41322043
New exact travelling wave solutions for the shallow long wave approximate equations
Based upon a generally projective Riccati equation method, which is a direct and unified algebraic method for constructing more general form travelling wave solutions of nonlinear partial differential equations and implemented in a computer algebraic system, we consider the shallow long wave approximate equations. New and more general form solutions are obtained, including kink-shaped solitons, bell-shaped solitons, singular solitons and periodic solutions. The properties of the new formal solitary wave solutions are shown by some figures.
27234161
Two-dimensional symmetry reduction of (2 + 1)-dimensional nonlinear Klein-Gordon equation
In this paper, one-dimensional optimal system of group invariant solutions of (2+1)-dimensional Klein-Gordon system is constructed. Then the classification of group invariant solutions is given out and the corresponding two-dimensional symmetry reduced equations are obtained. At last some symmetry transformations are gained in detail. Especially, we obtain the most general solution from a given solution by use of six variable one-parameter subgroups transformations.
17242205
On the (co)girth of a connected matroid
This article studies the girth and cogirth problems for a connected matroid. The problem of finding the cogirth of a graphic matroid has been intensively studied, but studies on the equivalent problem for a vector matroid or a general matroid have been rarely reported. Based on the duality and connectivity of a matroid, we prove properties associated with the girth and cogirth of a matroid whose contraction or restriction is disconnected. Then, we devise algorithms that find the cogirth of a matroid M from the matroids associated with the direct sum components of the restriction of M. As a result, the problem of finding the (co)girth of a matroid can be decomposed into a set of smaller sub-problems, which helps alleviate the computation. Finally, we implement and demonstrate the application of our algorithms to vector matroids.
11827610
A Runtime System for Dynamic DAG Programming
A runtime system is described here for dynamic DAG execution. A large D A G whihc represents an application program can be executed on a parallel system without consuming large amount of memory space. A DAG scheduling algorithm has been parallelized to scale to large systems. Inaccurate estimation of task execution time and comm unication time can be tolerated. Implementation of this parallel incremental system demonstrates the feasibility of this approach. Preliminary results show that it is superior to other approaches.
14204568
End-to-End Trust Starts with Recognition
Pervasive computing requires some level of trust to be established between entities. In this paper we argue for an entity recognition based approach to building this trust which differs from starting from more traditional authentication methods. We also argue for the concept of a ”pluggable” recognition module which allows different recognition schemes to be used in different circumstances. Finally, we propose that the trust in the underlying infrastructure has to be taken into account when considering end-to-end trust.
20327796
An effective algorithm of motif finding problem
Identification of the short DNA sequence motif, which serves as binding targets for transcription factors, is a fundamental problem in both computer science and molecular biology. Especially, finding the subtle motifs with variable gaps is more challenging. In this paper, a new algorithm is presented, which explores some new strategies. Based on a neighbourhood set concept, a new probability matrix is defined, which can capture the target motifs effectively. An iterative restart strategy is used, by which we can use several similar motifs' information to detect the real motif to demonstrate the effectiveness of our algorithm. We test it on several kinds of data and compare it with some other current representation algorithms. Simulation shows that the algorithm can effectively detect the subtle motifs.
2275333
Risk probability estimating based on clustering
Ubiquitous computing environments are highly dynamic, with new unforeseen circumstances and constantly changing environments, which introduces new risks that cannot be assessed through traditional means of risk analysis. Mobile entities in a ubiquitous computing environment require the ability to perform an autonomous assessment of the risk incurred by a specific interaction with another entity in a given context. This assessment will allow a mobile entity to decide whether sufficient evidence exists to mitigate the risk and allow the interaction to proceed. Such evidence might include records of prior experiences, recommendations from a trusted entity or the reputation of the other entity. We propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based on the automatic clustering of defining features of the environment and the other entity, which helps avoid subjective judgments as much as possible.