115232895
Elastostatic inverse formulation
Abstract. In this paper an inverse method for solving elastostatic problems with incomplete boundary conditions is presented. In general, inverse problems are ill-posed boundary value problems whose stability and uniqueness of solution and sensitivity-based formulations require additional constraints. In the development we use the Betti-reciprocal theorem to represent the boundary traction field in terms of the boundary and field displacements in an integral form. Initially, we assume the unknown boundary conditions and deformations required to solve the problem. In this way we equate the work done by the exact solution (unknown) to the work done by an assumed solution. Discretizing the resulting equations and using an iterative procedure each step in the solution process becomes the solution to a well-posed problem. Thus, with sufficient perturbations the correct boundary conditions are reconstructed.

120158207
Thermoelastic plastic metals with mass diffusion
Abstract. In this paper we develop new governing equations for contact stresses in metals. They include the coupled effects of thermal elastic-plastic theory, including balance and constitutive laws. While the results are quite general, this work had it origins in describing the metal cutting process. As one example, the resulting equations can be applied to precision and ultraprecision cutting.

21408324
A Stability Property of T. Chan's Preconditioner
In this short note, we prove that T. Chan's preconditioner proposed in {TChan} [SIAM J. Sci. Statist. Comput., 9 (1988), pp. 766--771] is stable for matrices that are normal and stable.
7238513
An extended event matching approach in content-based pub/sub systems for EAI
Content-based publish/subscribe offers a convenient abstraction for information producers and consumers, supporting a large-scale system design and evolution by integrating several distributed independent application systems. Unlike in the traditional address-based unicast or multicast, its core problem is how to match events by predicates on the content of events. In existing matching approaches, matching predicates are composed by the conjunction and disjunction of non-semantic constraints. But, in context of enterprise application integration, although they can match events by their contents, this traditional matching predicates are not expressive enough in manipulating the complex event matching, such as the "one-to-many" and "many-to-one" matching. Therefore, traditional matching approaches should be extended to solve the complex matching problems. After analyzing information matching patterns in enterprise application integration, we propose three matching models, extend this simple matching approach to the multi-semantic matching approach and further introduce the temporal constraint variable. The multi-semantic matching approach allows using different operations in accordance with different semantics; the temporal constraint variable supports processing several discrete events in temporal sequences. Then, we extend OBDD graphs into hierarchy coloured OBDD graphs and prove the equivalence of the transformation. Based on the extended OBDD graphs, the composite matching algorithm is presented and analysed. By experiments, we show the proposed algorithm is efficient.
24579136
The Periodic Solution of a Class of Two Neurons Hopfield Network with Distributed Delay
This paper considers the two neurons Hopfield network with distributed delay, which can be transformed into the three-dimensional differential system. Then we use the result of competitive system to get the periodic solution of the system. We also show that existence and uniqueness of equilibrium point, and if the equilibrium is unstable, then an orbitally asymptotically stable periodic solution exists.
20174343
An operator splitting method for variational inequalities with partially unknown mappings
In this paper, we propose a new operator splitting method for solving a class of variational inequality problems in which part of the underlying mappings are unknown. This class of problems arises frequently from engineering, economics and transportation equilibrium problems. At each iteration, by using the information observed from the system, the method solves a system of nonlinear equations, which is well-defined. Under mild assumptions, the global convergence of the method is proved, and its efficiency is demonstrated with numerical examples.
1527832
Document clustering with cluster refinement and model selection capabilities
In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clusters in the document corpus (i.e. the model selection capability). To accurately cluster the given document corpus, we employ a richer feature set to represent each document, and use the Gaussian Mixture Model (GMM) together with the Expectation-Maximization (EM) algorithm to conduct an initial document clustering. From this initial result, we identify a set of discriminative featuresfor each cluster, and refine the initially obtained document clusters by voting on the cluster label of each document using this discriminative feature set. This self-refinement process of discriminative feature identification and cluster label voting is iteratively applied until the convergence of document clusters. On the other hand, the model selection capability is achieved by introducing randomness in the cluster initialization stage, and then discovering a value C for the number of clusters N by which running the document clustering process for a fixed number of times yields sufficiently similar results. Performance evaluations exhibit clear superiority of the proposed method with its improved document clustering and model selection accuracies. The evaluations also demonstrate how each feature as well as the cluster refinement process contribute to the document clustering accuracy.