Amirhosein Ghaderi | University of Tabriz (original) (raw)

Papers by Amirhosein Ghaderi

Introduction: Contrary to Diagnostic and Statistical Manual of Mental Disorders (DSM-5), fifth ed... more Introduction: Contrary to Diagnostic and Statistical Manual of Mental Disorders (DSM-5), fifth edition, some studies indicate that ADHD-inattentive presentation (ADHD-I) is a distinct diagnostic disorder and not an ADHD presentation.
Methods: In this study, 12 ADHD-combined presentation (ADHD-C), 10 ADHD-I, and 13 controls were enrolled and their resting state EEG recorded. Following this, a graph theoretical analysis was performed and functional integration and segregation of brain network was calculated.
Results: The results show that clustering coefficient of theta band was significantly different among three groups and significant differences were observed in theta global efficiency between controls and ADHD-C. Regarding the alpha band, a lower clustering coefficient was observed in control subjects. In the beta band, clustering coefficient was significantly different between the control and children with ADHD-C and also between ADHD-I and ADHD-C. The clustering coefficient, in the subjects with ADHD-C, demonstrated a rapid decline and was significantly lower than the subjects with ADHD-I and control.
Conclusion: Decreased clustering, in high thresholds, may be associated with hyperactivity while increased segregation in low thresholds with inattentiveness. A different functional network occurs in the ADHD-C brain that is consistent with several studies that have reported
ADHD-I as a distinct disorder.

The theory of special relativity suggests that, time is a byproduct of velocity and it is created... more The theory of special relativity suggests that, time is a byproduct of velocity and it is created during movement, obligatory.
Subjective time is perceived during all senses and this perception also is obligatory. In this paper, I suppose that psychological perceived time is analogous to physical relative time. The brain uses many neural pathways in sensory system
for perception.
Overall the length of these pathways is very large and the information network is very huge. On the other hand, binding in this network is occurred in very little time. So the velocity of data transfer and integration in this network is too high. I suggest that time perception is related to this high speed. In this paper the internal clock and other dedicated models have been considered as Newtonian timing systems (an invalid theory). Also two time perception models which are based on the theory of special relativity are criticized and a novel hypothesis based on special relativity and brain activity is presented. The proposed hypothesis suggests that, the velocity of integration in the human cortex is near the speed of light and subjective time dilation and compression is occurred due to this relativistic speed. Many time distortions during psychological tasks and many physiological evidences are consistent with this novel hypothesis.

This paper introduces a new 3-step face detection algorithm which has been done in MATLAB. This 3... more This paper introduces a new 3-step face detection algorithm which has been done in MATLAB. This 3-step algorithm is based on skin mask, number of holes in each region and Support Vector Machine (SVM) for face detection in RGB images. Because of using the 10 levels images around its optimum threshold to train in SVM, the training step can be done so fast. In addition, it will be shown that this method is so accurate in compare with the previous methods because of using these 10 levels just around the optimum threshold value.

tThere are some computational models for fluids viscosity calculation. However, each of these mod... more tThere are some computational models for fluids viscosity calculation. However, each of these models isreliable in confined density. In this comparative study two methods are evaluated for viscosity predictionin all range of density. We determine the effectiveness of each of the models and we demonstrate thestrengths and weaknesses of them. Viscosity of the six refrigerants is calculated by some computationalmodels based on Chapman–Enskog and Rainwater–Friend theories. Then a feed forward artificial neuralnetwork (ANN) with multilayer perceptrons is used to viscosity prediction and finally two methods(computational models and artificial neural network) are comparing. It is concluded that there is noopinion by computational methods to calculate viscosity from low to high density. The results show thatprediction accuracy of computational models in low and moderate densities is good as ANN method.However artificial neural network has very good accuracy in high densities while computational methodis defeated when the density is more than 8.

The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature ... more The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature change is one example of the nonlinear systems. In this work, a new neural network method is proposed for forecasting maximum air temperature in two cities. In this method, the regular graph concept is used to construct some partially connected neural networks that have regular structures. The learning results of fully connected ANN and networks with proposed method are compared. In some case, the proposed method has the better result than conventional ANN. After specifying the best network, the effect of input pattern numbers on the prediction is studied and the results show that the increase of input patterns has a direct effect on the prediction accuracy.