In this paper, a model is described to add human-like scent perception to the Spatial Model of Interaction (SMI) [BF93]. The SMI is a generally accepted model for interaction between Intelligent Virtual Agents in Virtual Environments. The extension of the SMI with scent perception consists of Virtual Odor and a Virtual Nose Sensor. Virtual Odor is represented by particles in the Virtual Environ...

Objects are more easily recognized in their typical context. However, is contextual information activated early enough to facilitate the perception of individual objects, or is contextual facilitation caused by postperceptual mechanisms? To elucidate this issue, we first need to study the temporal dynamics and neural interactions associated with contextual processing. Studies have shown that th...

Situation awareness (SA) is a critical factor for human decision making and performance in dynamic environments. Actually SA is a mental model of the current state of the environment and includes many types of complex systems such as safety supervisory systems. The current paper employs two focus areas including neural network and expert system for maintaining SA in a safety supervisory system....

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

How the primate attentional control network interacts with posterior sensory regions to bias perception is not fully understood. Using magnetoencephalography (MEG) supplemented by functional magnetic resonance imaging (fMRI), a recent study reported that human inferior frontal junction (IFJ) could play a key role in biasing perception through neural synchrony with posterior sensory regions.

This paper presents a feed forward back-propagation neural network model to predict the retained tensile strength and design chart in order to estimation of the strength reduction factors of nonwoven geotextiles due to installation process. A database of 34 full-scale field tests were utilized to train, validate and test the developed neural network and regression model. The results show that t...

Computer simulations of neural network processes fill an important methodological niche, permitting the investigation of questions not resolvable by physiological, behavioral, or formal approaches alone. Two types of network simulations are considered: simulations of boundary completion and simulations of segmentation. Simulations that compare properties of published models with variations of t...

estimating the final price of products is of great importance. for manufacturing companies proposing a final price is only possible after the design process over. these companies propose an approximate initial price of the required products to the customers for which some of time and money is required. here using the existing data of already designed transformers and utilizing the bayesian anal...

Estimation (Forecasting) of industrial production costs is one of the most important factor affecting decisions in the highly competitive markets. Thus, accuracy of the estimation is highly desirable. Hibrid Regression Neural Network is an approach proposed in this paper to obtain better fitness in comparison with Regression Analysis and the Neural Network methods. Comparing the estimated resul...