A review of studies mapping (or cross walking) from non-preference based measures of health to generic preference-based measures

This paper presents a systematic review of current practice in mapping between nonpreference based measures and generic preference-based measures. It reviews the studies identified by a systematic search of the published literature and the grey literature. This review seeks to address the feasibility and overall validity of this approach, the circumstances when it should be considered and to bring together any lessons for future mapping studies.mapping; cross walking; preference-based measures; QALYs

Performance Evaluation of Java Web Services: A Developer\u27s Perspective

With the rapid growth of traffic on the internet, further development of the web technology upon which it is based becomes extremely important. For the evolvement of Web 2.0, web services are essential. Web services are programs that allow different computer platforms to communicate interactively across the web, without the need for extra data for interfaces and formats, such as webpage structures. Since web services are a future trend for the growth of the internet, the tools used for their development are also important. Although there are many choices of web service frameworks to choose from, developers should choose the framework that best fits their applications, based on performance, time, and effort. For this project, we compared the qualitative and quantitative metrics of four common frameworks. The four frameworks were Apache Axis, JBossWS, Codehaus XFire, and Resin Hessian. After testing, the results were statistically analyzed using the Statistical Analysis System (SAS)

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60

Fault ride-through of doubly-fed induction generator with converter protection schemes

This paper from the point view of wind farm fault ride-through (FRT) capability, discusses the performance of converter protection schemes to it. Different resistor protection methods are summarized and then a new combined protection with crowbar (CB) and series dynamic resistor (SDR) is proposed. With the analysis of rotor current during fault, resistance values are calculated for practical application. The rotor high current reduction performance is simulated with MATLAB/Simulink. Fault ride-through performance including the reactive power supply, torque fluctuation and rotor speed with crowbar and series dynamic resistor are compared. The proposed method is an alternative for further protection and requirements of wind farm riding-through grid disturbances. Index Terms-Fault ride-through (FRT), Doubly-fed induction generator (DFIG), converter protection, wind generation. © 2008 IEEE

A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems

Copyright @ Springer-Verlag 2008Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining methods, called adaptive dual mapping and triggered random immigrants, respectively, are also introduced into the proposed memetic algorithm for dynamic optimization problems. Based on a series of dynamic problems generated from several stationary benchmark problems, experiments are carried out to investigate the performance of the proposed memetic algorithm in comparison with some peer evolutionary algorithms. The experimental results show the efficiency of the proposed memetic algorithm in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant Nos. 70431003 and 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, and the National Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01

Group Leaders Optimization Algorithm

We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multidimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N^2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for two qubit Grover search algorithm which is a quantum algorithm providing quadratic speed-up over the classical counterpart

Sizable suppression of magnon Hall effect by magnon damping in Cr2_2Ge2_2Te6_6

Two-dimensional (2D) Heisenberg honeycomb ferromagnets are expected to have interesting topological magnon effects as their magnon dispersion can have Dirac points. The Dirac points are gapped with finite second nearest neighbor Dzyaloshinskii-Moriya interaction, providing nontrivial Berry curvature with finite magnon Hall effect. Yet, it is unknown how the topological properties are affected by magnon damping. We report the thermal Hall effect in Cr$_2$Ge$_2$Te$_6$, an insulating 2D honeycomb ferromagnet with a large Dirac magnon gap and significant magnon damping. Interestingly, the thermal Hall conductivity in Cr$_2$Ge$_2$Te$_6$ shows the coexisting phonon and magnon contributions. Using an empirical two-component model, we successfully estimate the magnon contribution separate from the phonon part, revealing that the magnon Hall conductivity was 20 times smaller than the theoretical calculation. Finally, we suggest that such considerable suppression in the magnon Hall conductivity is due to the magnon damping effect in Cr$_2$Ge$_2$Te$_6$.Comment: 15 pages, 3 figures. Accepted for publication in Phys. Rev.