Vibration based techniques of structural damage detection using model updating method, are computationally expensive for large-scale structures. In this study, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), To efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the M...

an integrated model for magnetoencephalography (meg) and functional magnetic resonance imaging (fmri) is proposed. in the proposed model, meg and fmri outputs are related to the corresponding aspects of neural activities in a voxel. post synaptic potentials (psps) and action potentials (aps) are two main signals generated by neural activities. in the model, both of meg and fmri are related to t...

abstract introduction: neuro-occupation is one of the newest models in occupational therapy (ot). the nature of this model is based on the coexistence and dynamic interactions between brain’s neural system functions and engagement of an individual in occupations. neuro-occupation model holistically views the individual as a blending of neuroscience and occupation. the human brain is perceived t...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...

Multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE), are chronic inflammatory demyelinating disorders of central nervous system (CNS). While the cause is unclear, the fundamental mechanism is thought to be destruction of myelin sheaths of neurons through immune system. One of the approaches being proposed in EAE therapy is neural stem cells (NSCs) trans...

In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...

Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

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...