A Note on Shor＇s Quantum Algorithm

Shor proposed a polynomial time algorithm for computing the order of one element in a multiplicative group using a quantum computer. Based on Miller＇s randomization, he then gave a factorization algorithm. But the algorithm has two shortcomings, the order must be even and the output might be a trivial factor. Actually, these drawbacks can be overcome if the number is an RSA modulus. Applying the special structure of the RSA modulus, an algorithm is presented to overcome the two shortcomings. The new algorithm improves Shor＇s algorithm for factoring RSA modulus. The cost of the factorization algorithm almost depends on the calculation of the order of 2 in the multiplication group.     

Fault reconfiguration of shipboard power system based on triple quantum differential evolution algorithm

Fault reconfiguration of shipboard power system is viewed as a typical nonlinear and multi-objective combinatorial optimization problem. A comprehensive reconfiguration model is presented in this paper, in which the restored loads, switch frequency and generator efficiency are taken into account. In this model, analytic hierarchy process(AHP) is proposed to determine the coefficients of these objective functions. Meanwhile, a quantum differential evolution algorithm with triple quantum bit code is proposed. This algorithm aiming at the characteristics of shipboard power system is different from the normal quantum bit representation. The individual polymorphic expression is realized, and the convergence performance can be further enhanced in combination with the global parallel search capacity of differential evolution algorithm and the superposition properties of quantum theory. The local optimum can be avoided by dynamic rotation gate. The validity of algorithm and model is verified by the simulation examples.     

Application of PI Control Algorithm to Discrete Manufacturing Systems

PI （proportional-integral） control algorithm is applied to control WlP （work-in-progress） in a discrete manufacturing system, where the cascade control of PI controllers is presented. It is in the frequency domain that the PI controller is designed with constraints on sensitivity options to ensure the stability and robustness of its parameters. A case is evaluated on a motorcycle engine crankcase production system, whose simulation results confirm that demand fluctuations can be compensated by PI controllers under a normal demand. PI controllers also possess low sensitivity to the distribution of production times.     

Logistic Regression for Evolving Data Streams Classification

Logistic regression is a fast classifier and can achieve higher accuracy on small training data.Moreover,it can work on both discrete and continuous attributes with nonlinear patterns.Based on these properties of logistic regression,this paper proposed an algorithm,called evolutionary logistical regression classifier(ELRClass),to solve the classification of evolving data streams.This algorithm applies logistic regression repeatedly to a sliding window of samples in order to update the existing classifier,to keep this classifier if its performance is deteriorated by the reason of bursting noise,or to construct a new classifier if a major concept drift is detected.The intensive experimental results demonstrate the effectiveness of this algorithm.     

Attribute-based signature on lattices

Attribute-based signature is a versatile class of digital signatures. In attribute-based signature, a signer obtains his private key corresponding to the set of his attributes from a trusted authority, and then he can sign a message with any predicate that is satisfied by his attributes set. Unfortunately, there does not exist an attribute- based signature which is resistance to the quantum attacks. This means we do not have secure attribute-based signature schemes in a post-quantum world. Based on this consideration, an attribute-based signature on lattices, which could resist quantum attacks, is proposed. This scheme employs ＂bonsai tree＂ techniques, and could be proved secure under the hardness assumption of small integer solution problem.     

Fault Detection Observer Design for LSFDJ： A Factorization Approach

Based on a new special co-inner-outer factorization, a factorization approach for design fault detection observer for LSFDJ was proposed. It is a simple state-space method and can deal with time varying LSFDJ with sensor noise and sensor faults. The performance of the fault detection observer is optimized in an H∞ setting,where the ratio between the gains from disturbance and fault to residual respectively is minimized. The design parameters of the detection observer were given in terms of the solution to the Riccati differential equation with jumps.     

A Dynamic Job Scheduling Algorithm for Parallel System

One of the fundamental problems in parallel and distributed systems is deciding how to allocate jobs to processors. The goals of job scheduling in a parallel environment are to minimize the parallel execution time of a job and try to balance the user‘s desire with the system‘s desire. The users always want their jobs be completed as quickly as possible, while the system wants to service as many jobs as possible. In this paper, a dynamic job-scheduling algorithm was introduced. This algorithm tries to utilize the information of a practical system to allo-cate the jobs more evenly. The communication time between the processor and scheduler is overlapped with the computation time of the processor. So the communication overhead can he little. The principle of scheduling the job is based on the desirability of each processor. The scheduler would not allocate a new job to a processor that is already fully utilized. The execution efficiency of the system will he increased. This algorithm also can he reused in other complex algorithms.     

