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The smoothness of the graph signals on predefined/constructed graphs appears in many natural applications of processing unstructured (i.e., graph-based) data. In the case of latent sources being smooth graph signals, blind source separation (BSS) quality can be significantly improved by exploiting graph signal smoothness along with the classic measures of statistical independence. In this paper, we propose a BSS method benefiting from the minimization of mutual information as a well-known independence criterion and also graph signal smoothness term of the estimated latent sources, and show that its performance is superior and fairly robust to the state-of-the-art classic and Graph Signal... 

In the nascent and challenging problem of the blind separation of the sources (BSS) supported by graphs, i.e., graph signals, along with the statistical independence of the sources, additional dependency information can be interpreted from their graph structure. To the best of our knowledge, in these cases, only GraDe and GraphJADE methods have been proposed to exploit the graph dependencies and/or Graph Signal Processing (GSP) techniques to improve the separation quality. Despite the significant advantages of these graph-based methods, they assume that the underlying graphs are known, which is a serious drawback, especially in many real-world applications. To address this issue, in this... 

The smoothness of graph signals has found desirable real applications for processing irregular (graph-based) signals. When the latent sources of the mixtures provided to us as observations are smooth graph signals, it is more efficient to use graph signal smoothness terms along with the classic independence criteria in Blind Source Separation (BSS) approaches. In the case of underlying graphs being known, Graph Signal Processing (GSP) provides valuable tools; however, in many real applications, these graphs can not be well-defined a priori and need to be learned from data. In this paper, a GSP-based approach for joint Graph Learning (GL) and BSS of smooth graph signal sources is proposed,... 

Graph Learning (GL) is at the core of leveraging connections in machine learning (ML). By observing a dataset of graph signals and considering specific assumptions, Graph Signal Processing (GSP) provides practical constraints in GL. Inferring a graph with desired frequency signatures, i.e., spectral templates, from stationary graph signals has gained great attention. However, a severe computational burden is a challenging barrier, especially for inference from high-dimensional product graph signals, i.e., graph signals live on the product of smaller factor graphs. Few product GLmethods have been proposed formostly inference with smoothness assumption, while they are limited to learning only... 

When our sources are graph signals, a more efficient algorithm for Blind Source Separation (BSS) can be provided by using structural graph information along with statistical independence and/or non-Gaussianity. To the best of our knowledge, the GraphJADE and GraDe algorithms are the only BSS methods addressing this issue in the case of known underlying graphs. However, in many real-world applications, these graphs are not necessarily a priori known. In this paper, we propose a method called GraphJADE-GL (GraphJADE with Graph Learning) that jointly separates the graph signal sources and learns the graphs related to them accurately, in an alternating style. © 1994-2012 IEEE  

The classification of sleep stages plays a crucial role in understanding and diagnosing sleep pathophysiology. Sleep stage scoring relies heavily on visual inspection by an expert, which is a time-consuming and subjective procedure. Recently, deep learning neural network approaches have been leveraged to develop a generalized automated sleep staging and account for shifts in distributions that may be caused by inherent inter/intra-subject variability, heterogeneity across datasets, and different recording environments. However, these networks (mostly) ignore the connections among brain regions and disregard modeling the connections between temporally adjacent sleep epochs. To address these... 

Manual inspection of Electroencephalography (EEG) signals to detect epileptic seizures is time-consuming and prone to inter-rater variability. Moreover, EEG signals are contaminated with different noise sources, e.g., patient movement during seizures, making the accurate identification of seizure activities challenging. In a Multi-View seizure detection system, since seizures do not uniformly affect the brain, some views likely play a more significant role in detecting seizures and should therefore be assigned a higher weight in the concatenation step. To address this dynamic weight assignment issue and also create a more interpretable model, in this work, we propose a fusion attentive deep... 

A novel intelligent semi-active control system for an eleven degrees of freedom passenger car's suspension system using magnetorheological (MR) damper with neuro-fuzzy (NF) control strategy to enhance desired suspension performance is proposed. In comparison with earlier studies, an improvement in problem modeling is made. The proposed method consists of two parts: a fuzzy control strategy to establish an efficient controller to improve ride comfort and road handling (RCH) and an inverse mapping model to estimate the force needed for a semi-active damper. The fuzzy logic rules are extracted based on Sugeno inference engine. The inverse mapping model is based on an artificial neural network... 

Using CNG as an additive for gasoline is a proper choice due to higher octane number of CNG enriched gasoline with respect to that of gasoline. As a result, it is possible to use gasoline with lower octane number in the engine. This would also mean the increase of compression ratio in SI engines resulting in higher performance and lower gasoline consumption. Over the years, the use of simulation codes to model the thermodynamic cycle of an internal combustion engine have developed tools for more efficient engine designs and fuel combustion. In this study, a thermodynamic cycle simulation of a conventional four-stroke spark-ignition engine has been developed. The model is used to study the... 

With the declining energy resources and increase of pollutant emissions, a great deal of efforts has been focused on the development of alternatives for fossil fuels. One of the promising alternative fuels to gasoline in the internal combustion engine is natural gas [1-5]. The application of natural gas in current internal combustion engines is realistic due to its many benefits. The higher thermal efficiency due to the higher octane value and lower exhaust emissions including CO2 as a result of the lower carbon to hydrogen ratio of the fuel are the two important feature of using CNG as an alternative fuel. It is well known that computer simulation codes are valuable economically as a cost... 

