An efficient current-based logic cell model for crosstalk delay analysis

Logic cell modelling is an important component in the analysis and design of CMOS integrated circuits, mostly due to nonlinear behaviour of CMOS cells with respect to the voltage signal at their input and output pins. A current-based model for CMOS logic cells is presented, which can be used for effective crosstalk noise and delta delay analysis in CMOS VLSI circuits. Existing current source models are expensive and need a new set of Spice-based characterisation, which is not compatible with typical EDA tools. In this article we present Imodel, a simple nonlinear logic cell model that can be derived from the typical cell libraries such as NLDM, with accuracy much higher than NLDM-based cell delay models. In fact, our experiments show an average error of 3% compared to Spice. This level of accuracy comes with a maximum runtime penalty of 19% compared to NLDM-based cell delay models on medium-sized industrial designs.     

Miniaturized integrated antennas for far-field wireless powering

This paper describes a series of high-efficiency miniaturized antennas of different sizes that can be integrated with the same wireless-powered RFID chip. Since this RFID chip has power scavenging capability in different ISM bands, several integrated on-chip and off-chip antennas in the three ISM bands of 900 MHz, 2.4 GHz and 5.8 GHz are designed, including one antenna integrated on chip. All proposed antennas are derived from a new planar antenna structure which can be designed toward arbitrary input impedance within a given area constraint. The measurement results for the presented antennas show a different read range. The resulting read range versus antenna size diagram specifies the best operating frequency band for a given read range and occupied area. Though this diagram depends on the chip's specifications like the power-on sensitivity and input impedance, it can be generated for any chip. In addition, the measurement results concerning read range and radiation patterns for the proposed antennas are presented and compared with simulation results, showing very good agreement.     

Calcified right ventricular fibroma causing outflow obstruction. Report of a case with successful excision

A 5-year-old boy with clinical findings of pulmonic stenosis was found to have a large calcified mass in the right ventricular outflow region and a gradient of 120 mm Hg between the right ventricle and the pulmonary artery. At surgery, an ovalshaped tumor attached to the interventricular septum and obstructing the right ventricular outflow tract was removed. The child survived and is doing well. Histologically, the tumor had the characteristics of fibroma. A hemodynamic study three months after surgery showed almost complete abolishment of the gradient. To our knowledge this is the fifth reported case of calcified right ventricular fibroma with successful operation. In childhood intracardiac calcifications, together with obstruction, are highly suggestive of this lesion.     

Modelling carbon dioxide solubility in ionic liquids

Solubility information for CO₂ in different ionic liquids, ILs, in part can potentially be used to select a specific IL for the separation of CO₂ from hydrocarbon fluids. Unfortunately, not all CO₂–IL systems have been experimentally described at similar temperatures and pressures; therefore, a direct comparison of performance by process simulation is not always possible. In the extreme cases, the design of a CO₂ separation process may require predicting the CO₂–IL equilibria for which there are no available solubility data. To address the need for this information, a semi‐empirical correlation was developed to estimate the dissolution of CO₂ in CO₂–IL solvent systems. The theoretical COSMO–RS calculation method was used to calculate the chemical potential of CO₂ in a wide variety of ILs and the Soave–Redlich–Kwong equation was used to calculate the fugacity coefficient of the CO₂ vapour phase. The model was correlated with available literature data, yielding an average error of AAR = 23% and small bias. © 2012 Canadian Society for Chemical Engineering     

Information-theoretic investigation of impact of huggable communication medium on prefrontal brain activation*

This paper examines the effect of mediated hugs that are achieved with a huggable communication medium on the brain activities of users during conversations. We measured their brain activities with functional near-infrared spectroscopy (NIRS) and evaluated them with two information theoretic measures: permutation entropy, an indicator of relaxation, and multiscale entropy, which captures complexity in brain activation at multiple time scales. We first verify the influence of lip movements on brain activities during conversation and then compare brain activities during tele-conversation through a huggable communication medium with a mobile phone. Our analysis of NIRS signals shows that mediated hugs decrease permutation entropy and increase multiscale entropy. These results suggest that touch interaction through a mediated hug induces a relaxed state in our brain but increases complex patterns of brain activation.     

A new design strategy for DC/DC LLC resonant converter: Concept,modeling, and fabrication

In this paper, a new design procedure for LLC converter has been introduced. In fact, this method is a computer-based design algorithm based on a numerical technique. In the process of designing, the value of the resonant element is obtained by solving the LLC converter fundamental equation. This converter will be controlled by using state feedback, such as output voltage variable. As a matter of fact, in a control system, the change of output voltage (because of load variation) will affect the switching frequency, so the output voltage will be tuned. In the designing process, the fundamental equations of LLC converter are obtained, and the value of the resonant elements is calculated. Also, a comparison analysis is carried out between the proposed and typical methods. The simulation is done to investigate the validity of the proposed method. Moreover, a prototype is manufactured, and the experimental test is done to evaluate its applicability.     

Fast-forward solver for inhomogeneous media using machine learning methods: artificial neural network,support vector machine and fuzzy logic

Encountering with a nonlinear second-order differential equation including ϵ _r and μ _r spatial distributions, while computing the fields inside inhomogeneous media, persuaded us to find their known distributions that give exact solutions. Similarities between random distributions of electric properties and known functions lead us to estimate them using three mathematical tools of artificial neural networks (ANNs), support vector machines (SVMs) and Fuzzy Logic (FL). Assigning known functions after fitting with minimum error to arbitrary inputs using results of machine learning networks leads to achieve an approximate solution for the field inside materials considering boundary conditions. A comparative study between the methods according to the complexity of the structures as well as the accuracy and the calculation time for testing of unforeseen inputs, including classification, prediction and regression is presented. We examined the extracted pairs of ϵ _r and μ _r with ANN, SVM networks and FL and got satisfactory outputs with detailed results. The application of the presented method in zero reflection subjects is exemplified.

     

Controller Design Based On Wavelet Neural Adaptive Proportional Plus Conventional Integral-Derivative For Bilateral Teleoperation Systems With Time-Varying Parameters

International Journal of Control, Automation and Systems - In this study, a new controller method based on wavelet neural adaptive proportional plus conventional integral-derivative (WNAP+ID)...     

Intelligent control of static synchronous series compensator via an adaptive self-tuning PID controller for suppression of torsional oscillations

In this paper, an intelligent controller is proposed to control a static synchronous series compensator (SSSC) in order to mitigate subsynchronous resonance (SSR) oscillations in a power system. This intelligent controller is an adaptive self-tuning PID controller. To train the PID controller, the gradient descent method is employed where the learning rate is adapted in every iteration in order to accelerate the speed of convergence. This control scheme also requires a wavelet neural network (WNN) to identify the controlled system dynamic. To update the parameters of WNN, the gradient descent (GD) along with the adaptive learning rates derived by the Lyapunov method is used. The computer simulations are used to show the ability of the proposed controller. In addition, the performance of the proposed controller is compared with another self-tuning PID controller. The results demonstrate that the proposed controller has a successful performance in minimizing the SSR.     

Application of homotopy analysis method to solve MHD Jeffery-Hamel flows in non-parallel walls

The MHD Jeffery-Hamel flows in non-parallel walls are investigated analytically for strongly nonlinear ordinary differential equations using homotopy analysis method (HAM). Results for velocity profiles in divergent and convergent channels are presented for various values of Hartmann and Reynolds numbers. The convergence of the obtained series solutions is explicitly studied and a proper discussion is given for the obtained results. Comparison between HAM and numerical solutions showed excellent agreement.