18855634
Symbolic Transition Graph with Assignment
A new model for message-passing processes is proposed which generalizes the notion of symbolic transition graph as introduced in [HL95], by allowing assignments to be carried in transitions. The main advantage of this generalization is that a wider class of processes can be represented as finite state graphs. Two kinds of operational semantics, ground and symbolic, are given to such graphs. On top of them both ground and symbolic bisimulations are defined and are shown to agree with each other. An algorithm is also presented which computes bisimulation formulae for finite state symbolic transition graphs with assignments, in terms of the greatest solutions of predicate equation systems.
208092
Axiomatising timed automata
Abstract. Timed automata has been developed as a basic semantic model for real time systems. Its algorithmic aspects for automated analysis have been well studied. But so far there is still no satisfactory algebraic theory to allow the derivation of semantical equivalence of automata by purely syntactical manipulation. The aim of this paper is to provide such a theory. We present an inference system of timed bisimulation equivalence for timed automata based on a CCS-style regular language for describing timed automata. It consists of the standard monoid laws for bisimulation and a set of inference rules. The judgments of the proof system are conditional equations of the form 
$\phi \rhd t = u$ where 
$\phi$ is a clock constraint and t,u are terms denoting timed automata. The inference system is shown to be sound and complete for timed bisimulation. The proof of the completeness result relies on the notion of symbolic timed bisimulation, adapted from the work on value–passing processes.
27608466
Symbolic Bisimulations
10181791
Model checking value-passing processes
An algorithm for model checking value-passing processes is presented. Processes are modeled as symbolic transition graphs with assignments. To specify properties for such processes a graphical predicate mu-calculus is introduced. It allows arbitrary nesting of the least and greatest fixpoints, and contains the propositional mu-calculus as a proper subset. The algorithm instantiates input variables on-the-fly and states are only generated when they are needed for the computation. To handle alternating fix-points properly, a multi-stack is employed and the controlling strategy is such that a state is evaluated without depending on the default values for more deeply nested states. The algorithm is shown correct with respect to the semantics of the predicate mu-calculus. Its complexity is also analysed.
37655914
Unique Fixpoint Induction for Mobile Processes
Complete proof systems for bisimulation equivalences in the π-calculus with recursion are presented. The key inference rule dealing with recursion is unique fixpoint induction which generalises that used in [Mil84] for regular pure-CCS. It is shown that the proof systems are sound, and also complete when restricted to the subset of π-calculus where recursions are guarded and the parallel composition is disallowed. These results on the one hand extend the proof systems for recursion-free π-calculus in [Lin94, Lin95] to infinite processes, on the other hand extend the inference system for guarded regular pure-CCS of [Mil84] to π-calculus.
37846137
Computing bisimulations for finite-control π-calculus
Symbolic bisimulation avoids the infinite branching problem caused by instantiating input names with all names in the standard definition of bisimulation in π-calculus. However, it does not automatically lead to an efficient algorithm, because symbolic bisimulation is indexed by conditions on names, and directly manipulating such conditions can be computationally costly. In this paper a new notion of bisimulation is introduced, in which the manipulation of maximally consistent conditions is replaced with a systematic employment of schematic names. It is shown that the new notion captures symbolic bisimulation in a precise sense. Based on the new definition an efficient algorithm, which instantiates input names “on-the-fly”, is presented to check bisimulations for finite-control π-calculus.
15921507
Automatic Detection and Segmentation of Robot-Assisted Surgical Motions
Robotic surgical systems such as Intuitive Surgical's da Vinci system provide a rich source of motion and video data from surgical procedures. In principle, this data can be used to evaluate surgical skill, provide surgical training feedback, or document essential aspects of a procedure. If processed online, the data can be used to provide context-specific information or motion enhancements to the surgeon. However, in every case, the key step is to relate recorded motion data to a model of the procedure being performed. This paper examines our progress at developing techniques for "parsing" raw motion data from a surgical task into a labelled sequence of surgical gestures. Our current techniques have achieved >90% fully automated recognition rates on 15 datasets.
1232058
CORNet: A Scalable and Bandwidth-Efficient Optical Burst Switching Ring Architecture for Metro Area Networks
The rapid evolution of networks has been driven by new advances in enabling technologies and the explosive growth of Internet traffic. optical burst switching (OBS) is not only cost-effective, but also provides high throughput, high bandwidth utilization, and low transmission latency. These benefits make OBS a viable solution for next-generation metro area networks (MANs) in which the traffic models are changed more dramatically than today's networks. Based on wavelength division multiplexing (WDM) technology, this study presents a loss-free optical burst switching metro ring architecture, designated the collision-free optic-burst ring network (CORNet). The proposed architecture ensures a collision-free transmission of data bursts, while retaining the advantage of the statistical multiplexing provided by conventional OBS networks. The simulation results confirm the effectiveness of the proposed CORNet architecture
7435104
Navigating inner space: 3-D assistance for minimally invasive surgery
Abstract Since its inception about three decades ago, modern minimally invasive surgery has made huge advances in both technique and technology. However, the minimally invasive surgeon is still faced with daunting challenges in terms of visualization and hand-eye coordination. At the Center for Computer Integrated Surgical Systems and Technology (CISST) we have been developing a set of techniques for assisting surgeons in navigating and manipulating the three-dimensional space within the human body. In order to develop such systems, a variety of challenging visual tracking, reconstruction and registration problems must be solved. In addition, this information must be tied to methods for assistance that improve surgical accuracy and reliability but allow the surgeon to retain ultimate control of the procedure and do not prolong time in the operating room. In this article, we present two problem areas, eye microsurgery and thoracic minimally invasive surgery, where computational vision can play a role. We then describe methods we have developed to process video images for relevant geometric information, and related control algorithms for providing interactive assistance. Finally, we present results from implemented systems.
15749336
Improving the ramping up behavior of TCP slow start
This paper proposes an improvement to the TCP ramp up behavior in slow-start. Current implementations of the TCP start-up procedure may result in an exponential growth of the congestion window, which results in the transmission of an excessive number of packets. Consequently, the network becomes congested and the self-clocking mechanism of the TCP fails. By estimating the number of packets that which can be in flight in the network from the viewpoint of the TCP source, this study develops an algorithm to suppress congestion before it becomes significant. The simulation results indicate that the proposed algorithm enhances the TCP performance by establishing a smoother transmission rate at the end of the slow-start phase and reducing the number of dropped packets significantly as a result.
10416252
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thresholds. We derive novel large-margin bounds of common error functions, such as the classification error and the absolute error. In addition to some existing algorithms, we also study two novel boosting approaches for constructing thresholded ensembles. Both our approaches not only are simpler than existing algorithms, but also have a stronger connection to the large-margin bounds. In addition, they have comparable performance to SVM-based algorithms, but enjoy the benefit of faster training. Experimental results on benchmark datasets demonstrate the usefulness of our boosting approaches.