Sharif Digital Repository

A comparison of various hydrogen production processes indicates that the thermal decomposition of methane (TDM) provides an attractive option from both economical and technical points of view. The main problem for this process is the deposition of the nano-carbon particles on the reactor wall (or catalyst surface). This research concentrates on the numerical simulation of the TDM process without use of a catalyst to find a technique that decreases the carbon accumulation in a tubular reactor. In this model, the produced carbon particles are tracked with the Lagrangian method under thermophoretic, Brownian, van der Waals, Basset, drag, lift, gravity, pressure and virtual mass forces. In... 

In this paper, an iterative signal reconstruction method is extended to cancel multi-user clipping noise in a uplink MC-CDMA systems. Clipping is the simplest method to overcome high peak-to-average power ratio of multi-carrier signals but it makes the multi-carrier signals distorted. Reconstruction methods use non-distorted samples to reconstruct distorted samples in the receiver but multi-user interference causes the methods do not work properly because all the received samples are distorted by clipping and interference and so there is no undistorted samples to be used in recovering clipped samples. On the other hand, multi-user interference cancellation methods do not work properly... 

In recent years, the demand for video transmission over wireless communication networks is growing very fast. The H.264 video compression standard which offers high quality at low bit rates, is a suitable codec for applications that require efficient video transmission over wireless networks. While the compressed videos are transmitted through error-prone networks, error robustness becomes an important issue. In this paper, a joint source-channel Lagrange optimization method in which the distortion of the decoder is estimated without using feedback which can be used for both multicast and point-to-point applications is proposed. The experimental results show that the new algorithm has a good... 

This paper discusses the application of unified power quality conditioner (UPQC) for improving power quality of a system supplying an electric arc furnace (EAF). The UPQC includes combined series and shunt active filters sharing a common DC link. It is used to mitigate voltage disturbances and compensate for reactive power, harmonics and interharmonics. A novel control strategy for the UPQC is presented. As voltages at the point of common coupling contain low-frequency interharmonics, conventional methods cannot be used for extracting voltage reference signals. In the proposed method, voltage references are extracted using a phase-locked loop to generate sinusoidal waveforms. Current... 

In this paper, a neural network based implementation of space vector modulation (SVM) of a two-level voltage fed Inverter is proposed. This network has the advantage of very fast implementation of SVM algorithm, particularly when a dedicated application- specific IC chip is used Instead of a digital signal processor (DSP). The proposed neural network consists of several subnets, a counter and a logic circuit. Subnets are used to Implement the stages of SVM algorithm while the counter is used to apply the switching state vectors in their specified times to Inverter. The logic circuit generates the Inverter switches commands according to the outputs of the subnets. The scheme has been... 

H.264/AVC, the latest video coding standard, achieves better video compression rates since it supports new features such as a large number of intra- and inter-prediction candidate modes. H.264/AVC adopts rate-distortion optimization (RDO) technique to obtain the best intra- and inter-prediction, while maximizing visual quality and minimizing the required bit rate. However, the RDO reduces the encoding speed via the exhaustive evaluation of all candidate modes. In this paper, we decrease the encoding time by reducing the computational complexity of the prediction function and the number of candidate modes. First, we improve Pan's method, by eliminating the DC mode from the candidates. Second,... 

In this article, we examine Independent Component Analysis (ICA) and the concept of Mutual information (MI) as a quantitative measure of independence from the point of view of analytical chemistry. We compare results obtained by different ICA methods with results obtained by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). These results have shown that, when non-negativity constraints are applied, values of MI increase considerably and the resolved components cannot anymore be considered to be independent (i.e. they can only be considered to be the " least dependent" components). MI values of profiles resolved by MCR-ALS and ICA did not differ significantly when... 

Goal: Continuous blood pressure (BP) monitoring can provide invaluable information about individuals' health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This paper presents an efficient algorithm, based on the pulse arrival time (PAT), for the continuous and cuffless estimation of the systolic BP, diastolic blood pressure (DBP), and mean arterial pressure (MAP) values. Methods: The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally,... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main... 

Electromyogram (EMG) signal is an electrical manifestation of muscle contractions. EMG signal collected from surface of the skin, a non-invasive bioelectric signal, can be used in different rehabilitation applications and artificial extremities control. This study has proposed to utilize the surface EMG (SEMG) signal to recognize patterns of hand prosthesis movements. It suggests using an adaptive neuro-fuzzy inference system (ANFIS) to identify motion commands for the control of a prosthetic hand. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP) and least mean square (LMS) is utilized. Also in order to optimize the number of fuzzy rules, a... 

A problem associated with modeling and control of the power factor correction rectifiers is that the ac variations in duty cycle, as well as in the ac input voltage and current are not small, and hence the traditional small signal analysis is not justified. Nonetheless, the low-frequency components of the converter can be modeled via the circuit averaging technique, but the resulting equivalent circuits are, in general, time varying and highly nonlinear. Nonlinear stability analysis methods are not appropriate for analysis and control design of such complicated circuits. In this paper a piecewise affine approximation is introduced for modeling of switching circuits. This approach makes the... 

Background: Electromyography (EMG) is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG) can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided... 

Acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also called COVID-19, is one of the most contagious viruses resulting in a progressive pandemic. Since specific antiviral treatments have not been developed yet and its fatal rate is almost high, early and fast detection is critical for controlling the outbreak. In this study, a piezoelectric microcantilever biosensor has been designed for detecting COVID-19 samples directly without requiring preparation steps. The biosensor acts as a transducer and is coated with the related antibody. When the SARS-CoV-2 antigens adsorbed on the microcantilever top surface through their spike proteins, a surface stress due to the mass change would be... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,...