Predicting the spontaneous termination of atrial fibrillation based on poincare section in the electrocardiogram phase space

Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia. Predicting the conditions under which AF terminates spontaneously is an important task that would bring great benefit to both patients and clinicians. In this study, a new method was proposed to predict spontaneous AF termination by employing the points of section (POS) coordinates along a Poincare section in the electrocardiogram (ECG) phase space. The AF Termination Database provided by PhysioNet for the Computers in Cardiology Challenge 2004 was applied in the present study. It includes one training dataset and two testing datasets, A and B. The present investigation was initiated by producing a two-dimensional reconstructed phase space (RPS) of the ECG. Then, a Poincare line was drawn in a direction that included the maximum point distribution in the RPS and also passed through the origin of the RPS coordinate system. Afterward, the coordinates of the RPS trajectory intersections with this Poincare line were extracted to capture the local behavior related to the arrhythmia under investigation. The POS corresponding to atrial activity were selected with regard to the fact that similar ECG morphologies such as P waves, which are corresponding to atrial activity, distribute in a specific region of the RPS. Thirteen features were extracted from the selected intersection points to quantify their distributions. To select the best feature subset, a genetic algorithm (GA), in combination with a support vector machine (SVM), was applied to the training dataset. Based on the selected features and trained SVM, the performance of the proposed method was evaluated using the testing datasets. The results showed that 86.67% of dataset A and 80% of dataset B were correctly classified. This classification accuracy is in the same range as or higher than that of recent studies in this area. These results show that the proposed method, in which no complicated QRST cancelation algorithm was used, has the potential to predict AF termination.     

Efficient and robust three‐phase split computations

The combination of successive substitution and the Newton method provides a robust and efficient algorithm to solve the nonlinear isofugacity and mass balance equations for two‐phase split computations. The two‐phase Rachford–Rice equation may sometimes introduce complexity, but the Newton and bisection methods provide a robust solution algorithm. For three‐phase split calculations, the literature shows that the computed three‐phase region is smaller than measured data indicate. We suggest that an improved solution algorithm for the three‐phase Rachford–Rice equations can address the problem. Our proposal is to use a two‐dimensional bisection method to provide good initial guesses for the Newton algorithm used to solve the three‐phase Rachford–Rice equations. In this work, we present examples of various degree of complexity to demonstrate powerful features of the combined bisection‐Newton method in three‐phase split calculations. To the best of our knowledge, the use of the bisection method in two variables has not been used to solve the three‐phase Rachford–Rice equations in the past. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

A new thermodynamic function for phase‐splitting at constant temperature,moles, and volume

We introduce a new thermodynamic function for phase‐split computations at constant temperature, moles, and volume. The new volume function F_i introduced in this work is a natural choice under these conditions. Phase equilibrium conditions in terms of the volume functions are derived using the Helmholtz free energy. We present a numerical algorithm to investigate two‐phase equilibrium based on the fixed point iteration and Newton method. We demonstrate usefulness and powerful features of the new thermodynamic function for a number of examples in two‐phase equilibrium calculations. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Modeling of multicomponent diffusions and natural convection in unfractured and fractured media by discontinuous Galerkin and mixed methods

Computation of the distribution of species in hydrocarbon reservoirs from diffusions (thermal, molecular, and pressure) and natural convection is an important step in reservoir initialization. Current methods, which are mainly based on the conventional finite‐difference approach, may not be numerically efficient in fractured and other media with complex heterogeneities. In this work, the discontinuous Galerkin (DG) method combined with the mixed finite element (MFE) method is used for the calculation of compositional variation in fractured hydrocarbon reservoirs. The use of unstructured gridding allows efficient computations for fractured media when the cross flow equilibrium concept is invoked. The DG method has less numerical dispersion than the upwind finite‐difference methods. The MFE method ensures continuity of fluxes at the interface of the grid elements. We also use the local DG (LDG) method instead of the MFE to calculate the diffusion fluxes. Results from several numerical examples are presented to demonstrate the efficiency, robustness, and accuracy of the model. Various features of convection and diffusion in homogeneous, layered, and fractured media are also discussed.     

Numerical simulation of nano-carbon deposition in the thermal decomposition of methane

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 additional to experimental studies, numerical simulation also shows some carbon particle deposit around and especially downstream of the reaction zone. The results indicate that the main cause of the separation of particles from the wall is the thermophoretic force, and that downstream of the reactor, where the temperature gradient has decreased, the particles are trapped on the wall under van der Waals and Brownian forces. Two methods are investigated to decrease carbon deposition on the wall. The first is to increase the wall temperature to use the thermophoretic effect, which is rejected because in addition to the increase of thermophoretic force, the probability of particle generation increases nearly 10 times. The second method is the application of a wall jet as a sweeping flow to generate a buffer gas and to decrease particle generation near the wall. This design provides good results in producing a clean reactor.     

Emotion classification during music listening from forehead biosignals

Emotion recognition systems are helpful in human–machine interactions and clinical applications. This paper investigates the feasibility of using 3-channel forehead biosignals (left temporalis, frontalis, and right temporalis channel) as informative channels for emotion recognition during music listening. Classification of four emotional states (positive valence/low arousal, positive valence/high arousal, negative valence/high arousal, and negative valence/low arousal) in arousal–valence space was performed by employing two parallel cascade-forward neural networks as arousal and valence classifiers. The inputs of the classifiers were obtained by applying a fuzzy rough model feature evaluation criterion and sequential forward floating selection algorithm. An averaged classification accuracy of 87.05 % was achieved, corresponding to average valence classification accuracy of 93.66 % and average arousal classification accuracy of 93.29 %.     

Analysis of Production Logging Data to Develop a Model to Predict Pressure Drop in Perforated Gas Condensate Wells

Abstract

Accurate prediction of pressure drop in perforated wells with a high fluid flow rate is a challenge in production engineering calculations. In this study, production logging data obtained from an Iranian gas condensate field were analyzed to develop a model to predict the pressure drop in perforated wells. To calculate the pressure drop due to the friction in the perforated section of the wall, a relation between perforation friction factor, pipe and wall Reynolds number, and Moody friction factor was developed by means of nonlinear regression. Perforation effects were also considered in total pressure drop, which occur due to the mixing of axial and radial momentum fluxes in the perforated section. The results predicted by our developed model showed good agreement with the measured production logging data from the studied field within 14% error. This model can be used to accurately estimate the well performance curve.     

Reservoir depletion calculations for gas condensates using extended analyses in the peng-robinson equation of state

The Peng-Robinson-AGA computer program was applied to the predicting of liquid yields in flash and stepwise depletion calculations. Prior tests of the validity of the program were based on agreement between bubble and dew point pressures and equilibrium constants. Here, the liquid yields under ietrograde conditions were compared with only a moderate degree of agreement. The need for accurate extended analyses of condensate systems as well as the documentation of an accurate characterization of the cuts is emphasized.