Sharif Digital Repository

Graphene oxide nanoplatelets (GONPs) with extremely sharp edges (lateral dimensions ∼20-200 nm and thicknesses <2 nm) were applied in extraction of the overexpressed guanine synthesized in the cytoplasm of leukemia cells. The blood serums containing the extracted guanine were used in differential pulse voltammetry (DPV) with reduced graphene oxide nanowall (rGONW) electrodes to develop fast and ultra-sensitive electrochemical detection of leukemia cells at leukemia fractions (LFs) of ∼10-11 (as the lower detection limit). The stability of the DPV signals obtained by oxidation of the extracted guanine on the rGONWs was studied after 20 cycles. Without the guanine extraction, the DPV peaks... 

This paper presents a new combined method for accurate upscaling of two-phase displacements in highly heterogeneous reservoirs. The method has the capability to retain its high performance for various flow regimes, from viscous to gravity dominant displacements, without the need for further modifications and computational steps. Two different grids are incorporated for simulation. The grid on fine scale is used to recognize the complicated physics of flow which depends on dominated driving forces and their interaction with heterogeneity. However, to achieve a fast simulation, the global flow calculation is performed on the coarse scale grid using upscaled equivalent properties. The... 

The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance... 

Intrusion Detection Systems (IDS) for Mobile Ad hoc NETworks (MANETs) are necessary when they are deployed in reality. In This paper, we have presented a combined method of selecting IDS agent nodes in mobile ad hoc networks. Since, the IDS agents in MANET due to more activities need to more battery power. In our method, first, compromised nodes are detected and then the nodes with the highest energy power from among valid nodes as IDS agent nodes are considered. So, with this method, some valid nodes contribute in intrusion detection activities and costs of the network monitoring will be reduced and the network lifetime will be increased. © 2009 IEEE  

We develop a heuristic procedure for solving the discrete time/resource trade-off problem in the field of project scheduling. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero, which require one or more constrained renewable resources. Each activity has a specified work content and can be performed in different modes, i.e. with different durations and resource requirements, as long as the required work content is met. The objective is to schedule each activity in one of its modes in order to minimize the project makespan. We use a scatter search algorithm to tackle this problem, using path relinking methodology as... 

For processes that repeat the same task an iterative control method can be applied that learns from the previous runs and corrects the tracking error for the next run. Meanwhile, a set membership identification technique is be combined with the regulation part to identify the plant response using the informative input-output data of previous observations. This combination method has been experimentally tested on a radio frequency machine and the results are presented in the paper. © 2019 EUCA  

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... 

Next generation wideband and ultra-wideband radar antenna arrays need efficient true-time delay networks for array control. Optical beam-forming networks have been considered as a promising solution in such arrays. Performance analysis of optical beam-formers is thus quiet necessary. In this paper signal to noise ratio and dynamic range of simple optical beam-forming structures are investigated with a custom microwave CAD tool. Two structures with optical and RF power combining methods are discussed. With the proposed devices' parameters, the optical combining method shows better performance for low and moderate optical powers  

We consider a combined time-hopping (TH) and spread-time (ST) multiple-access technique that uses an internal code. In this method, the duration of each bit is divided into Ns frames. The outputs of the encoder and a pseudorandom (PN) sequence specify the number of the frame in which the data bit is transmitted in ST code-division multiple-access (ST-CDMA) form using the second PN sequence. We consider the correlator receiver, followed by the channel decoder. We obtain the performance of the combined method in additive white Gaussian noise (AWGN) and fading channels in the presence of multiple-access interference (MAI) and narrowband interference (NBI). We also consider the conventional... 

In this paper we study the effectiveness of using multiple classifier combination for EEG signal classification aiming to obtain more accurate results than it possible from each of the constituent classifiers. The developed system employs two linear classifiers (SVM,LDA) fused at the abstract and measurement levels for integrating information to reach a collective decision. For making decision, the majority voting scheme has been used. While at the measurement level, two types of combination methods have been investigated: one used fixed combination rules that don't require prior training and a trainable combination method. For the second type, the fuzzy integral method was used. The...