An Efficient Algorithm for Processing Multi-Relation Queries in Relational Databases

After a relation scheme R is decomposed into the set of schemes ρ={R1，…，Rn},we may pose queries as if Rexisted in the database,taking a join of Ri‘s,when it is necessary to implement the query,Suppos a query involves a set of attributes S R，we want to find the smallest subset of ρ whose union includes.S.We prove that the problem is NP-complete and present a polynomial-bounded approximation algorithm.A subset of ρ whose union includes S and has a decomposition into 3NF with a lossless join and preservation of dependencies in given in the paper.     

L* Algorithm—A Linear Computational Complexity Graph Searching Algorithm for Path Planning

The state-of-the-art graph searching algorithm applied to the optimal global path planning problem for mobile robots is the A* algorithm with the heap structured open list. In this paper, we present a novel algorithm, called the L* algorithm, which can be applied to global path planning and is faster than the A* algorithm. The structure of the open list with the use of bidirectional sublists (buckets) ensures the linear computational complexity of the L* algorithm because the nodes in the current bucket can be processed in any sequence and it is not necessary to sort the bucket. Our approach can maintain the optimality and linear computational complexity with the use of the cost expressed by floating-point numbers. The paper presents the requirements of the L* algorithm use and the proof of the admissibility of this algorithm. The experiments confirmed that the L* algorithm is faster than the A* algorithm in various path planning scenarios. We also introduced a method of estimating the execution time of the A* and the L* algorithm. The method was compared with the experimental results.     

An Efficient Algorithm for ℓ 0 Minimization in Wavelet Frame Based Image Restoration

Wavelet frame based models for image restoration have been extensively studied for the past decade (Chan et al. in SIAM J. Sci. Comput. 24(4):1408–1432, 2003; Cai et al. in Multiscale Model. Simul. 8(2):337–369, 2009; Elad et al. in Appl. Comput. Harmon. Anal. 19(3):340–358, 2005; Starck et al. in IEEE Trans. Image Process. 14(10):1570–1582, 2005; Shen in Proceedings of the international congress of mathematicians, vol. 4, pp. 2834–2863, 2010; Dong and Shen in IAS lecture notes series, Summer program on “The mathematics of image processing”, Park City Mathematics Institute, 2010). The success of wavelet frames in image restoration is mainly due to their capability of sparsely approximating piecewise smooth functions like images. Most of the wavelet frame based models designed in the past are based on the penalization of the ? ₁ norm of wavelet frame coefficients, which, under certain conditions, is the right choice, as supported by theories of compressed sensing (Candes et al. in Appl. Comput. Harmon. Anal., 2010; Candes et al. in IEEE Trans. Inf. Theory 52(2):489–509, 2006; Donoho in IEEE Trans. Inf. Theory 52:1289–1306, 2006). However, the assumptions of compressed sensing may not be satisfied in practice (e.g. for image deblurring and CT image reconstruction). Recently in Zhang et al. (UCLA CAM Report, vol. 11-32, 2011), the authors propose to penalize the ? ₀ “norm” of the wavelet frame coefficients instead, and they have demonstrated significant improvements of their method over some commonly used ? ₁ minimization models in terms of quality of the recovered images. In this paper, we propose a new algorithm, called the mean doubly augmented Lagrangian (MDAL) method, for ? ₀ minimizations based on the classical doubly augmented Lagrangian (DAL) method (Rockafellar in Math. Oper. Res. 97–116, 1976). Our numerical experiments show that the proposed MDAL method is not only more efficient than the method proposed by Zhang et al. (UCLA CAM Report, vol. 11-32, 2011), but can also generate recovered images with even higher quality. This study reassures the feasibility of using the ? ₀ “norm” for image restoration problems.     

An Efficient Algorithm for the Calculation of NURBS Curves and All Their Derivatives

Through a precise recursion of B-spline bases, this paper presents an efficient algorithm for the calculation of NURBS curves and all their derivatives. The algorithm requires less storage and is proved to be stable.     

Real-Time Collision-Free Path Planning for Robots in Configuration Space

Collision-free path planning for an industrial robot in configuration space requires mapping obstacles from robot‘s workspace into its configuration space.In this paper,an approach to real-time collision-free path planning for robots in configuration space is presented.Obstacle mapping is carried out by fundamental obstacles defined in the workspace and their images in the configuration space.In order to avoid dealing with unimportant parts of the configuration space that do not affect searching a collision-free path between starting and goal configurations,we construct a free subspace by slice configuration obstacles.In this free subspace,the collision-free path is determined by the A^* algorithm.Finally,graphical simulations show the effectiveness of the proposed approach.     

