Sharif Digital Repository

In this paper, a method for apnea bradycardia detection in preterm infants is presented based on coupled hidden semi Markov model (CHSMM). CHSMM is a generalization of hidden Markov models (HMM) used for modeling mutual interactions among different observations of a stochastic process through using finite number of hidden states with corresponding resting time. We introduce a new set of equations for CHSMM to be integrated in a detection algorithm. The detection algorithm was evaluated on a simulated data to detect a specific dynamic and on a clinical dataset of electrocardiogram signals collected from preterm infants for early detection of apnea bradycardia episodes. For simulated data, the... 

Apnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For... 

In this paper, we present a novel framework for the coupled hidden Markov model (CHMM), based on the forward and backward recursions and conditional probabilities, given a multidimensional observation. In the proposed framework, the interdependencies of states networks are modeled with Markovian-like transition laws that influence the evolution of hidden states in all channels. Moreover, an offline inference approach by maximum likelihood estimation is proposed for the learning procedure of model parameters. To evaluate its performance, we first apply the CHMM model to classify and detect disturbances using synthetic data generated by the FitzHugh-Nagumo model. The average sensitivity and... 

In this article, a multiscale modeling procedure is implemented to study the effect of interphase on the Young's modulus of CNT/polymer composites. For this purpose, a three-phase RVE is introduced which consists of three components, i.e., a carbon nanotube, an interphase layer, and an outer polymer matrix. The nanotube is modeled at the atomistic scale using molecular structural mechanics. Moreover, three-dimensional elements are employed to model the interphase layer and polymer matrix. The nanotube and polymer matrix are assumed to be bonded by van der Waals interactions based on the Lennard-Jones potential at the interface. Using this Molecular Structural Mechanics/Finite Element... 

In this article, a Molecular Structural Mechanics/Finite Element (MSM/FE) multiscale modeling of carbon nanotube/polymer composites with viscoelastic (VE) polymer matrix is introduced. The nanotube is modeled at the atomistic scale using structural molecular mechanics. The matrix deformation is analyzed by nonlinear finite element method considering VE behavior. The nanotube and matrix are assumed to be bonded by van der Waals interactions based on the Lennard-Jones potential at the interface. Using the MSM/FE multiscale model, we investigate the effect of carbon nanotube (CNT) on the improvement of mechanical stability of the nanocomposite. Also, the buckling behavior of these... 

Carbon nanotube (CNT)-reinforced polymer composites have attracted great attention due to their exceptionally high strength. Their high strength can be affected by the presence of defects in the nanotubes used as reinforcements in practical nanocomposites. In this article, a new three-phase molecular structural mechanics/finite element (MSM/FE) multiscale model is used to study the effect of CNT vacancy defects on the stability of single-wall (SW) CNT-polymer composites. The nanotube is modeled at the atomistic scale using MSM, whereas the interphase layer and polymer matrix are analyzed by the FE method. The nanotube and polymer matrix are assumed to be bonded by van der Waals interactions... 

CNT-reinforced polymer composites have attracted attention due to their exceptional high strength. The high strength can be affected by the presence of defects in the nanotubes used as reinforcements in the practical nanocomposites. In this paper, a Molecular Structural Mechanics / Finite Element (MSM/FE) multiscale modeling is used to study the effect of carbon nanotube geometrical defects on the stability of SWCNT-polymer composites. Here, two types of representative volume elements (RVEs) for these nanocomposites are considered with perfect and defected CNT. These RVEs have the same dimensions. The nanotube is modeled at the atomistic scale using molecular structural mechanics whereas the... 

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called “switch” is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and... 

Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

The graphitic carbon nitride/tin oxide (g-C3N4/SnO2) nanocomposite synthesized under microwave irradiation was used for adsorptive removal of sulfur-containing dibenzothiophene (DBT) from Tehran vehicular gasoline. High-resolution transmission electron microscopy, X-ray powder diffraction, energy dispersive X-ray spectroscopy, Brunauer-Emmett-Teller, Fourier-transform infrared spectroscopy, and field emission scanning electron microscopy techniques determined the adsorbent characteristics, and gas chromatography with a flame ionization detector determined the DBT concentration of the samples. Application of the experimental data into the solid/fluid kinetic models indicated a chemisorption... 

This paper presents the fuzzy logic computing for the design and implementation of fuel controller for gas turbine engines. For this purpose, a fuzz controller is designed in order to be implemented on an electronic control unit where it is used to drive a servo operated fuel control valve. The fuzzy logic computing approach for different parts of the controller including fuzzification, rule base, inference engine and defuzzification are then described. Finally, computer simulation of the fuzzy controllers integrated with the engine model is performed to investigate the effectiveness of the proposed fuzzy controller on the performance of a turbojet engine. The results are provided to show... 

Neural activity is very important source for data mining and can be used as a control signal for brain-computer interfaces (BCIs). Particularly, Magnetic signals of neurons are enriched with information about the movement of different part of the body such as wrist movement. In this paper, we use MEG (Magneto encephalography) signals of two subjects recorded during wrist movement task in four directions. Data were prepared for BCI competition 2008 for multiclass classification. Our approach for this classification problem consists of PCA as a noise reduction method, ULDA for feature reduction and various linear classifiers such as Bayesian, KNN and SVM. Final results (58%-62% for subject 1... 

Cascaded split-source inverter (CSSI) is a new single-stage modular multilevel topology. Each cell of this converter converts dc to ac power in the buck or boost operation mode without any additional power switch. This article develops a design method based on a detailed model for CSSI. This model shows that energy storage elements experience double-fundamental frequency ripples besides high-frequency ones. It accurately calculates voltage gains and capacitor voltage and inductor current ripples. On the other hand, common carrier-based multilevel modulations have been modified in terms of both reference and carrier signals to control the inverter under symmetric and asymmetric conditions....