Accurate GTO model for circuit simulations

The GTO model presented in this paper uses analytical expressions to describe the internal physics of the device. It has been implemented to run as compiled code in the SPICE simulation package and as a MAST template in the Saber simulator. A rigorous comparison of measured simulated waveforms and performance parameters (including turn-off energies) for a 3000A device is described and discussed.

Stepped gate polysilicon thin film transistor for large area power applications

For the first time, we report a new poly-Si stepped gate Thin Film Transistor (SG TFT) on glass. The Density of States extracted from measured I-V characteristics has been used to evaluate the device performance with a two dimensional device simulator. The results show that the three-terminal SG TFT device has a switching speed comparable to a low voltage structure and the high on-current capability of a metal field plate (MFP) TFT and the potential for comparable breakdown characteristics.

Theoretical and numerical investigation of SiC JFET and MOSFET at 6.5 kV

This paper presents a preliminary theoretical and numerical investigation of 4H-SiC JFET and MOSFET at 6.5 kV. To improve the on-state/breakdown performance of the JFET, buried layers in conjunction with a highly doped buffer layer have been used. Trench technology has been employed for the MOSFET. The devices were simulated and optimized using MEDICI[I] simulator. From the comparison between the two devices, it turns out that the JFET offers a better on-state/breakdown trade-off, while the trench MOSFET has the advantage of MOS-control.

Analytical model for the 3D-RESURF effect

This paper presents an analytical model for the determination of the basic breakdown properties of three-dimensional (3D)-RESURF/CoolMOS/super junction type structures. To account for the two-dimensional (2D) effect of the 3D-RESURF action, 2D models of the electric field distribution are developed. Based on these, expressions are derived for the breakdown voltage as a function of doping concentration and physical dimensions. In addition to cases where the drift regions are fully depleted, the model developed is also applicable to situations involving drift regions which are almost depleted. Accuracy of the analytical approach is verified by comparison with numerical results obtained from the MEDICI device simulator.

Investigation of extinction in unsteady flames in turbulent combustion by 2D-LIF of OH radials and flamelet analysis

An experimental and theoretical investigation of premixed turbulent combustion in an engine simulator is presented. The distribution of hydroxyl radicals formed in the combustion of propane/air mixtures was visualized by 2D-LIF and used to monitor the progress of the combustion process. For stoichiometric mixtures, images showed a continuous wrinkled flame front, while in lean (λ=1.5) mixtures, local flame extinction was observed as discontinuities in the reaction zone. A bright active reaction zone was still observed in flame inlets and closed concave structures. The effects of self-absorption and of collisional quenching on the fluorescence signal are considered and appear to have only a minor net influence on the shape and width of the flame front. The images are evaluated and interpreted in terms of the Lewis number effect and the laminar flamelet model. Analysis was performed by determining the contour lines of the images (specifically, the ratios of average maximum to equilibrium OH concentration) and comparing with corresponding ratios from unstrained flame simulations. The results show that although the degree of turbulence is not high enough for straining effects to be important, flamelet curvature does play a significant role in the combustion of lean mixtures; this is manifested by a mean effective flame velocity that is less than the laminar burning velocity. © 1991 Combustion Institute.

Applying quality control in building energy modelling: Comparative simulation of a high performance building

Quality control is considered from the simulator's perspective through comparative simulation of an ultra energy-efficient building with EE4-DOE2.1E and EnergyPlus. The University of Calgary's Leadership in Energy and Environmental Design Platinum Child Development Centre, with a 66% certified energy cost reduction rating, was the case study building. A Natural Resources Canada incentive program required use of EE4 interface with DOE2.1E simulation engine for energy modelling. As DOE2.1E lacks specific features to simulate advanced systems such as radiant cooling in the CDC, an EnergyPlus model was developed to further evaluate these features. The EE4-DOE2.1E model was used for quality control during development of the base EnergyPlus model and simulation results were compared. Advanced energy systems then added to the EnergyPlus model generated small difference in estimated total annual energy use. The comparative simulation process helped identify the main input errors in the draft EnergyPlus model. The comparative use of less complex simulation programs is recommended for quality control when producing more complex models. © 2009 International Building Performance Simulation Association (IBPSA).

