in recent decades, seizure prediction caused a lot of research in both signal processing and neuroscience field. the researches tried to enhance the conventional seizure prediction algorithms such that rate of the false alarms be appropriately small so that seizures can be predicted according to clinical standards. up to now none of the proposed algorithms have been sufficiently adequate. in th...

lack of trust is one of the key bottle necks in e-commerce development. nowadays many advanced technologies are trying to address the trust issues in e-commerce. one among them suggests using suitable user interfaces. this paper investigates the functionality and capabilities of 3d graphical user interfaces in regard to trust building in the customers of next generation of b2c e-commerce websit...

for large and complex reacting systems, computational efficiency becomes a critical issue in process simulation, optimization and model-based control. mechanism simplification is often a necessity to improve computational speed. we present a novel approach to simplification of reaction networks that formulates the model reduction problem as an optimization problem and solves it using genetic al...

in this study with the inspirations from both neuroscience and computer science, a combinatorial framework for object recognition was proposed having benefited from the advantages of both biologically-inspired hmax_s architecture model for feature extraction and extreme learning machine (elm) as a classifier. hmax model is a feed-forward hierarchical structure resembling the ventral pathway in ...

logic analysis and attack construction methods are two major approaches in verification of cryptographic protocols. however, it is almost preferable to use both of them for a complete analysis. in this paper, a generic framework for the integration of the two verification approaches is presented. using the framework we can propose analysis methods in which security properties and breach scenari...

computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. nowadays, despite the numerous time series forecasting models propos...

in this work the mathematical model of a spatial pattern inchemical and biological systems is investigated numerically. theproposed model considered as a nonlinear reaction-diffusionequation. a computational approach based on finite difference andrbf-collocation methods is conducted to solve the equation withrespect to the appropriate initial and boundary conditions. theability and robustness o...

a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...