Optimal design for correlated processes with input-dependent noise

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

A linear relational DEA model to evaluate two-stage processes with shared inputs

Two-stage data envelopment analysis (DEA) efficiency models identify the efficient frontier of a two-stage production process. In some two-stage processes, the inputs to the first stage are shared by the second stage, known as shared inputs. This paper proposes a new relational linear DEA model for dealing with measuring the efficiency score of two-stage processes with shared inputs under constant returns-to-scale assumption. Two case studies of banking industry and university operations are taken as two examples to illustrate the potential applications of the proposed approach.

Mathematical modelling and optimal multivariable control of chemical processes

This work reports the developnent of a mathenatical model and distributed, multi variable computer-control for a pilot plant double-effect climbing-film evaporator. A distributed-parameter model of the plant has been developed and the time-domain model transformed into the Laplace domain. The model has been further transformed into an integral domain conforming to an algebraic ring of polynomials, to eliminate the transcendental terms which arise in the Laplace domain due to the distributed nature of the plant model. This has made possible the application of linear control theories to a set of linear-partial differential equations. The models obtained have well tracked the experimental results of the plant. A distributed-computer network has been interfaced with the plant to implement digital controllers in a hierarchical structure. A modern rnultivariable Wiener-Hopf controller has been applled to the plant model. The application has revealed a limitation condition that the plant matrix should be positive-definite along the infinite frequency axis. A new multi variable control theory has emerged fram this study, which avoids the above limitation. The controller has the structure of the modern Wiener-Hopf controller, but with a unique feature enabling a designer to specify the closed-loop poles in advance and to shape the sensitivity matrix as required. In this way, the method treats directly the interaction problems found in the chemical processes with good tracking and regulation performances. Though the ability of the analytical design methods to determine once and for all whether a given set of specifications can be met is one of its chief advantages over the conventional trial-and-error design procedures. However, one disadvantage that offsets to some degree the enormous advantages is the relatively complicated algebra that must be employed in working out all but the simplest problem. Mathematical algorithms and computer software have been developed to treat some of the mathematical operations defined over the integral domain, such as matrix fraction description, spectral factorization, the Bezout identity, and the general manipulation of polynomial matrices. Hence, the design problems of Wiener-Hopf type of controllers and other similar algebraic design methods can be easily solved.

The impact of ageing and gender on visual mental imagery processes:a study of performance on tasks from the Complete Visual Mental Imagery Battery (CVMIB)

In this study we aim to evaluate the impact of ageing and gender on different visual mental imagery processes. Two hundred and fifty-one participants (130 women and 121 men; age range = 18–77 years) were given an extensive neuropsychological battery including tasks probing the generation, maintenance, inspection, and transformation of visual mental images (Complete Visual Mental Imagery Battery, CVMIB). Our results show that all mental imagery processes with the exception of the maintenance are affected by ageing, suggesting that other deficits, such as working memory deficits, could account for this effect. However, the analysis of the transformation process, investigated in terms of mental rotation and mental folding skills, shows a steeper decline in mental rotation, suggesting that age could affect rigid transformations of objects and spare non-rigid transformations. Our study also adds to previous ones in showing gender differences favoring men across the lifespan in the transformation process, and, interestingly, it shows a steeper decline in men than in women in inspecting mental images, which could partially account for the mixed results about the effect of ageing on this specific process. We also discuss the possibility to introduce the CVMIB in clinical assessment in the context of theoretical models of mental imagery.

The MISLEM Project : developing meta-level quality indicators for establishing a systematic linkage between educational institutions and the labour market:education, employment and graduate employability: project manual

The MISLEM Project comprised representatives from Higher and Vocational Education in four partner countries, Austria, Romania, Slovenia and the UK. In addition to this, representatives from a major UK graduate employment agency and the Austria Quality Assurance Agency were also involved. At the inaugural meeting of the Project, partner teams discussed and agreed upon appropriate methodological processes with which to carry the Project forward.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Probability distribution modelling to improve stability in nonlinear MIMO control

We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

The analysis and case studies of successful express logistics companies

With the globalisation of world business, the border-crossing activities between organisations have substantially increased. Organisations not only need to handle supply functions, but also play a tremendous role in demand simulation through integration both inside the firm and outside with business partners and customers. Logistics has become more and more mature and sophisticated by taking on an external focus, incorporating suppliers and customers in the business processes, with all the supply chain functions integrated into a whole. By minimising the costs in the value chain or providing customised services, logistics acts as a major source of competitive advantages and profitability. To meet this goal, it would require the integration of activities to focus on customer-oriented measures. Customer service and logistics activities are a chain of interdependent activities that supplement each other to facilitate the flow of information, goods and cash within the value chain. The absence of one activity may imply some specific channels need to supplement another unit. Generally, this paper is to study the impact of corporate strategy, technology and customer satisfaction on the firm’s performance, filling the gap of good customer service effects on long-term profits. Two international delivery providers, UPS and FedEx, are studied to realise the critical success factors of express logistics.