Geometrical design of blade＇s surface and boundary control of Navier-Stokes equations

In this article a new principle of geometric design for blade＇s surface of an impeller is provided. This is an optimal control problem for the boundary geometric shape of flow and the control variable is the surface of the blade. We give a minimal functional depending on the geometry of the blade＇s surface and such that the flow＇s loss achieves minimum. The existence of the solution of the optimal control problem is proved and the Euler-Lagrange equations for the surface of the blade are derived. In addition, under a new curvilinear coordinate system, the flow domain between the two blades becomes a fixed hexahedron, and the surface as a mapping from a bounded domain in R2 into R3 , is explicitly appearing in the objective functional. The Navier-Stokes equations, which include the mapping in their coefficients, can be computed by using operator splitting algorithm. Furthermore, derivatives of the solution of Navier- Stokes equations with respect to the mapping satisfy linearized Navier-Stokes equations which can be solved by using operator splitting algorithms too. Hence, a conjugate gradient method can be used to solve the optimal control problem.     

A New Algorithm for Mining Frequent Pattern

Mining frequent pattern in transaction database,time-series databases,and many other kinds of databases have been studied popularly in data mining research.Most of the previous studies adopt Apriori-like candidate set generation-and-test approach.However,candidate set generation is very costly.Han J.proposed a novel algorithm FP-growth that could generate frequent pattern without candidate set.Based on the analysis of the algorithm FP-growth,this paper proposes a concept of equivalent FP-tree and proposes an improved algorithm,denoted as FP-growth,which is much faster in speed,and easy to realize,FP-growth adopts a modifeid structure of FP-tree and header table,and only generates a header table in each recursive operation and projects the tree to the original FP-tree,The two algorithms get the same frequent pattern set in the same transaction database,but the performance study on computer shows that the speed of the improved algorithm,FP-growth,is at least two times as fast as that of FP-growth.     

Probability-based clustering and its application to WLAN location estimation

Wireless local area networks (WLAN) localization based on received signal strength is becoming an important enabler of location based services. Limited efficiency and accuracy are disadvantages to the deterministic location estimation techniques. The probabilistic techniques show their good accuracy but cost more computation overhead. A Gaussian mixture model based on clustering technique was presented to improve location determination efficiency. The proposed clustering algorithm reduces the number of candidate locations from the whole area to a cluster. Within a cluster, an improved nearest neighbor algorithm was used to estimate user location using signal strength from more access points. Experiments show that the location estimation time is greatly decreased while high accuracy can still be achieved.     

Simplified Group Search Optimizer Algorithm for Large Scale Global Optimization

A simplified group search optimizer algorithm denoted as"SGSO"for large scale global optimization is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problems.The SGSO adopts an improved sharing strategy which shares information of not only the best member but also the other good members,and uses a simpler search method instead of searching by the head angle.Furthermore,the SGSO increases the percentage of scroungers to accelerate convergence speed.Compared with genetic algorithm(GA),particle swarm optimizer(PSO)and group search optimizer(GSO),SGSO is tested on seven benchmark functions with dimensions 30,100,500 and 1 000.It can be concluded that the SGSO has a remarkably superior performance to GA,PSO and GSO for large scale global optimization.     

Research on an Algorithm of Shape from Shading

Shape from shading(SFS)is an important domain in computer vision. The paper presented an improved algorithm of shape from shading based on a single image according to an existed one. The presented algorithm enhanced the boundary constraints to eliminate the rotation distortion on the border of reconstructed object and introduced the factor of brightness error to weaken the influence irradiance equation‘s nonlinearity on reconstructed errors. The reconstructed results verify the performance improvement in terms of accuracy by the input image of a synthetic image and a real image of weld.     

An Optimal Algorithm for a Class of Parallel Machines Scheduling Problem

This paper considers the parallel machines scheduling problem where jobs are subject to different releas etimes. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In general, the quality of the solutions provided by heuristics degrades with the increase of the probiem‘s scale. Combined the global search ability of genetic algorithm, this paper proposed a hybrid heuristic to improve the quality of solutions further. The computational results show that the hybrid heuristic combines the advantages of heuristic and genetic algorithm effectively and can provide very good solutions to some large problems in a reasonable amount of computer time.     