An Efficient Optimization Procedure for Tetrahedral Meshes by Chaos Search Algorithm

A simple and efficient local optimization-based procedure for node reposition-ing/smoothing of three-dimensional tetrahedral meshes is presented.The initial tetrahedral mesh is optimized with respect to a specified element shape measure by chaos search algorithm,which is very effective for the optimization problems with only a few design variables.Examples show that the presented smoothing procedure can provide favorable conditions for local transformation approach and the quality of mesh can be significantly improved by the combination of these two procedures with respect to a specified element shape measure.Meanwhile,several commonly used shape measures for tetrahedral element,which are considered to be equivalent in some weak sense over a long period of time,are briefly re-examined in this paper.Preliminary study indicates that using different measures to evaluate the change of element shape will probably lead to inconsistent result for both well shaped and poorly shaped elements.The proposed smoothing approach can be utilized as an appropriate and effective tool for evaluating element shape measures and their influence on mesh optimization process and optimal solution.     

TRUCE – An Adaptive Trust Management Algorithm Over MANET for Service-Based Mobile Computing Environments

ABSTRACT

Managing trust in a distributed MANET is challenging when collaboration or cooperation is critical to achieve mission and system goals such as reliability, availability, scalability, or reconfigurability. This paper discusses initiation and updation of trust values (called as TRUCE Value) over a defined trust model for mobile ad hoc networks. Each node {ni, where i ∈ 1, 2, 3, .., m} is assigned a trust level initially, while trust levels are updated dynamically based on behavior of nodes {n1, n2, .., nm} using threat detection tools and metrics, such as Intrusion Detection Systems (IDSs) (Zhang et al. (2002) Zhang, Y. 2002. Intrusion detection techniques for mobile wireless networks. ACM/Kluwer Mobile Networks and Applications (MONET),  [Google Scholar], between all nodes in the network. The node {nj} neighboring to a node {nk} exhibiting suspicious behavior can initiate trust reports, and based on an average set of trust reports, the node's {nj} trust value is modified. These defined trust reports are propagated through the network using one of TRUCE (proposed methods). A similar acceptable set of trust nodes can join together to evaluate the security of routes {r} from source to destination nodes. Using these trust levels as a guide, the source node can then select a route that meets the security requirements of the message to be transmitted.

This paper focuses on design, development of Trust evaluation, assignment algorithm termed TRUCE over a dynamic, highly insecure MANET network. Also, it demonstrates the procedure of establishing a collaborative, dynamic trust model and uses this model as an example to enhance the security of message routing in mobile ad hoc networks. Performance by simulation reveals that existing malicious nodes behave with vulnerability over MANET routing protocols such as DSR and AODV, but TRUCE with proposed trust-based node incentive mechanism performs better than DSR in terms of packet successful delivery ratio and mean number of packets dropped.     

Generalization of the Firm’s Profit Maximization Problem: An Algorithm for the Analytical and Nonsmooth Solution

In this paper we present a generalization of the classic Firm’s profit maximization problem, using the linear model for the production function, considering a non constant price and maximum constraints for the inputs. We formulate the problem by previously calculating the analytical minimum cost function. This minimum cost function will be calculated for each production level via the infimal convolution of quadratic functions and the result will be a piecewise quadratic function. To solve this family of optimization problems, we present an algorithm of quasi-linear complexity. Moreover, the resulting cost function in certain cases is not $C^{1}$ and the profit maximization problem will be solved within the framework of nonsmooth analysis. Finally, we present a numerical example.     

Continuously Parameterized Symmetries and Buchberger’s Algorithm

Systems of polynomial equations often have symmetries. In solving such a system using Buchberger’s algorithm, the symmetries are neglected. Incorporating symmetries into the solution process enables us to solve larger problems than with Buchberger’s algorithm alone. This paper presents a method that shows how this can be achieved and also gives an algorithm that brings together continuously parameterized symmetries with Buchberger’s algorithm.     

