Time complexity and convergence analysis of domain theoretic Picard method

We present an implementation of the domain-theoretic Picard method for solving initial value problems (IVPs) introduced by Edalat and Pattinson [1]. Compared to Edalat and Pattinson's implementation, our algorithm uses a more efficient arithmetic based on an arbitrary precision floating-point library. Despite the additional overestimations due to floating-point rounding, we obtain a similar bound on the convergence rate of the produced approximations. Moreover, our convergence analysis is detailed enough to allow a static optimisation in the growth of the precision used in successive Picard iterations. Such optimisation greatly improves the efficiency of the solving process. Although a similar optimisation could be performed dynamically without our analysis, a static one gives us a significant advantage: we are able to predict the time it will take the solver to obtain an approximation of a certain (arbitrarily high) quality.

Understanding policy convergence in Britain and Germany: towards a framework for analysis

This introduction considers reasons why public policies might be expected to converge between Britain and Germany, arguing that the inter-related forces of globalisation, Europeanisation, policy transfer (in various guises) and the election of centre-left governance in 1997 and 1998 could be expected to lead to such convergence. It then outlines important reasons why such convergence may not occur, due to the radically different institutional settings, as well as 'path dependence' and the resilience of established institutions all playing a role in continuing divergence in a number of important areas of public policy.

Convergence-divergence of HRM in the Asia-Pacific:context-specific analysis and future research agenda

In this article, we highlight the significance and need for conducting context-specific human resource management (HRM) research, by focusing on four critical themes. First, we discuss the need to analyze the convergence-divergence debate on HRM in Asia-Pacific. Next, we present an integrated framework, which would be very useful for conducting cross-national HRM research designed to focus on the key determinants of the dominant national HRM systems in the region. Following this, we discuss the critical challenges facing the HRM function in Asia-Pacific. Finally, we present an agenda for future research by presenting a series of research themes.

Convergence and knowledge processing in multi-agent systems

Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems.

A comparative analysis of cultural value orientations of Polish and Turkish employees:implications for international human resource management

This study empirically compares and contrasts the cultural value orientations of employees from Poland and Turkey by testing the compatibility of their values in three stages through seven cultural dimensions. The first phase of the study deals with the assessment of inter-country cultural value differences; the second phase investigates the intra-country cultural dynamics between selected demographic groups; and the third phase examines the inter-country cultural differences among the selected demographic groups of employees. The research has been conducted adopting the Maznevski, DiStephano, and Nason's (1995) version of cultural perspectives questionnaire with a sample of 744 (548 Polish and 196 Turkish) respondents. The results show significant cultural differences between Poland and Turkey, a presence of cultural dynamics among certain demographic groups within the country, and a mixture of convergence and divergence in the value systems of certain demographic groups both within and between the two nation(s). The research findings convey important messages to international human resource strategists in order for them to employ an effective and rational employment policy and business negotiation approach(es) to effectively operate in these countries. It also highlights that diversity of cultural values not only requires viewing each of them through cultural dimensions at a macro-level with a cross-country reference, but also requires monitoring their dynamics at the micro-level with reference to controlled demographic groups. © 2013 Taylor & Francis.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.