Gaining insight into possible vibratory responses of dynamical systems around their stable equilibria is an essential step, which must be taken before their design and application. The results of such a study can significantly help prevent instability in closed-loop stabilized systems by avoiding the excitation of the system in the neighborhood of its resonance. This paper investigates nonlinear oscillations of a rotary inverted pendulum (RIP) with a full-state feedback controller. Lagrange’s equations are employed to derive an accurate 2-DoF mathematical model, whose parameter values are extracted by both the measurement and 3D modeling of the real system components. Although the governing... 

A suction-controlled ring device has been developed to continuously measure the coefficient of lateral soil pressure in deformable unsaturated soil samples from the at-rest to the active condition under application of increasing vertical pressure and controlled matric suction. The device incorporates a thin aluminum specimen ring equipped with horizontal strain gages for recording the lateral soil strains. In addition, a sensor recording water volume changes is utilized to continuously monitor the degree of saturation of the soil sample during tests. The matric suction within the soil texture is controlled using the axis translation technique. In order to verify the performance of the ring... 

We introduce a new smooth, non-toxic, biocompatible method for cross-linking of gum tragacanth (GT), a polysaccharide of natural origin, in order to serve as a new supporting matrix for immobilization systems. The modified gum is used as a matrix for the catalysis of the conversion of benzyl penicillin to 6-aminopenicillanic acid (6-APA) by means of Escherichia coli ATCC11105 with penicillin G acylase (PGA) activity. The results show that GT beads can not only serve as a proper matrix for immobilization, but show enhanced hydrolysis rate and stability compared to other immobilization systems used for this reaction. This signifies the potential of GT as a biocompatible matrix for... 

The Class-E power amplifier has been widely studied and formulated in the literature. Although the majority of reported inductive coupling wireless power transfer (WPT) systems use a class-E power amplifier for driving the primary coil, still there is a lack of a comprehensive study on class-E circuit dedicated to WPT, providing a set of closed form design equations for proper class-E operation. This paper presents the required design equations needed to design a 'true' class-E circuit for WPT applications. Equations for the series-tuned secondary coil WPT system are presented, as well as two different design procedures for the parallel-tuned secondary coil. The derived equations have been... 

Pole Side Impact Tes is one out of three crash tests described by Euro NCAP standard for star rating of a vehicle and is required for assessing the Adult Occupant Protection. In this paper the goal is to determine the crashworthiness of side doors and B pillar in a Pole Side Impact Test based on Euro New Car Assessment Program (Euro-NCAP) using computer and simulation method. In this matter, a vehicle model has been prepared and meshed using Hypermesh and CATIA. The velocity of 29 km/h has been assigned to the vehicle which was on top of a cart while the pole has been assigned as a rigid static object based on Euro NCAP requirements specifically. Results show that different amounts of energy... 

To assess a car under the Euro New Car Assessment Program (Euro-NCAP), Adult Occupant Protection is one out of three parameters which need to be calculated with a weight factor of 50% while the other parameters, Child Occupant Protection and Pedestrian Occupant Protection, have a weight factor of 20%. The Pole Side Impact Test, beside two other tests, Side and Front Impact, is also required to calculate the Adult Occupant Protection. It shows how important the Pole Side Impact Test is and what an effective role it has in the car rating assessment. In this paper, the objective is to evaluate the effect of thickness on the energy absorbed by the side doors and the B pillar and its... 

In Euro NCAP standard, adult protection is one of the most important rating scores with 50% weight factor while child protection and pedestrian protection are accounted into consideration with 20% weight factor. For adult protection testing, three tests are required to perform: (1) side impact, (2) pole impact, (3) front impact. In the side impact test, dummy's head, chest, shoulder, thorax, ribs, abdomen, pelvic and femur must be studied to evaluate the rating score. Crashworthiness of a car during side impact can describe the score rated for that car. In this paper the goal is to determine the crashworthiness of side doors and B-pillar in side impact crash est by simulation using LS DYNA... 

In side impact test which is one out of three tests of Euro NCAP standard, front and rear doors and B pillar are most absorbance parts among vehicle body parts. Passengers are highly in danger while side crash, because of the distance between passenger's head and vehicle body. In this paper effect of material and thickness of doors and B-pillar and their absorbed energy during crash and improvement of its crashworthiness with respect to light weight design are studied using LS DYNA solver. The objective of this paper is to propose a material for doors and B-pillar with a specified thickness to achieve maximum absorbed energy and minimum weight. The shape of the doors and B-pillar remains... 

In this study, the influence of CO2 and CH4 on the performance and selectivity of Co-Ru/Al2O3 catalyst is investigated by injection of these gases (0-20 vol.% of feed) to the feed stream. The effect of temperature and feed flow rate are also inspected. The results show that low amounts of CO2 in the feed stream do not change the catalyst activity, but increasing the amount of CO2 (more than 10 vol.%), causes the CO conversion to decrease and the selectivity of heavy components to increase. Methane acts as an inert gas and does not affect the catalyst performance. Increasing feed flow rate has a negative effect on both CO conversion and heavy component selectivity. By raising the temperature,... 

In this paper, we present a nano-quantum photonic approach for the calculation of normal dispersion phenomena in organic crystals such as N-(4-nitrophenyl)-L-prolinol(NPP). We assume that a laser beam consists of a flow of energetic particles that interact with the distorted π-electron system. We approximate the distorted π-electron cloud by an ellipse to simplify calculations. By the precise analysis of photon interaction with the π-electron system of benzene ring in the NPP crystal, we obtain the refractive index in any wavelength by Monte Carlo simulation. The maximum error between our simulation results and the measurement data is 0.058, which is agreeable. © 2007 IOP Publishing Ltd