Parallel and Symbolic Model Checking for Fixpoint Logic with Chop

We consider the model checking problem for FLC, a modal fixpoint logic capable of defining non-regular properties. This paper presents a refinement of a symbolic model checker and discusses how to parallelise this algorithm. It reports on a prototype implementation of the algorithm in Glasgow Parallel Haskell (GpH) and its performance on a cluster of workstations.     

A microscopic interpretation of the RF noise performance of fabricated FDSOI MOSFETs

In this paper, a detailed research of the high-frequency noise sources and figures of merit (FOMs) of fabricated deep-submicrometer n-channel fully depleted silicon-on-insulator MOSFETs is carried out. Special care is given to reproduce the main topology parameters, together with the most relevant parasitic elements of real devices in order to accomplish an accurate and reliable simulation. The information provided by the Monte Carlo (MC) tool allows getting a physical insight of the relationship between internal quantities and the main noise sources inside the device; moreover, the spectral density of velocity fluctuations has been analyzed spatially in order to determine the local current noise source in the gradual channel and velocity overshoot sections of the effective channel. Together with the calculation of intrinsic noise sources, the MC simulator is able to reproduce the measurements for the main noise FOMs in the RF and microwave frequency ranges. Moreover, the whole simulation framework allows addressing the importance of parasitic elements in the final value of these FOMs.     

Densification behavior of tungsten heavy alloy based on master sintering curve concept

The master sintering curve (MSC) theory is modified by substituting the densification ratio (φ) for the densification parameter (ψ) to identify regions where shrinkage occurs by a similar combination of sintering mechanisms. The modified MSC theory is used to analyze the results of dilatometry experiments conducted with W-Ni-Fe heavy alloys, in which a phase change occurs during sintering. Apparent activation energies for sintering in three regions (solid state, transition, and liquid phase) are calculated. These activation energies are compared with experimental values for diffusion and other mass-transport phenomena to identify the dominant mechanisms in each region. A series of master sinter curves for varying W contents are developed into a master sintering surface that includes tungsten content and integral work.     

Curvature-Driven PDE Methods for Matrix-Valued Images

Matrix-valued data sets arise in a number of applications including diffusion tensor magnetic resonance imaging (DT-MRI) and physical measurements of anisotropic behaviour. Consequently, there arises the need to filter and segment such tensor fields. In order to detect edge-like structures in tensor fields, we first generalise Di Zenzo’s concept of a structure tensor for vector-valued images to tensor-valued data. This structure tensor allows us to extend scalar-valued mean curvature motion and self-snakes to the tensor setting. We present both two-dimensional and three-dimensional formulations, and we prove that these filters maintain positive semidefiniteness if the initial matrix data are positive semidefinite. We give an interpretation of tensorial mean curvature motion as a process for which the corresponding curve evolution of each generalised level line is the gradient descent of its total length. Moreover, we propose a geodesic active contour model for segmenting tensor fields and interpret it as a minimiser of a suitable energy functional with a metric induced by the tensor image. Since tensorial active contours incorporate information from all channels, they give a contour representation that is highly robust under noise. Experiments on three-dimensional DT-MRI data and an indefinite tensor field from fluid dynamics show that the proposed methods inherit the essential properties of their scalar-valued counterparts.     

Adaptive decision-making frameworks for dynamic multi-agent organizational change

This article presents a capability called Adaptive Decision-Making Frameworks (ADMF) and shows that it can result in significantly improved system performance across run-time situation changes in a multi-agent system. Specifically, ADMF can result in improved and more robust performance compared to the use of a single static decision-making framework (DMF). The ADMF capability allows agents to dynamically adapt the DMF in which they participate to fit their run-time situation as it changes. A DMF identifies a set of agents and specifies the distribution of decision-making control and the authority to assign subtasks among these agents as they determine how a goal or set of goals should be achieved. The ADMF capability is a form of organizational adaptation and differs from previous approaches to organizational adaptation and dynamic coordination in that it is the first to allow dynamic and explicit manipulation of these DMF characteristics at run-time as variables controlling agent behavior. The approach proposed for selecting DMFs at run-time parameterizes all domain-specific knowledge as characteristics of the agents’ situation, so the approach is application-independent. The presented evaluation empirically shows that, for at least one multi-agent system, there is no one best DMF for multiple agents across run-time situational changes. Next, it motivates the further exploration of ADMF by showing that adapting DMFs to run-time variations in situation can result in improved overall system performance compared to static or random DMFs.     

Microchannel bioreactors for bioartificial liver support

An extracorporeal bioartificial liver (BAL) device containing viable hepatocytes has the potential to provide temporary hepatic support to liver failure patients, serving as a bridge to transplantation while awaiting a suitable donor. In some patients, providing temporary hepatic support may be sufficient to allow adequate regeneration of the host liver, thereby eliminating the need for a liver transplant. Although the BAL device is a promising technology for the treatment of liver failure, there are several technical challenges that must be overcome in order to develop systems with sufficient processing capacity and of manageable size. In this study, the authors describe the critical issues involved in developing a BAL device. They also discuss their experiences in hepatocyte culture optimization within the context of a microchannel flat-plate BAL device.     

Caching video objects: layers vs versions?

Because Internet access rates are highly heterogeneous, many video content providers today make available different versions of the videos, with each version encoded at a different rate. Multiple video versions, however, require more server storage and may also dramatically impact cache performance in a traditional cache or in a CDN server. An alternative to versions is layered encoding, which can also provide multiple quality levels. Layered encoding requires less server storage capacity and may be more suitable for caching; but it typically increases transmission bandwidth due to encoding overhead. In this paper we compare video streaming of multiple versions with that of multiple layers in a caching environment. We examine caching and distribution strategies that use both versions and layers. We consider two cases: the request distribution for the videos is known a priori; and adaptive caching, for which the request distribution is unknown. Our analytical and simulation results indicate that mixed distribution/caching strategies provide the best overall performance.A shorter version of this work has appeared in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Vol. 2, pages 45–48, Lausanne, Switzerland, August 2002     

Update strategies for kriging models used in variable fidelity optimization

Many optimization methods for simulation-based design rely on the sequential use of metamodels to reduce the associated computational burden. In particular, kriging models are frequently used in variable fidelity optimization. Nevertheless, such methods may become computationally inefficient when solving problems with large numbers of design variables and/or sampled data points due to the expensive process of optimizing the kriging model parameters in each iteration. One solution to this problem would be to replace the kriging models with traditional Taylor series response surface models. Kriging models, however, were shown to provide good approximations of computer simulations that incorporate larger amounts of data, resulting in better global accuracy. In this paper, a metamodel update management scheme (MUMS) is proposed to reduce the cost of using kriging models sequentially by updating the kriging model parameters only when they produce a poor approximation. The scheme uses the trust region ratio (TR-MUMS), which is a ratio that compares the approximation to the true model. Two demonstration problems are used to evaluate the proposed method: an internal combustion engine sizing problem and a control-augmented structural design problem. The results indicate that the TR-MUMS approach is very effective; on the demonstration problems, it reduced the number of likelihood evaluations by three orders of magnitude compared to using a global optimizer to find the kriging parameters in every iteration. It was also found that in trust region-based method, the kriging model parameters need not be updated using a global optimizer—local methods perform just as well in terms of providing a good approximation without affecting the overall convergence rate, which, in turn, results in a faster execution time.