fardad farokhi
Biomedical Engineering Department, Islamic Azad University Central Tehran Branch
[ 1 ] - Integrated Fuzzy Control of Temperature, Light and Emergency Conditions for Smart Home Application
Smart home is composed of several controllers with different plants in control. If each controller works independently, without considering the mutual effect of the others in the control process, the whole system could definitely not converge to an optimum desired status and may not ever reach the demanded condition. The function of different controller system may has conflict In some condition...
[ 2 ] - Improvement of Coverage Algorithm in WSN in Terms of Sensor Numbers and Power Amount
Wireless sensor networks(WSN) have unique properties that distinguished them from other wireless networks and have special challenges. Not-chargeable, not-changeable and limited power supplies of sensor nodes is the most important challenge of this networks, and if the power supply of node expired, a part of data maybe lost. Because of the importance of covers in wireless sensors, in this work ...
[ 3 ] - Neural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features
This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...
[ 4 ] - Efficient Data Mining with Evolutionary Algorithms for Cloud Computing Application
With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...
[ 5 ] - Efficient Parameters Selection for CNTFET Modelling Using Artificial Neural Networks
In this article different types of artificial neural networks (ANN) were used for CNTFET (carbon nanotube transistors) simulation. CNTFET is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. In determining the accurate output drain current of CNTFET, time lapsed and accuracy of different simulation methods were compared. The training data for...
[ 6 ] - Intrusion Detection in Wireless Sensor Networks using Genetic Algorithm
Wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. Routing attacks on the networks, where a malicious node from sending data to the base station is perceived. In this article, a method that can be used to transfer the data securely to prevent attacks...
[ 7 ] - Image Stitching of the Computed Radiology images Using a Pixel-Based Approach
In this paper, a method for automatic stitching of radiology images based on pixel features has been presented. In this method, according to the smooth texture of radiological images and in order to increase the number of the extracted features after quality enhancement of initial radiology images, 45 degree isotropic mask is applied to each radiology image to observe the image details. After t...
[ 8 ] - Decreasing Starting Current for Separate Excited DC Motor using ANFIS Controller
Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...
[ 9 ] - Effective Feature Selection for Pre-Cancerous Cervix Lesions Using Artificial Neural Networks
Since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. There are 2 ways to stop this disease from developing. One way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. The presented approach...
[ 10 ] - Improvement of Working Memory Performance by Parietal Upper Alpha Neurofeedback Training
Working memory (WM) is a part of human memory, the ability to maintain and manipulate information. WM performance is impaired in some neurological and psychiatric disorders such as schizophrenia and ADHD. Neurofeedback training is a self-regulation method which can be used to improve WM performance by changing related EEG parameters. In this paper we used neurofeedback training to improve WM pe...
[ 11 ] - Prediction of Corneal Condition After Corneal Ring Implantation in Keratoconus Patients
Background: Keratoconus is a common complication among corneal defects. As a result of expeditious and extensive progress of medical science in recent decades, corneal ring implantation has turned into a successful surgical procedure to correct the vision of Keratoconus patients; however, selecting the right patient is essential in the success of the operation. The prediction of corneal conditi...
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