Two classes of passive time-varying well-posed linear systems

We investigate two classes of time-varying well-posed linear systems. Starting from a time-invariant scattering-passive system, each of the time-varying systems is constructed by introducing a time-dependent inner product on the state space and modifying some of the generating operators. These classes of linear systems are motivated by physical examples such as the electromagnetic field around a moving object. To prove the well-posedness of these systems, we use the Lax–Phillips semigroup induced by a well-posed linear system, as in scattering theory.     

A fluid approach to large volume job shop scheduling

We consider large volume job shop scheduling problems, in which there is a fixed number of machines, a bounded number of activities per job, and a large number of jobs. In large volume job shops it makes sense to solve a fluid problem and to schedule the jobs in such a way as to track the fluid solution. There have been several papers which used this idea to propose approximate solutions which are asymptotically optimal as the volume increases. We survey some of these results here. In most of these papers it is assumed that the problem consists of many identical copies of a fixed set of jobs. Our contribution in this paper is to extend the results to the far more general situation in which the many jobs are all different. We propose a very simple heuristic which can schedule such problems. We discuss asymptotic optimality of this heuristic, under a wide range of previously unexplored situations. We provide a software package to explore the performance of our policy, and present extensive computational evidence for its effectiveness.     

Assessing the state of software in a large enterprise

To be relevant to the goals of an enterprise, an industrial software engineering research organization must identify problems of interest to, and find solutions that have an impact on, the software development organizations within the company. Using a systematic measurement program both to identify the problems and assess the impact of solutions is key to satisfying this need. Avaya has had such a program in place for about seven years. Every year we produce an annual report known as the State of Software in Avaya that describes software development trends throughout the company and that contains prioritized recommendations for improving Avaya’s software development capabilities. We start by identifying the goals of the enterprise and use the goal-question-metric approach to identify the measures to compute. The result is insight into the enterprise’s problems in software development, recommendations for improving the development process, and problems that require research to solve. We will illustrate the process with examples from the Software Technology Research Department in Avaya Labs whose purpose is to improve the state of software development and know it. “Know it” means that improvement should be subjectively evident and objectively quantifiable. “Know it” also means that one must be skilled at identifying the data sources, performing the appropriate analyses to answer the questions of interest, and validating that the data are accurate and appropriate for the purpose. Examples will include how and why we developed a measure of software quality that appeals to customers, how and why we are studying the effectiveness of distributed software development, and how and why we are helping development organizations to adopt iterative development methods. We will also discuss how we keep the company and the department apprised of the current strengths and weaknesses of software development in Avaya through the publication of the annual State of Software in Avaya Report. Our purpose is both to provide a model for assessment that others may emulate, based on seven years of experience, and to spotlight analyses and conclusions that we feel are common to software development today.     

Adaptive supervision of moving objects for mobile robotics applications

One of the main tasks of mobile robotics is vision. Lighting independence, adaptivity and automated learning are still the main issues when it comes to applications. In this article, we present an image understanding system and its methods targeting automatic, lighting-independent and reliable color-based object recognition under real time conditions. Its application test bed is global vision robot soccer (i.e. FIRA MiroSot und RoboCup Small Size leagues) but it has many other applications in color-based supervision of moving objects. Under typical conditions, it learns the objects of recognition automatically, has zero setup time and tolerates environmental changes during run-time.     

Development of active matrix LCD for use in high‐resolution adaptive headlights

Conventional adaptive driving beam headlamps are limited in achieving still higher quantities of switchable pixels by the number of LEDs and movable elements needed. In this paper, it is shown that by integrating an active matrix liquid crystal display module, it is possible to realize fully adaptive high‐resolution headlights without mechanical elements and a finite number of LED with 30 k switchable pixels.     

User assisted separation of reflections from a single image using a sparsity prior

When we take a picture through transparent glass the image we obtain is often a linear superposition of two images: the image of the scene beyond the glass plus the image of the scene reflected by the glass. Decomposing the single input image into two images is a massively ill-posed problem: in the absence of additional knowledge about the scene being viewed there are an infinite number of valid decompositions. In this paper we focus on an easier problem: user assisted separation in which the user interactively labels a small number of gradients as belonging to one of the layers. Even given labels on part of the gradients, the problem is still ill-posed and additional prior knowledge is needed. Following recent results on the statistics of natural images we use a sparsity prior over derivative filters. This sparsity prior is optimized using the terative reweighted least squares (IRLS) approach. Our results show that using a prior derived from the statistics of natural images gives a far superior performance compared to a Gaussian prior and it enables good separations from a modest number of labeled gradients.     

Stepwise dissection and visualization of the catalytic mechanism of haloalkane dehalogenase LinB using molecular dynamics simulations and computer graphics

The different steps of the dehalogenation reaction carried out by LinB on three different substrates have been characterized using a combination of quantum mechanical calculations and molecular dynamics simulations. This has allowed us to obtain information in atomic detail about each step of the reaction mechanism, that is, substrate entrance and achievement of the near-attack conformation, transition state stabilization within the active site, halide stabilization, water molecule activation and subsequent hydrolytic attack on the ester intermediate with formation of alcohol, and finally product release. Importantly, no bias or external forces were applied during the whole procedure so that both intermediates and products were completely free to sample configuration space in order to adapt to the plasticity of the active site and/or search for an exit. Differences in substrate reactivity were found to be correlated with the ease of adopting the near-attack conformation and two different exit pathways were found for product release that do not interfere with substrate entrance. Additional support for the different entry and exit pathways was independently obtained from an examination of the enzyme's normal modes.     

Distributed Symbolic Bounded Property Checking

In this paper we describe an algorithm for distributed, BDD-based bounded property checking and its implementation in the verification tool SymC. The distributed algorithm verifies larger models and returns results faster than the sequential version.The core algorithm distributes partitions of the state set to computation nodes after reaching a threshold size. The nodes proceed with image computation on the nodes asynchronously. The main scalability problem of this scheme is the overlap of state set partitions. We present static and dynamic overlap reduction techniques.     

The effect of axial residual stress on the mechanical behaviour of composites

The effect of axial residual stress on the properties of continuous fibre composites is calculated. It is emphasized that composite strength should be considered as a more complex phenomenon than usually done so by merely considering ultimate strength. It is shown that the information contained in ()-curves if plotted in a more suitable form as hysteresis and set versus total strain, taking into account residual stress, may be a useful means for characterizing the composite and for detecting deviations from perfect structure. Conclusions are derived as to how composite performance may be improved. The results are substantiated by metallic composite data.