Response:Ideas are ten a penny - It's team implementation not idea generation that counts

Cet article présente une synthèse des recherches et théories qui éclairent notre compréhension de la créativité et de la mise en oeuvre de l’innovation dans les groupes de travail. Il semble que la créativité apparaisse essentiellement au cours des premières étapes du processus, avant la mise en oeuvre. On étudie l’influence des caractéristiques de la tâche, des capacités et de l’éventail des connaissances du groupe, des demandes externes, des mécanismes d’intégration et de cohérence de groupe. La perception d’une menace, l’incertitude ou de fortes exigences entravent la créativité, mais favorisent l’innovation. La diversité des connaissances et des capacités est un bon prédicteur de l’innovation, mais l’intégration du groupe et les compétences sont indispensables pour récolter les fruits de la diversité. On examine aussi les implications théoriques et pratiques de ces considérations. In this article I synthesise research and theory that advance our understanding of creativity and innovation implementation in groups at work. It is suggested that creativity occurs primarily at the early stages of innovation processes with innovation implementation later. The influences of task characteristics, group knowledge diversity and skill, external demands, integrating group processes and intragroup safety are explored. Creativity, it is proposed, is hindered whereas perceived threat, uncertainty or other high levels of demands aid the implementation of innovation. Diversity of knowledge and skills is a powerful predictor of innovation, but integrating group processes and competencies are needed to enable the fruits of this diversity to be harvested. The implications for theory and practice are also explored.

Sparkling fountains or stagnant ponds:An integrative model of creativity and innovation implementation in work groups

In this article I synthesise research and theory that advance our understanding of creativity and innovation implementation in groups at work. It is suggested that creativity occurs primarily at the early stages of innovation processes with innovation implementation later. The influences of task characteristics, group knowledge diversity and skill, external demands, integrating group processes and intragroup safety are explored. Creativity, it is proposed, is hindered whereas perceived threat, uncertainty or other high levels of demands aid the implementation of innovation. Diversity of knowledge and skills is a powerful predictor of innovation, but integrating group processes and competencies are needed to enable the fruits of this diversity to be harvested. The implications for theory and practice are also explored.

Measuring the operational performance of intensive care units using the analytic hierarchy process approach

Purpose - The purpose of this study is to develop a performance measurement model for service operations using the analytic hierarchy process approach. Design/methodology/approach - The study reviews current relevant literature on performance measurement and develops a model for performance measurement. The model is then applied to the intensive care units (ICUs) of three different hospitals in developing nations. Six focus group discussions were undertaken, involving experts from the specific area under investigation, in order to develop an understandable performance measurement model that was both quantitative and hierarchical. Findings - A combination of outcome, structure and process-based factors were used as a foundation for the model. The analyses of the links between them were used to reveal the relative importance of each and their associated sub factors. It was considered to be an effective quantitative tool by the stakeholders. Research limitations/implications - This research only applies the model to ICUs in healthcare services. Practical implications - Performance measurement is an important area within the operations management field. Although numerous models are routinely being deployed both in practice and research, there is always room for improvement. The present study proposes a hierarchical quantitative approach, which considers both subjective and objective performance criteria. Originality/value - This paper develops a hierarchical quantitative model for service performance measurement. It considers success factors with respect to outcomes, structure and processes with the involvement of the concerned stakeholders based upon the analytic hierarchy process approach. The unique model is applied to the ICUs of hospitals in order to demonstrate its effectiveness. The unique application provides a comparative international study of service performance measurement in ICUs of hospitals in three different countries. © Emerald Group Publishing Limited.

