Using the example of an electronic photo album, a novel user input method for digital appliances is introduced. Based on tilting and gesturing with the device, the Rock ’n’ Scroll input method is shown to be sufficient for scrolling, selection, and commanding an application without resorting to buttons, touch screens, spoken commands or other input methods. User experiments with a prototype sys...

Process parameter window selection in semiconductor manufacturing field is usually the problem to find out the ranges of input parameters that meet production requirements, which requires allocating optima of a multimodal function efficiently. To achieve good results under the conditions of multimodal model and process control requirement, a NichePSO algorithm based method for parameter window ...

The problem of input variable selection is well known in the task of modeling real world data. In this paper, we propose a novel model-free algorithm for input variable selection using independent component analysis and higher order cross statistics. Experimental results are given which indicate that the method is capable of giving reliable performance and that it outperforms other approaches w...

The Japanese input method is a complex procedure involving preediting operations. An application that accepts Japanese from an input device must have three systems for the input method: a keybinding system, a manipulator for preediting, and a kana-to-kanji conversion system. Various keybinding systems and manipulators accelerate input operations. Our implementation separates an application from...

The problem of input variable selection is well known in the task of modeling real-world data. In this paper, we propose a novel model-free algorithm for input variable selection using independent component analysis and higher order cross statistics. Experimental results are given which indicate that the method is capable of giving reliable performance and that it outperforms other approaches w...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

To deal with the overfitting problems that occur when there are not enough examples compared to the number of input variables in supervised learning, traditional approaches are weight decay and greedy variable selection. An alternative that has recently started to attract attention is to keep all the variables but to put more emphasis on the “most useful” ones. We introduce a new regularization...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

A method of incorporating experience in iterative learning controllers is proposed in this paper. Importance of the selection of initial control input in the convergence of error is highlighted. It is proposed that if previous experience of the controller can be incorporated in the selection of the initial control input for a new desired trajectory tracking task, the convergence of error can be...

Considering the importance of Cd and U as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the Eshtehard region in Iran by means of a developed artificial neural network (ANN) model. The forward selection (FS) method is used to select the input variables and develop hybrid models by ANN. From 45 input candidates, 13 and 14 ...