The design of multiple feedback topology Chebyshev low-pass active filter with average differential evolution algorithm

Neural Computing and Applications - This study presents the design of a tenth-order multiple feedback Chebyshev low-pass filter (MF-C-LPF). Component selection and gain calculation of filters are...     

3D Hair sketching for real-time dynamic & key frame animations

Physically based simulation of human hair is a well studied and well known problem. But the “pure” physically based representation of hair (and other animation elements) is not the only concern of the animators, who want to “control” the creation and animation phases of the content. This paper describes a sketch-based tool, with which a user can both create hair models with different styling parameters and produce animations of these created hair models using physically and key frame-based techniques. The model creation and animation production tasks are all performed with direct manipulation techniques in real-time.     

Methodological Challenges in Union Commitment Studies.

Methodological problems in studies of union commitment were identified and illustrated with data from 4,641 members and 479 stewards in 297 local teachers' unions. Using a 20-item union commitment scale, results confirmed the existence of 3 substantive factors and 1 method factor at the individual level of analysis: loyalty to the union, responsibility to the union, willingness to work for the union, and a factor of negatively worded items. Tests of measurement invariance showed that the scale captured commitment for rank-and-file members but not for union stewards. The authors also found partial measurement invariance between long-time and newer members and full measurement invariance between men and women. Finally, the authors found that violation of the statistical assumption of independence reduced model fit when individual commitment scores were analyzed without attention to the hierarchical nature of the data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Forecasting of Turkey's net electricity energy consumption on sectoral bases

In this study forecast of Turkey's net electricity energy consumption on sectoral basis until 2020 is explored. Artificial neural networks (ANN) is preferred as forecasting tool. The reasons behind choosing ANN are the ability of ANN to forecast future values of more than one variable at the same time and to model the nonlinear relation in the data structure. Founded forecast results by ANN are compared with official forecasts.