Multimodal Evolution Approach to Multidimensional Intrusion Detection

An artificial immunity based multimodal evolution algorithm is developed to generate detectors with variable coverage for multidimensional intrusion detection. In this algorithm, a proper fitness function is used to drive the detectors to fill in those detection holes close to self set or among self spheres, and genetic algorithm is adopted to reduce the negative effects that different distribution of self imposes on the detector generating process. The validity of the algorithm is tested with spherical and rectangular detectors, respectively, and experiments performed on two real data sets （machine learning database and DAPRA99） indicate that the proposed algorithm can obtain good results on spherical detectors, and that its performances in detection rate, false alarm rate, stabih＇ty, time cost, and adaptability to incomplete training set on spherical detectors are all better than on rectangular ones.     

A New Type of Continuously Variable Displacement Mechanism Used for Hydraulic Motors

A continuously variable displacement mechanism, which is composed of a hydraulic control valve with mechanical-positional feedback to camshaft, was designed for changing the displacement of traditional camshaft connecting-rod low speed high torque (LSHT) hydraulic motor continuously. The new type of continuously variable displacement mechanism is simple and easy to be made. The structure and principle of a continuously variable displacement mechanism was introduced. The mathematic model of the continuously variable displacement mechanism was set up and its static and dynamic characteristics were analyzed with the help of computer simulation. It can be seen that the cam ring on camshaft of the traditional LSHT hydraulic motor can stop at any position between minimum and maximum eccentricity, according to an input fluid pressure signal. And it can also stay anywhere stably through self-adjusting. Besides, it can work stabilized when load impact or oil leakage exists.     

On-line detecting of transformer winding deformation based on parameter identification of leakage inductance

Transformers are required to demonstrate the ability to withstand short circuit currents. Over currents caused by short circuit can give rise to windings deformation. In this paper, a novel method is proposed to monitor the state of transformer windings, which is achieved through on-line detecting the leakage inductance of the windings. Specifically, the mathematical model is established for on-line identifying the leakage inductance of the windings by applying least square algorithm （LSA） to the equivalent circuit equations. The effect of measurement and model inaccuracy on the identification error is analyzed, and the corrected model is also given to decrease these adverse effect on the results. Finally, dynamic test is carried out to verify our method. The test results clearly show that our method is very accurate even under the fluctuation of load or power factor. Therefore, our method can be effectively used to on-line detect the windings deformation.     

A Novel Algorithm Based on 3D-MUSIC Algorithm for Localizing Near-Field Source

A novel 3-D MUSIC algorithm based on the classical 3D-MUSIC algorithm for the location of near-field source was presented. Under the far-field assumption of actual near-field, two algebraic relations of the location parameters between the actual near-field sources and the far-field ones were derived. With Fourier transformation and polynomial-root methods, the elevation and the azimuth of the far-field were obtained, the tracking paths can be developed, and the location parameters of the near-field source can be determined, then the more accurate resuits can be estimated using an optimization method. The computer simulation results prove that the algorithm for the location of the near-fields is more accurate, effective and suitable for real-time applications.     

New Iris Localization Method Based on Chaos Genetic Algorithm

This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is used to extract the boundary of the iris. Simulation results show that the proposed algorithms is efficient and robust, and can achieve sub pixel precision. Because Genetic Algorithms (GAs) can search in a large space, the algorithm does not need accurate estimation of iris center for subsequent localization, and hence can lower the requirement for original iris image processing. On this point, the present localization algirithm is superior to Daugman‘s algorithm.     

Elliptical splats based isosurface visualization for volume data

Elliptical splats are used to represent and render the isosurface of volume data. The method consists of two steps. The first step is to extract points on the isosurface by looking up the case table. In the second step, properties of splats are computed based on local geometry. Rendering is achieved using surface splatting algorithm. The obtained results show that the extraction time of isosurfaces can be reduced by a factor of three. So our approach is more appropriate for interactive visualization of large medical data than the classical marching cubes (MC) technique.     

Optimal Genetic View Selection Algorithm for Data Warehouse

To efficiently solve the materialized view selection problem, an optimal genetic algorithm of how to select a set of views to be materialized is proposed so as to achieve both good query performance and low view maintenance cost under a storage space constraint. First, a pre-processing algorithm based on the maximum benefit per unit space is used to generate initial solutions. Then, the initial solutions are improved by the genetic algorithm having the mixture of optimal strategies. Furthermore, the generated infeasible solutions during the evolution process are repaired by loss function. The experimental results show that the proposed algorithm outperforms the heuristic algorithm and canonical genetic algorithm in finding optimal solutions.