Monte Carlo optimization strategies for air-traffic control

The safety of the flights, and in particular conflict resolution for separation assurance, is one of the main tasks of Air Traffic Control. Conflict resolution requires decision making in the face of the considerable levels of uncertainty inherent in the motion of aircraft. We present a Monte Carlo framework for conflict resolution which allows one to take into account such levels of uncertainty through the use of a stochastic simulator. A simulation example inspired by current air traffic control practice illustrates the proposed conflict resolution strategy. Copyright © 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Reinforcement learning for parameter estimation in statistical spoken dialogue systems

Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estimate the parameters of a dialogue policy which selects the system's responses based on the inferred dialogue state. However, the inference of the dialogue state itself depends on a dialogue model which describes the expected behaviour of a user when interacting with the system. Ideally the parameters of this dialogue model should be also optimised to maximise the expected cumulative reward. This article presents two novel reinforcement algorithms for learning the parameters of a dialogue model. First, the Natural Belief Critic algorithm is designed to optimise the model parameters while the policy is kept fixed. This algorithm is suitable, for example, in systems using a handcrafted policy, perhaps prescribed by other design considerations. Second, the Natural Actor and Belief Critic algorithm jointly optimises both the model and the policy parameters. The algorithms are evaluated on a statistical dialogue system modelled as a Partially Observable Markov Decision Process in a tourist information domain. The evaluation is performed with a user simulator and with real users. The experiments indicate that model parameters estimated to maximise the expected reward function provide improved performance compared to the baseline handcrafted parameters. © 2011 Elsevier Ltd. All rights reserved.

Parameter estimation for agenda-based user simulation

This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhibited by real users. The train-able part is formed by a set of random decision points that may be encountered during the process of receiving a system act and responding with a user act. A sample-based method is presented for using real user data to estimate the parameters that control these decisions. Evaluation results are given both in terms of statistics of generated user behaviour and the quality of policies trained with different simulators. Compared to a handcrafted simulator, the trained system provides a much better fit to corpus data and evaluations suggest that this better fit should result in improved dialogue performance. © 2010 Association for Computational Linguistics.

On-line policy optimisation of spoken dialogue systems via live interaction with human subjects

Statistical dialogue models have required a large number of dialogues to optimise the dialogue policy, relying on the use of a simulated user. This results in a mismatch between training and live conditions, and significant development costs for the simulator thereby mitigating many of the claimed benefits of such models. Recent work on Gaussian process reinforcement learning, has shown that learning can be substantially accelerated. This paper reports on an experiment to learn a policy for a real-world task directly from human interaction using rewards provided by users. It shows that a usable policy can be learnt in just a few hundred dialogues without needing a user simulator and, using a learning strategy that reduces the risk of taking bad actions. The paper also investigates adaptation behaviour when the system continues learning for several thousand dialogues and highlights the need for robustness to noisy rewards. © 2011 IEEE.

Designing inclusive interfaces through user modeling and simulation

Elderly and disabled people can be hugely benefited through the advancement of modern electronic devices, as those can help them to engage more fully with the world. However, existing design practices often isolate elderly or disabled users by considering them as users with special needs. This article presents a simulator that can reflect problems faced by elderly and disabled users while they use computer, television, and similar electronic devices. The simulator embodies both the internal state of an application and the perceptual, cognitive, and motor processes of its user. It can help interface designers to understand, visualize, and measure the effect of impairment on interaction with an interface. Initially a brief survey of different user modeling techniques is presented, and then the existing models are classified into different categories. In the context of existing modeling approaches the work on user modeling is presented for people with a wide range of abilities. A few applications of the simulator, which shows the predictions are accurate enough to make design choices and point out the implication and limitations of the work, are also discussed. © 2012 Copyright Taylor and Francis Group, LLC.

