Appearance of bound states in random potentials with applications to soliton theory

We analyze the stochastic creation of a single bound state (BS) in a random potential with a compact support. We study both the Hermitian Schrödinger equation and non-Hermitian Zakharov-Shabat systems. These problems are of special interest in the inverse scattering method for Korteveg–de-Vries and the nonlinear Schrödinger equations since soliton solutions of these two equations correspond to the BSs of the two aforementioned linear eigenvalue problems. Analytical expressions for the average width of the potential required for the creation of the first BS are given in the approximation of delta-correlated Gaussian potential and additionally different scenarios of eigenvalue creation are discussed for the non-Hermitian case.

Interactions of personality variables with inductive and deductive teaching strategies

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Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.

Research on reliability evaluation of reconfigurable manufacturing system

It is a crucial task to evaluate the reliability of manufacturing process in product development process. Process reliability is a measurement of production ability of reconfigurable manufacturing system (RMS), which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. An integration framework of manufacturing process reliability evaluation is presented together with product development process. A mathematical model and algorithm based on universal generating function (UGF) is developed for calculating the reliability of manufacturing process with respect to task intensity and process capacity, which are both independent random variables. The rework strategies of RMS are analyzed under different task intensity based on process reliability is presented, and the optimization of rework strategies based on process reliability is discussed afterwards.

Random walk with restart over dynamic graphs

Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V|^3) time and O(|V|^2) memory to compute all (|V|^2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V|^3) to O(|delta|) time for each update without loss of accuracy, where |delta| (<<|V|^2) is the number of affected proximities. (2) To avoid O(|V|^2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V|) memory and O(|V|/l) I/O costs, where 1<=l<=|V| is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1–2 orders of magnitude faster than other competitors while securing scalability and exactness.

Dual-wavelength, ultralong Raman laser with Rayleigh-scattering feedback

We present experimental demonstration of a 200-km-long, dual-wavelength Raman laser utilizing two slightly different-wavelength fiber Bragg gratings, one on each side of the fiber span. The obtained results clearly prove the generation of two independent Raman lasers with a distributed “random” Rayleigh scattering mirror forming a cavity together with each of the individual fiber Bragg grating reflectors.

Optimising the diagnostic performance of the Geriatric Depression Scale

The aim of this work is to empirically generate a shortened version of the Geriatric Depression Scale (GDS), with the intention of maximising the diagnostic performance in the detection of depression compared with previously GDS validated versions, while optimizing the size of the instrument. A total of 233 individuals (128 from a Day Hospital, 105 randomly selected from the community) aged 60 or over completed the GDS and other measures. The 30 GDS items were entered in the Day Hospital sample as independent variables in a stepwise logistic regression analysis predicting diagnosis of Major Depression. A final solution of 10 items was retained, which correctly classified 97.4% of cases. The diagnostic performance of these 10 GDS items was analysed in the random sample with a receiver operating characteristic (ROC) curve. Sensitivity (100%), specificity (97.2%), positive (81.8%) and negative (100%) predictive power, and the area under the curve (0.994) were comparable with values for GDS-30 and higher compared with GDS-15, GDS-10 and GDS-5. In addition, the new scale proposed had excellent fit when testing its unidimensionality with CFA for categorical outcomes (e.g., CFI=0.99). The 10-item version of the GDS proposed here, the GDS-R, seems to retain the diagnostic performance for detecting depression in older adults of the GDS-30 items, while increasing the sensitivity and predictive values relative to other shortened versions.

Advanced mean field methods:theory and practice

A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

Individual spirit at work and its relationship with employee work attitudes and organisational outcomes:An empirical examination in corporate Thailand

The purpose of this thesis is to conduct empirical research in corporate Thailand in order to (1) validate the Spirit at Work Scale (2) investigate the relationships between individual spirit at work and three employee work attitudinal variables (job satisfaction, organisational identification and psychological well-being) and three organisational outcomes (in-role performance, organisational citizenship behaviours (OCB), and turnover intentions) (3) further examine causal relations among these organisational behaviour variables with a longitudinal design (4) examine three employee work attitudes as mediator variables between individual spirit at work and three organisational outcomes and (5) explore the potential antecedents of organisational conditions that foster employee experienced individual spirit at work. The two pilot studies with 155 UK and 175, 715 Thai samples were conducted for validation testing of the main measure used in this study: Spirit at Work Scale (Kinjerski & Skrypnek, 2006a). The results of the two studies including discriminant validity analyses strongly provided supportive evidence that Spirit at Work Scale (SAWS) is a sound psychometric measure and also a distinct construct from the three work attitude constructs. The final model of SAWS contains a total of twelve items; a three factor structure (meaning in work, sense of community, and spiritual connection) in which the sub-factors loaded on higher order factors and also had very acceptable reliability. In line with these results it was decided to use the second-order of SAWS model for Thai samples in the main study and subsequent analysis. The 715 completed questionnaires were received from the first wave of data collection during July - August 2008 and the second wave was conducted again within the same organisations and 501 completed questionnaires were received during March - April 2009. Data were obtained through 49 organisations which were from three types of organisations within Thailand: public organisations, for-profit organisations, and notfor-profit organisations. Confirmatory factor analysis of all measures used in the study and hypothesised model were tested with structural equation modelling techniques. The results were greatly supportive for the direct structural model and partially supportive for the fully mediated model. Moreover, there were different findings across self report and supervisor rating on performance and OCB models. Additionally, the antecedent conditions that fostered employees experienced individual spirit at work and the implications of these findings for research and practice are discussed.

