In organizational management, researchers and managers study separations or faultlines that occur in diverse teams when members form subgroups based on the alignment of multiple demographic characteristics. The team faultline concept is operationalized using multivariate cluster analysis—analysts use faultline measures to identify subgroups/clusters in a team and to quantify how subgroups/clust...

Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effectiveness of this technique on large data is reduced by edge clutter. In this paper, we present a novel framework to reduce edge clutter, consequently improving the effectiveness of visual clustering. We exploit curved...

as widespread deserts is located in west and southwest of iran plateau, dust storms form due to west andsouthwest systems over syria or iraq as well as arabian peninsula. these systems severely affect west and southwestregions. sometimes the fine dusts transmit to central, north east, and east regions. in this study for investigating dustysynoptical patterns, meteorological data at 5 synoptic s...

background: in order to check the practicality of classification of universities of medical sciences (umss) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of umss. methods: in the first phase, we approached a group of experts who had a deep experience in the management of umss and in the mini...

introduction of human development index (hdi) by undp in early 1990 followed a surge in use of non-parametric and parametric indices for measurement and comparison of countries performance in development, globalization, competition, well-being and etc. the hdi is a composite index of three indicators. its components are to reflect three major dimensions of human development: longevity, knowledg...

the main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. in case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...

We propose an approach for performing adaptive principal component extraction. By this approach, the Least Mean Squared Error Reconstruction (LMSER) Principle is implemented in a successive way such that the reconstruction error is fedback as inputs for training the network's weights. Simulations results have shown that this type of LMSER implementation can perform Robust Principal Component An...

a neural network is developed for the determination of leaky confined aquifer parameters. leakage into the aquifer takes place from the storage in the confining aquitard. the network is trained for the well function of leaky confined aquifers by the back propagation technique and adopting the levenberg–marquardt optimization algorithm. by applying the principal component analysis (pca) on the a...

Understanding how protein folds into a functional and structural configuration is arguably one of the most important and challenging problems in computational biology. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus the reaction coordinates such as the fraction of native contacts, the radius of gyration, the principal components an...

Article history: Received 15 December 2011 Received in revised form 28 June 2013 Accepted 5 July 2013 Available online 16 July 2013