Complete inference systems for weak bisimulation equivalences in the pi-calculus
Proof systems for weak bisimulation equivalences in the π-calculus are presented, and their soundness and completeness are shown. Two versions of π-calculus are investigated, one without and the other with the mismatch operator. For each version of the calculus proof systems for both late and early weak bisimulation equivalences are studied. Thus there are four proof systems in all. These inference systems are related in a natural way: the inference system for early equivalence is obtained from the one for late equivalence by replacing the inference rule for input prefix, while the inference system for the version of π-calculus with mismatch is obtained by adding a single inference rule for mismatch to the one for the version without it. The proofs of the completeness results rely on the notion of symbolic bisimulation.

title: 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.

title: Computing bisimulations for finite-control π-calculus
abstract: 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.

title: Symbolic Bisimulations

title: Model checking value-passing processes
abstract: 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.

title: Unique Fixpoint Induction for Mobile Processes
abstract: 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.

title: Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
abstract: 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.

title: Improving the ramping up behavior of TCP slow start
abstract: 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.

title: A Note on the Decomposition Methods for Support Vector Regression
abstract: 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.

title: Automatic Detection and Segmentation of Robot-Assisted Surgical Motions
abstract: 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.

title: 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.