1,721,526 research outputs found
Organization change and development
No full texttag=1 data=Organization change and development
tag=2 data=Beer, Michael%Walton, Anna Elise
tag=3 data=Annual Review of Psychology. No.38 p.339-367
tag=6 data=^d ^m ^y1987
tag=8 data=MANAGEMENT
tag=10 data=Applying theory from psychology and organizational behaviour, organization development comprises a set of actions undertaken to improve organizational effectiveness and employee well-being.
tag=15 data=JOUApplying theory from psychology and organizational behaviour, organization development comprises a set of actions undertaken to improve organizational effectiveness and employee well-being
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Why change programs don't produce change. by Michael Beer, Russell A. Eisenstat, and Bert Spector
No full texttag=1 data=Why change programs don't produce change. by Michael Beer, Russell A. Eisenstat, and Bert Spector
tag=2 data=Beer, Michael%Eisenstat, Russell A.%Spector, Bert
tag=3 data=Harvard Business Review,
tag=6 data=November/December 1990
tag=7 data=158-166.
tag=8 data=MANAGEMENT
tag=10 data=Effective corporate renewal starts at the bottom, through informal efforts to solve business problems.
tag=11 data=1991/3/1
tag=12 data=91/0108
tag=13 data=CABEffective corporate renewal starts at the bottom, through informal efforts to solve business problems
Optimization or Bayesian strategy? Performance of the Bhattacharyya distance in different algorithms of stochastic model updating
No full textThe Bhattacharyya distance has been developed as a comprehensive uncertainty quantification metric by capturing multiple uncertainty sources from both numerical predictions and experimental measurements. This work pursues a further investigation of the performance of the Bhattacharyya distance in different methodologies for stochastic model updating, and thus to prove the universality of the Bhattacharyya distance in various currently popular updating procedures. The first procedure is the Bayesian model updating where the Bhattacharyya distance is utilized to define an approximate likelihood function and the transitional Markov chain Monte Carlo algorithm is employed to obtain the posterior distribution of the parameters. In the second updating procedure, the Bhattacharyya distance is utilized to construct the objective function of an optimization problem. The objective function is defined as the Bhattacharyya distance between the samples of numerical prediction and the samples of the target data. The comparison study is performed on a four degrees-of-freedom mass-spring system. A challenging task is raised in this example by assigning different distributions to the parameters with imprecise distribution coefficients. This requires the stochastic updating procedure to calibrate not the parameters themselves, but their distribution properties. The second example employs the GARTEUR SM-AG19 benchmark structure to demonstrate the feasibility of the Bhattacharyya distance in the presence of practical experiment uncertainty raising from measuring techniques, equipment, and subjective randomness. The results demonstrate the Bhattacharyya distance as a comprehensive and universal uncertainty quantification metric in stochastic model updating.</p
Distribution-free stochastic model updating of dynamic systems with parameter dependencies
Full text linkThis work proposes a distribution-free stochastic model updating framework to calibrate the joint probabilistic distribution of the multivariate correlated parameters. In this framework, the marginal distributions are defined as the staircase density functions and the correlation structure is described by the Gaussian copula function. The first four moments of the staircase density functions and the correlation coefficients are updated by an approximate Bayesian computation, in which the Bhattacharyya distance-based metric is proposed to define an approximate likelihood that is capable of capturing the stochastic discrepancy between model outputs and observations. The feasibility of the framework is demonstrated on two illustrative examples and a followed engineering application to the updating of a nonlinear dynamic system using observed time signals. The results demonstrate the capability of the proposed updating procedure in the very challenging condition where the prior knowledge about the distribution of the parameters is extremely limited (i.e., no information on the marginal distribution families and correlation structure is available)
Efficient variational Bayesian model updating by Bayesian active learning
Full text linkAs a main task of inverse problem, model updating has received more and more attention in the area of inspection, sensing, and monitoring technologies during the recent decades, where the estimation of posterior probability density function (PDF) of unknown model parameters is still challenging for expensive-to-evaluate models of interest. In this paper, a novel variational Bayesian inference method is proposed to approximate the real posterior PDF of unknown model parameters by using Gaussian mixture model and measurement responses. A Gaussian process regression model is first trained for approximating the logarithm of the product of likelihood function and prior PDF, with which, another Gaussian process model is induced for approximating the expensive evidence lower bound (ELBO). Then, two Bayesian numerical methods, i.e., Bayesian optimization and Bayesian quadrature, are combined sequentially as a novel Bayesian active learning method for searching the global optima of the parameters of the variational posterior density. The proposed method inherits the advantages of both Bayesian numerical methods, which includes good global convergence, much less number of simulator calls, etc. Three examples, including the dynamic model of a two degrees of freedom structures, the lubrication model of a hybrid journal bearing, and the dynamic model of an airplane structure, are introduced for demonstrating the relative merits of the proposed method. Results show that, given desired requirement of numerical accuracy, the proposed method is more efficient than the parallel methods
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
