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.
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.
14039097
A Proof System for Timed Automata
A proof system for timed automata is presented, based on a CCS-style 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 Φ ▹ t = u where Φ is a clock constraint and t, u are terms denoting timed automata. It is proved that the proof system is complete for timed bisimulation over the recursion-free subset of the language. The completeness proof relies on the notion of symbolic timed bisimulation. The axiomatisation is also extended to handle an important variation of timed automata where each node is associated with an invariant constraint.
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.
359393
PAM: A Process Algebra Manipulator
PAM is a general proof tool for process algebras. It allows users to define their own calculi and then perform algebraic style proofs in these calculi by directly manipulating process terms. The logic that PAM implements is equational logic plus recursion, with some features tailored to the particular requirements of process algebras. Equational reasoning is implemented by rewriting, while recursion is dealt with by induction. Proofs are constructed interactively, giving users the freedom to control the proof processes.
27608466
Symbolic Bisimulations
12726489
A Note on the Decomposition Methods for Support Vector Regression
The dual formulation of support vector regression involves two closely related sets of variables. When the decomposition method is used, many existing approaches use pairs of indices from these two sets as the working set. Basically, they select a base set first and then expand it so all indices are pairs. This makes the implementation different from that for support vector classification. In addition, a larger optimization subproblem has to be solved in each iteration. We provide theoretical proofs and conduct experiments to show that using the base set as the working set leads to similar convergence (number of iterations). Therefore, by using a smaller working set while keeping a similar number of iterations, the program can be simpler and more efficient.
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.
5244200
TCP Selective Negative Acknowledgment over IEEE 802.11 Wireless Networks
This paper investigates the performance of the TCP transport protocol over IEEE 802.11 wireless networks. A wireless link is generally characterized by high transmission errors and a varying latency. The erratic packet losses and poor bandwidth utilization which occur as a result limit the TCP's performance, resulting in a curbing of the flow of segments on the TCP connection and a corresponding degradation of the network performance. This paper examines the effects of the 802.11 characteristics on the TCP performance and proposes a scheme to improve the performance of TCP over wireless links. A novel acknowledgement scheme, SNACK, is introduced and a series of ns-2 based simulations are performed to compare its performance against that of other TCP schemes. The simulation results confirm that SNACK provides a better performance than other conventional TCP implementations in 802.11 wireless networks
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