A path-following driver-vehicle model with neuromuscular dynamics, including measured and simulated responses to a step in steering angle overlay

An existing driver-vehicle model with neuromuscular dynamics is improved in the areas of cognitive delay, intrinsic muscle dynamics and alpha-gamma co-activation. The model is used to investigate the influence of steering torque feedback and neuromuscular dynamics on the vehicle response to lateral force disturbances. When steering torque feedback is present, it is found that the longitudinal position of the lateral disturbance has a significant influence on whether the drivers reflex response reinforces or attenuates the effect of the disturbance. The response to angle and torque overlay inputs to the steering system is also investigated. The presence of the steering torque feedback reduced the disturbing effect of torque overlay and angle overlay inputs. Reflex action reduced the disturbing effect of a torque overlay input, but increased the disturbing effect of an angle overlay input. Experiments on a driving simulator showed that measured handwheel angle response to an angle overlay input was consistent with the response predicted by the model with reflex action. However, there was significant intra-and inter-subject variability. The results highlight the significance of a drivers neuromuscular dynamics in determining the vehicle response to disturbances. © 2012 Copyright Taylor and Francis Group, LLC.

A MIMO-OFDM testbed for wireless local area networks

We describe the design steps and final implementation of a MIMO OFDM prototype platform developed to enhance the performance of wireless LAN standards such as HiperLAN/2 and 802.11, using multiple transmit and multiple receive antennas. We first describe the channel measurement campaign used to characterize the indoor operational propagation environment, and analyze the influence of the channel on code design through a ray-tracing channel simulator. We also comment on some antenna and RF issues which are of importance for the final realization of the testbed. Multiple coding, decoding, and channel estimation strategies are discussed and their respective performance-complexity trade-offs are evaluated over the realistic channel obtained from the propagation studies. Finally,we present the design methodology, including cross-validation of the Matlab, C++, and VHDL components, and the final demonstrator architecture. We highlight the increased measured performance of the MIMO testbed over the single-antenna system. £.

Uncertainty management for on-line optimisation of a POMDP-based large-scale spoken dialogue system

The optimization of dialogue policies using reinforcement learning (RL) is now an accepted part of the state of the art in spoken dialogue systems (SDS). Yet, it is still the case that the commonly used training algorithms for SDS require a large number of dialogues and hence most systems still rely on artificial data generated by a user simulator. Optimization is therefore performed off-line before releasing the system to real users. Gaussian Processes (GP) for RL have recently been applied to dialogue systems. One advantage of GP is that they compute an explicit measure of uncertainty in the value function estimates computed during learning. In this paper, a class of novel learning strategies is described which use uncertainty to control exploration on-line. Comparisons between several exploration schemes show that significant improvements to learning speed can be obtained and that rapid and safe online optimisation is possible, even on a complex task. Copyright © 2011 ISCA.

Modelling 2DEG charges in AlGaN/GaN heterostructures

In this paper we compare different approaches to calculating the charge density in the 2DEG layer of AlGaN/GaN HEMTs. The methods used are (i) analytical theory implemented in MATLAB, (ii) finite-element analysis using semiconductor TCAD software that implements only the Poisson and continuity equations, and (iii) 1D software that solves the Poisson and Schrödinger equations self-consistently. By using the 1D Poisson-Schrödinger solver, we highlight the consequences of neglecting the Schrödinger equation. We conclude that the TCAD simulator predicts with a reasonable level of accuracy the electron density in the 2DEG layer for both a conventional HEMT structure and one featuring an extra GaN cap layer. In addition, while the sheet charge density is not significantly affected by including Schrödinger, its confinement in the channel is found to be modified. © 2012 IEEE.