An Approximation Algorithm for Binary Searching in Trees

We consider the problem of computing efficient strategies for searching in trees. As a generalization of the classical binary search for ordered lists, suppose one wishes to find a (unknown) specific node of a tree by asking queries to its arcs, where each query indicates the endpoint closer to the desired node. Given the likelihood of each node being the one searched, the objective is to compute a search strategy that minimizes the expected number of queries. Practical applications of this problem include file system synchronization and software testing. Here we present a linear time algorithm which is the first constant factor approximation for this problem. This represents a significant improvement over previous O(log n)-approximation.     

An Efficient SMO Algorithm for Solving Non-smooth Problem Arising in $$varepsilon $$ ε -Insensitive Support Vector Regression

Neural Processing Letters - Classical support vector regression (C-SVR) is a powerful function approximation method, which is robust against noise and performs a good generalization, since it is...     

An Efficient WRF Framework for Discovering Risk Genes and Abnormal Brain Regions in Parkinson’s Disease Based on Imaging Genetics Data

As an emerging research field of brain science,multimodal data fusion analysis has attracted broader attention in the study of complex brain diseases such as Parkinson's disease (PD).However,current studies primarily lie with detecting the association among different modal data and reducing data attributes.The data mining method after fusion and the overall analysis framework are neglected.In this study,we propose a weighted random forest (WRF) model as the feature screening classifier.The interactions between genes and brain regions are detected as input multimodal fusion features by the correlation analysis method.We implement sample classification and optimal feature selection based on WRF,and construct a multimodal analysis framework for exploring the pathogenic factors of PD.The experimental results in Parkinson's Progression Markers Initiative (PPMI) database show that WRF performs better compared with some advanced methods,and the brain regions and genes related to PD are detected.The fusion of multi-modal data can improve the classification of PD patients and detect the pathogenic factors more comprehensively,which provides a novel perspective for the diagnosis and research of PD.We also show the great potential of WRF to perform the multimodal data fusion analysis of other brain diseases.     

Rough Set GA-based Hybrid Method for Robot Path Planning

In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations are optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed.     

Power Control Algorithm for Wireless Cellular System

A novel distributed power control algorithm based on interference estimation is presented for wireless cellular system. A classical result of stochastic approximation is applied in this scheme. The power control algorithm is converted to seeking for the zero point problem of a certain function. In this distributed power algorithm, each user iteratively updates its power level by estimating the interference. It does not require any knowledge of the channel gains or state information of other users. Hence, the proposed algorithm is robust. It is proved that the algorithm converges to the optimal solution by stochastic approximation approach.     

An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application

For many years, the hidden Markov model (HMM) has been one of the most popular tools for analysing sequential data. One frequently used special case is the left-right model, in which the order of the hidden states is known. If knowledge of the duration of a state is available it is not possible to represent it explicitly with an HMM. Methods for modelling duration with HMM’s do exist (Rabiner in Proc. IEEE 77(2):257–286, [1989]), but they come at the price of increased computational complexity. Here we present an efficient and robust algorithm for modelling duration in HMM’s, and this algorithm is successfully used to control autonomous computer actors in a theatrical play.     

An Artificial Neural Network for Solving Distributed Optimal Control of the Poisson’s Equation

Neural Processing Letters - This paper presents a simple and efficient method based on artificial neural network to solve distributed optimal control of Poisson’s equation with Dirichlet...     

An Algorithm for Solving a Family of Fourth-Degree Diophantine Equations that Satisfy Runge’s Condition

Programming and Computer Software - This paper proposes an algorithmic implementation of the elementary version of Runge’s method for a family of fourth-degree Diophantine equations in two...     

An Attack-Finding Algorithm for Security Protocols

This paper proposes an automatic attack construction algorithm in order to find potential attacks on ecurity protocols.It is based on a dynamic strand space model,which enhances the original strand space model by introducing active nodes on strands so as to characterize the dynamic procedure of protocol execution.With exact causal dependency relations between messages considered in the model,this algorithm can avoid state space explo-sion caused by asynchronous composition.In order to get a finite state space,a new method called strand-added on demand is exploited,which extends a bundle in an incremental manner without requiring explicit configuration of protocol execution parameters.A finer granularity model of term structure is also introduced, in which subterms are divided into check subterms and data subterms .Moreover,data subterms can be further classified based on the compatible data subterm relation to obtain automatically the finite set of valid acceptable terms for an honest principal.In this algorithm,terms core is designed to represent the intruder‘s knowledge compactly,and forward search technology is used to simulate attack patterns easily.Using this algorithm,a new attack on the Dolve-Yao protocol can be found,which is even more harmful beeause the secret is revealed before the session terminates.