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In this paper we consider the problem of time-consistency of the subcore in a multistage TU-cooperative game. We propose necessary and sufficient conditions for the time-consistency of an imputation from the subcore. Based on these conditions, we suggest an algorithm providing time-consistency of a selector of the subcore. Besides, we prove consistency of the subcore with respect to the MDM-reduction. Finally we introduce the notions of reduced game and dynamic consistency for multistage cooperative games. One of the main results of this paper is a theorem stating some properties of dynamic consistency of the subcore selectors. We focus particularly on the conditions of the dynamic consistency of the subcore with respect to the MDM-reduced game. [ABSTRACT FROM AUTHOR]

The generation of Pareto optimal solutions for complex systems with multiple conflicting objectives can be easier if the problem can be decomposed and solved as a set of smaller coordinated subproblems. In this paper, a new decomposition-coordination method is proposed, where the global problem is partitioned into subsystems on the basis of the connection structure of the mathematical model, assigning a relative importance to each of them. In order to obtain Pareto optimal solutions for the global system, the aforementioned subproblems are coordinated taking into account their relative importance. The scheme that has been developed is an iterative one, and the global efficient solutions are found through a continuous information exchange process between the coordination level (upper level) and the subsystem level (lower level). Computational experiments on several randomly generated problem instances show that the suggested algorithm produces efficient solutions within reasonable computational times. [ABSTRACT FROM AUTHOR]

This paper addresses a novel sentence reduction algorithm based on a decision tree model in which semantic information is used to enhance the accuracy of sentence reduction. The proposed algorithm is able to deal with the changeable order problem in sentence reduction. Furthermore, the use of decision list to solve the fragment problem in sentence reduction based decision tree model is also discussed. Our experimental results show an improvement when compared with earlier methods. [ABSTRACT FROM AUTHOR]

This paper proposes a new reliability model, circular consecutive 2-out-of-(r,r)-from-(n,n):F model. In this model, the system consists of a square grid of side n (containing of n2 components) such that the system fails if and only if there is at least one square of side r which includes among them at least two failed components. For i.i.d. case an algorithm is given for computing the reliability of circular system. The reliability function can be expressed by the number of 0–1 matrices having no two or more 0s at any square of side r. [ABSTRACT FROM AUTHOR]

The brain has evolved to enable organisms to survive in a complicated and dynamic world. Its operation is based upon a priori models of the environment which are adapted, during learning, in response to new and changing stimuli. The same qualities that make biological learning mechanisms ideal for organisms make their underlying mathematical algorithms ideal for certain technological applications, especially those concerned with understanding the physical processes giving rise to complicated data sets. In this paper, we offer a mathematical model for the underlying mechanisms of biological learning, and we show how this mathematical approach to learning can yield a solution to the problem of imaging time-varying objects from X-ray computed tomographic (CT) data. This problem relates to several practical aspects of CT imaging including the correction of motion artifacts caused by patient movement or breathing. [ABSTRACT FROM AUTHOR]

This paper proposes a procedure to design fault tolerant algorithms for the R-Mesh and some of its restrictive variations. This procedure first identifies a healthy sub-mesh from a faulty model using the bypass and removal fault model. Then it uses scalable algorithms to simulate the larger faulty model on the resulting healthy sub-mesh. The algorithms for the bypass model tolerates n faults in an n×n R-Mesh (LR-Mesh) and runs in O(T log n) (O(T)) time, where T is the execution time on the original mesh without faults. For the removal model, we design fault tolerant algorithms for some interesting variations of the R-Mesh, specifically, the NXR-Mesh and the NXLR-Mesh. We propose the first scaling simulations for these models and present a simulation of the R-Mesh on the NXR-Mesh. The results of this paper enable us to consider certain reconfigurable models in a more practical environment than previously allowed. [ABSTRACT FROM AUTHOR]

This paper introduces an automatic robust nonlinear identification algorithm using the leave-one-out test score also known as the PRESS (Predicted REsidual Sums of Squares) statistic and regularised orthogonal least squares. The proposed algorithm aims to achieve maximised model robustness via two effective and complementary approaches, parameter regularisation via ridge regression and model optimal generalisation structure selection. The major contributions are to derive the PRESS error in a regularised orthogonal weight model, develop an efficient recursive computation formula for PRESS errors in the regularised orthogonal least squares forward regression framework and hence construct a model with a good generalisation property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated model construction procedure without resort to any other validation data set for model evaluation. [ABSTRACT FROM AUTHOR]

A new multi-class classifier, decision tree SVM (DTSVM) which is a binary decision tree with a very simple structure is presented in this paper. In DTSVM, a problem of multi-class classification is decomposed into a series of ones of binary classification. Here, the binary decision tree is generated by using kernel clustering algorithm, and each non-leaf node represents one binary classification problem. By compared with the other multi-class classification methods based on the binary classification SVMs, the scale and the complexity of DTSVM are less, smaller number of support vectors are needed, and has faster test speed. The final simulation results confirm the feasibility and the validity of DTSVM. [ABSTRACT FROM AUTHOR]

The Multi-Tier (M-Tier) algorithm proposed in [1], has enabled an enhanced correlation between dynamic resource utilization and QoS guarantees. The algorithm favored the delay sensitive applications. Indirectly, this infers that the assignment of priorities practiced in the algorithm is static. In redesigning the algorithm, priority assignments should be able to be implemented dynamically. Thus, enabling an embedded element to provide implementation mobility. This would depend upon the current status of the classified buffers and the tolerance level of the delay sensitive traffic. Integrating control parameters to enable alternation in scheduling priorities is an option to resolve the element of partiality present in the M-Tier algorithm. Thereafter, the proposed algorithm will be denoted as the M-Tier(T) algorithm [2]. The paper proposes a detailed mathematical model for the analysis of dynamic resource reservation algorithms implemented in IP switches. The semi-markov process (SMP) approach utilized provides an accurate performance prediction and representation of resource reservation mechanisms. The algorithm correlates the average packet delay and packet loss ratio parameters to activate the dynamic resource reservation mechanism in a hierarchical manner. The developed models are validated through discrete-event simulation. The performance of the algorithm is studied in terms of average packet delay and network throughput. [ABSTRACT FROM AUTHOR]

In this paper, we consider a set of mobile nodes, each of which moves with constant velocity. We present algorithms to determine which of these mobile nodes can be captured the soonest by a set of one or more pursuers. We use a time parameterized R-tree (TPR-tree) to index these moving points. We then develop algorithms that operate on the TPR-tree to answer three query variations: (1) a single pursuer that is faster than all of the mobile nodes, (2) a single pursuer that is slower than some of the mobile nodes and (3) multiple pursuers. Experimental results show that our algorithms are simpler and faster than other approaches to solve the problem. [ABSTRACT FROM AUTHOR]