financial difficulties. In particular, non-regular employees working longer hours tended to encounter socioeconomic difficulties and often lacked support from family and friends. Female workers with children may have different social backgrounds and different stressors according to their working hours and work status.

The Formal Organization of Knowledge: An Analysis of Academic Structure.

Science.gov (United States)

Gumport, Patricia J.; Snydman, Stuart K.

2002-01-01

A case study of San Jose State University examined how changes in what counts as knowledge are reflected in universities' academic structure. Found that the multidimensionality of academic structure, with bureaucratic (departmental) structure relatively fixed and programmatic (degree program) structure relatively open, enables universities to…

Fiscal 1997 project on the R and D of industrial scientific technology under consignment from NEDO. Report on the results of the R and D of technologies to invent original high-functional materials (development of precise structure control materials for enhancement of oil refining); 1997 nendo sangyo kagaku gijutsu kenkyu kaihatsu jigyo Shin Energy Sangyo Gijutsu Sogo Kaihatsu Kiko itaku. Dokusoteki kokino zairyo sosei gijutsu no kenkyu kaihatsu (sekiyu seisei kodoka seimitsu kozo seigyo zairyo kaihatsu) seika hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-03-01

The paper described the R and D of technologies for creating original high-functional materials under the R and D system of industrial scientific technology. Japan chemical Innovation Institute (JCII) is conducting intensive joint researches under consignment from NEDO with private companies, universities and national research institutes. Among those, the paper reported the fiscal 1997 results of the following two researches conducted as development of precise structure control materials for enhancement of oil refining: precision catalytic polymerization and multi-dimensional space polymer. As to the precision catalytic polymerization, the paper is aimed at developing base technologies for the molecular weight and stereoregularity by which remarkable improvement in performance of addition polymerization type polymer can be expected, and on the development of a polymerization catalyst which arbitarily controls the primary structure such as end group structure and of a precision addition polymerization process. Subthemes are addition polymerization with limit and oriented catalytic polymerization. In relation to multi-dimensional space polymer, the paper is aimed at developing highly selective polymerization technology of aromatic compounds using enzyme related catalysts and synthesis technology of regular structure polymer, and synthesis technology of new polymer group having a new chain pattern except covalent bond/new polymer group having characteristics in three-dimensional space geometric structure. 244 refs,, 160 figs., 94 tabs.

A comparison of multidimensional scaling methods for perceptual mapping

NARCIS (Netherlands)

Bijmolt, T.H.A.; Wedel, M.

Multidimensional scaling has been applied to a wide range of marketing problems, in particular to perceptual mapping based on dissimilarity judgments. The introduction of methods based on the maximum likelihood principle is one of the most important developments. In this article, the authors compare

Multidimensional adaptive testing with a minimum error-variance criterion

NARCIS (Netherlands)

van der Linden, Willem J.

1997-01-01

The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple

A Template Model for Multidimensional Inter-Transactional Association Rules