Sharif Digital Repository

Surface electromyogram (sEMG) signals are extensively used for rehabilitation and control purposes. However due to their intrinsic complexities and intense sensor crosstalk, feature classification and pattern recognition of sEMG signals especially for motion analysis are quite challenging. This study proposes a versatile sEMG Artificial Neural Network based regression approach to evaluate a simple elbow motion with respect to a reference frame. The proposed approach attempts to appropriately interpolate intermediate position angles in an attempt to evaluate and substantiate a continuous motion of the forearm. Results show that based on the proposed algorithm, with a correlation of about 91%... 

In this work, a series of solvent- and water-injection scenarios were conducted on horizontal five-spot glass micromodels that were saturated initially with heavy oil. Sandstone and limestone rock look-alike and network patterns with different pore structures were used in the experiments. The results show that the ultimate oil recovery of a water-alternating-solvent (WAS) scheme was greater than that of a simultaneously water-alternating-solvent (SWAS) scheme, and the efficiency of a solvent-soak scheme also offers a greater recovery. Likewise, the WAS scheme resulted in greater oil recovery when compared with continuous solvent injection (CSI), with the same amount of solvent consumption.... 

Tourism is one of the largest sources of economic revenue for many countries around the world. The historical and cultural treasures of Iran made it one the main destinations for international tourists. One of the biggest problems encountered by the tourists during the visit to monuments of Iran is the lack of information about the visited landmark. Given that cameras can be found in all of the smart phones, the use of the landmark's photos can be very important for obtaining information about the tourism sites. The detection of the landmarks in an image taken by the mobile phone camera can be a very complex task depending on the angle and the light situation in which the photo is taken. In... 

The process of scanning the events occurring in a computer system or network and analyzing them for warning of intrusions is known as intrusion detection system (IDS). This paper presents a new intrusion detection system based on tabu search based fuzzy system. Here, we use tabu search algorithm to effectively explore and exploit the large state space associated with intrusion detection as a complicated classification problem. Experiments were performed on KDD-Cup99 data set which has information about intrusive and normal behaviors on computer networks. Results show that the proposed method obtains notable accuracy and lower cost in comparison with several renowned algorithms  

A novel very light weight approach to isolated word speech recognition is introduced. The approach uses a new simplistic feature set and a neural network recognition system. The algorithm's main processing requirements are FFT computation and a simple neural network comparison, making the method a suitable solution for low price embedded devices. The proposed method is tested on single speaker and multiple speaker test sets and the results are compared with a widely used speech recognition approach, presenting very fast recognition and quite good recognition rate. © 2006 IEEE  

A new approach for person identification based on hand geometry is presented. After preprocessing hand features are extracted from a photograph taken while user has placed his/her hand (either left or right) on the platform of a document scanner with no limits or fixation. Different pattern recognition techniques like Gaussian mixture modeling (GMM), Radial basis function neural networks (RBF), Multi layer perceptron (MLP), k-Nearest Neighbor (k-NN), Bayes method and mahalanobis/Hamming distance have been used in classification section. Experimental results show a rate of success above 90%. © 2005 IEEE  

Gravity drainage is the main production mechanism in the gas invaded zone in naturally fractured reservoirs. However, there are large ambiguities and complexities, resulting from the dynamic of oil depletion from matrix blocks toward the fracture network. Visualization of drained oil at pore scale using glass micromodels provides the opportunity to better understand the effects of different parameters which might affect oil recovery from fractured reservoirs. In this work a micromodel apparatus generated by laser etching is used to perform some gravity drainage tests on the network patterns. The experiments were performed on double block systems using crude oil. The block to block... 

Early diagnosis of lung cancer is very important in improving patients life expectancies. Due to the high number of Computed Tomography (CT) images, fast and accurate diagnosis is difficult for radiologists. Therefore, there is an increasing demand for Computer-Aid Diagnosis (CAD) lung cancer. The core of all lung cancer detection systems is the distinction between cancer and non-cancerous tissues. This operation is performed in the false positive reduction phase, which is one of the most critical part of the lung cancer detection systems. The primary objective of this paper is to present a new method based on 3D Convolutional Neural Networks (CNN) that can reduce the false positives rate... 

In the past decade, making the cities green and environmentally friendly is becoming a major issue for many countries around the world. The green city is an urban environment in which the parklands and natural habitats are integrated into the living and the working space of the communities. This significant increase in the scale of parklands in the green cities requires autonomous landscaping. In this paper, a computer vision system for an autonomous landscaping robot which is capable of seeding various types of grass and designing patterns in the lawns is developed. The proposed robotic platform uses deep convolutional neural networks for finding the required patches for the replanting of... 

Vaccines require a period of at least three months for clinical trials, hence a method that can identify elicitation of immune response a few days after the first dose is a necessity. Evolutionary variable selections are modeling approaches for proper manipulation of available data which were used to set up an animal model for classification of time dependent 'HNMR metabolomic profiles and pattern recognition of fluctuations of metabolites in two groups of male rabbits. One group of rabbits was immunized with human red blood cells and the other used as control. Blood was obtained every 48 h from each rabbit for a period of six weeks and the serum monitored for antibodies and metabolites by... 

In order to safe design and optimize performance of some industrial systems, it's often needed to categorize two-phase flow into different regimes. In each flow regime, flow conditions have similar geometric and hydrodynamic characteristics. Traditionally, flow regime identification was carried out by flow visualization or instrumental indicators. In this research3 kind of neural networks have been used to predict system characteristic and flow regime, and results of them were compared: radial basis function neural networks, self organized and Multilayer perceptrons (supervised) neural networks. The data bank contains experimental pressure signalfor a wide range of operational conditions in... 

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then... 

Pavement performance models are key components of any pavement management system (PMS). These models are used in a network-level PMS to predict future performance of a pavement section and identify the maintenance and rehabilitation needs. They are also used to estimate the network conditions after the application of various maintenance and rehabilitation alternatives and to determine the relative cost effectiveness of each maintenance and rehabilitation alternative. Change in pavement surface roughness over time is one of the most important performance indicators in this regard. A model for changes in the international roughness index (IRI) over time was developed through artificial neural... 

Topology control algorithms in mobile ad-hoc networks aim to reduce the power consumption while keeping the topology connected. These algorithms can preserve network resources and increase network capacity. However, few efforts have focused on the issue of topology control in presence of node mobility. One of the notable mobility aware topology control protocols is the "Mobility Aware Distributed Topology Control Protocol". The main drawback of this protocol is on its mobility prediction method. This prediction method assumes linear movements and is unable to cope with sudden changes in the mobile node movements. In this paper, we propose a pattern matching based mobility prediction method...