UncertML: an XML schema for exchanging uncertainty

Authors from Burrough (1992) to Heuvelink et al. (2007) have highlighted the importance of GIS frameworks which can handle incomplete knowledge in data inputs, in decision rules and in the geometries and attributes modelled. It is particularly important for this uncertainty to be characterised and quantified when GI data is used for spatial decision making. Despite a substantial and valuable literature on means of representing and encoding uncertainty and its propagation in GI (e.g.,Hunter and Goodchild 1993; Duckham et al. 2001; Couclelis 2003), no framework yet exists to describe and communicate uncertainty in an interoperable way. This limits the usability of Internet resources of geospatial data, which are ever-increasing, based on specifications that provide frameworks for the ‘GeoWeb’ (Botts and Robin 2007; Cox 2006). In this paper we present UncertML, an XML schema which provides a framework for describing uncertainty as it propagates through many applications, including online risk management chains. This uncertainty description ranges from simple summary statistics (e.g., mean and variance) to complex representations such as parametric, multivariate distributions at each point of a regular grid. The philosophy adopted in UncertML is that all data values are inherently uncertain, (i.e., they are random variables, rather than values with defined quality metadata).

A DEA model for units with negative data

In this paper we propose an alternative method for measuring efficiency of Decision making Units, which allows the presence of variables with both negative and positive values. The model is applied to data on the notional effluent processing system to compare the results with recent developed methods; Modified Slacks Based Model as suggested by Sharp et al (2007) and Range Directional Measures developed by Silva Portela et al (2004). A further example explores advantages of using the new model.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Managerial job satisfaction:a longitudinal study

The study examines the job satisfaction of supervisors and managers in four organisations over time. It also considers the importance which they attached to different facets of their job. The major objectives were: To examine the constituent dimensions of job satisfaction at intervals over one year. To examine reasons for change inthe level of job satisfaction at intervals over one year. To provide information on job satisfaction for those concerned with job satisfaction policies. The sample consisted of one hundred and eight people. Each was interviewed on at least three occasions over the course of a year. Interviews took place at predetermined time intervals. The study shows that job satisfaction is dynamic over a relatively short period of time. The ratings which supervisors and managers gave to aspects of their job did not, however, all change by equal amounts or in the same direction. Changes in job satisfaction were associated with events experienced but it was the meaning of those events to correspondents which appeared to be particularly important. People tended to adopt a localised frame of reference when considering their work situation. Certain job variables, such as variety, were consistently and positively correlated with job satisfaction. With some other variables, the relationship varied across time. Frequently, age and job level moderated the association between independent variables and job satisfaction. Links were found between the quality of life and job satisfaction. There was a consistent positive association between job satisfaction and life satisfaction. However, the job was rarely considered to be the main factor contributing to a person's quality of life. The research highlights the difficulties and desirability of introducing standardised job satisfaction policies in the light of individual differences. In addition, it demonstrates that merely correlating variables with job satisfaction at one point in time may conceal complex relationships and meanings. A new measure of job satisfaction - whereby facets are assessed and rated relative to each other was also developed as part of this study.

Random walks in local dynamics of network losses

We suggest a model for data losses in a single node (memory buffer) of a packet-switched network (like the Internet) which reduces to one-dimensional discrete random walks with unusual boundary conditions. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that for a finite-capacity buffer at the critical point the loss rate exhibits strong fluctuations and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process.

Selling, resistance and reconciliation:a critical discursive approach to subsidiary role evolution in MNEs

Studies of political dynamics between multinational enterprise (MNE) parents and subsidiaries during subsidiary role evolution have focused largely on control and resistance. This paper adopts a critical discursive approach to enable an exploration of subtle dynamics in the way that both headquarters and subsidiaries subjectively reconstruct their independent-interdependent relationships with each other during change. We draw from a real-time qualitative study of a revealing case of charter change in an important European subsidiary of an MNE attempting to build closer integration across European country operations. Our results illustrate the role of three discourses – selling, resistance and reconciliation – in the reconstruction of the subsidiary–parent relationship. From this analysis we develop a process framework that elucidates the important role of these three discourses in the reconstruction of subsidiary roles, showing how resistance is not simply subversive but an important part of integration. Our findings contribute to a better understanding of the micro-level political dynamics in subsidiary role evolution, and of how voice is exercised in MNEs. This study also provides a rare example of discourse-based analysis in an MNE context, advancing our knowledge of how discursive methods can help to advance international business research more generally.