Pragmatic approach to the development of robust real-time protocols

This research is concerned with the development of distributed real-time systems, in which software is used for the control of concurrent physical processes. These distributed control systems are required to periodically coordinate the operation of several autonomous physical processes, with the property of an atomic action. The implementation of this coordination must be fault-tolerant if the integrity of the system is to be maintained in the presence of processor or communication failures. Commit protocols have been widely used to provide this type of atomicity and ensure consistency in distributed computer systems. The objective of this research is the development of a class of robust commit protocols, applicable to the coordination of distributed real-time control systems. Extended forms of the standard two phase commit protocol, that provides fault-tolerant and real-time behaviour, were developed. Petri nets are used for the design of the distributed controllers, and to embed the commit protocol models within these controller designs. This composition of controller and protocol model allows the analysis of the complete system in a unified manner. A common problem for Petri net based techniques is that of state space explosion, a modular approach to both the design and analysis would help cope with this problem. Although extensions to Petri nets that allow module construction exist, generally the modularisation is restricted to the specification, and analysis must be performed on the (flat) detailed net. The Petri net designs for the type of distributed systems considered in this research are both large and complex. The top down, bottom up and hybrid synthesis techniques that are used to model large systems in Petri nets are considered. A hybrid approach to Petri net design for a restricted class of communicating processes is developed. Designs produced using this hybrid approach are modular and allow re-use of verified modules. In order to use this form of modular analysis, it is necessary to project an equivalent but reduced behaviour on the modules used. These projections conceal events local to modules that are not essential for the purpose of analysis. To generate the external behaviour, each firing sequence of the subnet is replaced by an atomic transition internal to the module, and the firing of these transitions transforms the input and output markings of the module. Thus local events are concealed through the projection of the external behaviour of modules. This hybrid design approach preserves properties of interest, such as boundedness and liveness, while the systematic concealment of local events allows the management of state space. The approach presented in this research is particularly suited to distributed systems, as the underlying communication model is used as the basis for the interconnection of modules in the design procedure. This hybrid approach is applied to Petri net based design and analysis of distributed controllers for two industrial applications that incorporate the robust, real-time commit protocols developed. Temporal Petri nets, which combine Petri nets and temporal logic, are used to capture and verify causal and temporal aspects of the designs in a unified manner.

Learning in ultrametric committee machines

The problem of learning by examples in ultrametric committee machines (UCMs) is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error in UCMs with L hidden layers and for a large enough number of units. In most of the regimes studied we find that the generalization error, as a function of the number of examples presented, develops a discontinuous drop at a critical value of the load parameter. We also find that when L>1 a number of teacher networks with the same number of hidden layers and different overlaps induce learning processes with the same critical points.

B2B e-marketplaces in the airline industry:process drivers and performance indicators

Competitive pressures are increasing within and between different strategically oriented groups of airlines. This paper focuses on the level of efficiency improvements gained by using e-Marketplaces in the procurement process. Findings from a survey among 88 international airlines reveal that the use of Business-to-Business (B2B) e-Marketplaces does play different roles across the various airline groupings. Airlines that are involved in strategic alliances show higher joint procurement activities than airlines that are not involved in strategic alliances. However, alliances are probably viewed as loose arrangements and thus airlines may be reluctant to share information on procurement prices and processes with another airline that could also be acting as a competitor. The financial involvement in or initiation of e-Marketplaces by airlines is very low. Low cost airlines show high use of e-Marketplaces, but demonstrate little financial involvement in contrast. Overall, the categories of spares and repairs, office supplies, tools and ground support equipment (GSE) show the greatest potential for reducing costs and increasing procurement process efficiencies. The intense competitive pressures facing carriers will make their search for tools to realise even incremental savings and efficiency gains ever more urgent. There is evidence that e-Marketplaces are one tool to improve such performance indicators.

Investigating the influence of African American and African Caribbean race on primary care doctors' decision making about depression

This paper explores differences in how primary care doctors process the clinical presentation of depression by African American and African-Caribbean patients compared with white patients in the US and the UK. The aim is to gain a better understanding of possible pathways by which racial disparities arise in depression care. One hundred and eight doctors described their thought processes after viewing video recorded simulated patients presenting with identical symptoms strongly suggestive of depression. These descriptions were analysed using the CliniClass system, which captures information about micro-components of clinical decision making and permits a systematic, structured and detailed analysis of how doctors arrive at diagnostic, intervention and management decisions. Video recordings of actors portraying black (both African American and African-Caribbean) and white (both White American and White British) male and female patients (aged 55 years and 75 years) were presented to doctors randomly selected from the Massachusetts Medical Society list and from Surrey/South West London and West Midlands National Health Service lists, stratified by country (US v.UK), gender, and years of clinical experience (less v. very experienced). Findings demonstrated little evidence of bias affecting doctors' decision making processes, with the exception of less attention being paid to the potential outcomes associated with different treatment options for African American compared with White American patients in the US. Instead, findings suggest greater clinical uncertainty in diagnosing depression amongst black compared with white patients, particularly in the UK. This was evident in more potential diagnoses. There was also a tendency for doctors in both countries to focus more on black patients' physical rather than psychological symptoms and to identify endocrine problems, most often diabetes, as a presenting complaint for them. This suggests that doctors in both countries have a less well developed mental model of depression for black compared with white patients. © 2014 The Authors.