A loop-shaping approach to intelligent control

In this paper, we propose a loop-shaping approach to in telligent control with dynamically constructed neurocon troller. In the proposed control scheme, the process uncer tainly is reduced in the controller rather than in the process, without explicit identification of the process under control. The inherent noise/distrurbances in the process are utilized to satisfy persistency of excitation condition. The use of a reference model in form of a filter allow the frequency response of the closed-loop to be adapted in line with the changes in frequency response of the filter. The approach is evaluated on the example of control of polymerization reactor with promising results.

How do critical care nurses define the discharge planning process?

Background: Professional, political and organisational factors have focused attention on the discharge planning process in the Victorian health care sector. Discharge planning for patients, as part of continuity of care, is seen as a key concept in the delivery of nursing care. However, there is no question that discharge planning has emerged as a complex area of practice, and is, perhaps, most complex in the critical care area.

Aim: The study reported here is part of a larger thesis exploring critical care nurses’ perceptions and understanding of the discharge planning process in the health care system in the state of Victoria, Australia. As part of the survey participants were asked to define discharge planning as it related to the critical care environment in which they worked.

Methods: Utilising an exploratory descriptive approach, 502 Victorian critical care nurses were approached to take part in the study. The resultant net total of 218 participants completed the survey, which represented a net response rate of 43.4%. The data were analysed using quantitative and qualitative methodologies.

Findings: Three common themes emerged. A significant number of participants did not believe that discharge planning occurred in critical care, and therefore, thought that they could not provide a definition. There was uncertainty as to what the discharge planning process actually referred to in terms of discharge from critical care to the general ward or discharge from the hospital. There was an emphasis on movement of the patient to the general ward, which was considered in three main ways by first, getting the patient ready for transfer; second, ensuring a smooth transition to the ward and third, transfer of the patient to the ward often occurred because the critical care bed was needed for another patient.

Conclusion: The findings presented here suggest at a nursing level, the discharge planning process is not well understood and some degree of mutual exclusivity still remains. There is a need for further education of critical care nurses with regard to the underlying principles of the discharge planning process.

Conceptual framework of the precautionary principle approach in the decision-making process

This article reviews the precautionary principle as an approach in addressing decisions with far reaching environmental consequences under scientific uncertainty. The precautionary principle is intended to assist with structuring environmentally risky decisions toward sustainable development. It responds to the lack of scientific evidence of a potential environmental problem. There is currently no framework to assist with the process indicating the areas of importance and stages of decisionmaking. This paper suggests a framework to assist with the process of decision-making for complex environmental problems. The main areas of concern are the issues relating to the costs, risks, and benefits assessments. The main stages of the framework includes; definition of the problem, analysis of the potential environmental risks, assessments of specific anticipated legal, social, economic, political, and technological impacts, review of the key players (social, organisation and government) obligations, comparison of alternatives available, determination of accountability, implementation, decision making, monitoring and control processes.

The use of analytic hierarchy process to incorporate stakeholder preferences into regional forest planning

Forest management decisions are often characterised by complexity, irreversibility and uncertainty. Much of the complexity arises from the multiple-use nature of forest goods and services, difficulty in monetary valuation of ecological services and the involvement of numerous stakeholders. Under these circumstances, conventional methods such as cost-benefit analysis are ill-suited to evaluate forest decisions. The Analytic Hierarchy Process (AHP), can be useful in regional forest planing as it can accommodate conflictual, multidimensional, incommensurable and incomparable set of objectives. The objective of this paper is to examine the scope and feasibility of the AHP in incorporating stakeholder preferences into regional forest planning. The Australian Regional Forest Agreement Programme is taken as an illustrative case for the analysis. The results show that the AHP can formalize public participation in decision making and increase the transparency and the credibility of the process.

Technology uncertainty and market collusion

In this paper, we propose technology uncertainty as a new factor relevant to market collusion. We analyze an infinitely repeated quantity game where, for each firm, the marginal productivity of the input employed in the production process is affected by an unobservable shock. Each firm faces technology uncertainty, measured by the variance of the shocks, in every period. We show that, under both grim trigger strategies and optimal punishments, technology uncertainty enhances cartel stability, suggesting that, in industries characterized by technology uncertainty, the actions of the antitrust authorities should be intensified. We also show that collusion is less likely when technology shocks are highly correlated, implying that regulators interested in deterring collusion should promote the formation of industrial clusters.

The effects of perceived business uncertainty, external consultants and risk management on organisational outcomes

Purpose – The purpose of this paper is to investigate the relations between perceived business uncertainty (PBU), use of external risk management (RM) consultants, formalisation of RM, magnitude of RM methods and perceived organisational outcomes.
Design/methodology/approach – This paper is based on a questionnaire survey of members of the Chartered Institute of Management Accountants in the UK. Using AMOS 17.0, the paper tests the strength of the direct and indirect effects among the variables and explores the fit of the overall path model.
Findings – The results indicate significant and positive associations exist between the extent of PBU and the level ofRMformalisation, as well as between the level ofRMformalisation and the magnitude of RMmethods adopted. The use of externalRMconsultants is also found to have a significant and positive impact on the magnitude of RM methods adopted. Finally, both the extent of RM formalisation and the magnitude of RM methods adopted are seen to be significantly associated with overall improvement in organisational outcomes.
Research limitations/implications – The study uses perceptual measures of the level of business uncertainty, usage of RM and organisational outcomes. Further, the respondents are members of a management accounting professional body and the views of other managers, such as risk managers, who are also important to the governance process are not incorporated.
Originality/value – This study provides empirical evidence on the impact ofRMdesign and usage on improvements in organisational outcomes. It contributes to the RM literature where empirical research is needed in order to be comparable with the traditional management control system literature.

Critical uncertainty factors for efficient risk allocation in privately financed public infrastructure projects in Australia

Risk allocation in privately financed public infrastructure projects, commonly referred to as public-private partnership (PPP) projects, is a challenging job due to the nature of incomplete contracting. Choosing a risk allocation strategy could be viewed as the process of deciding the proportion of risk management attributable to the public and private partners based on a series of characteristics of the risk management service transaction in question. These characteristics can be related to the various uncertainty factors. In this study, uncertainty factors have been grouped into Institutional, Social and industrial, Economic, and Project-specific categories and examined in order to achieve efficient risk allocation and minimize risk management-related costs in a long-term view. Critical uncertainty factors for the allocation of three major risks have been identified through an industry-wide survey in Australia. These identified critical uncertainty factors are expected to help decision-makers from both public and private sectors choose efficient allocation strategies for major risks. Future research directions are also set out.

Critical uncertainty factors for efficient allocation of demand risk in privately financed public infrastructure projects in Australia

Risk allocation in privately financed public infrastructure projects, which are mainly referred as public-private partnership (PPP) projects, is a challenging job due to the nature of incomplete contracting. Among the various risks that may eventually materialise, demand risk is one of the major challenges that PPPs face. Choosing a risk allocation strategy could be viewed as the process of deciding the proportion of risk management responsibility between public and private partners based on a series of characteristics of risk management service transaction in question. These characteristics are more or less related to the various uncertainty factors. In this study, various uncertainty factors have been examined in order to achieve efficient allocation of demand risk and minimise risk management-related costs in a long-term view. Critical uncertainty factors have been identified through an industry-wide survey in Australia. Future research directions are also set out.

Insulin entry into muscle involves a saturable process in the vascular endothelium

Aims/hypothesis : Insulin's rate of entry into skeletal muscle appears to be the rate-limiting step for muscle insulin action and is slowed by insulin resistance. Despite its obvious importance, uncertainty remains as to whether the transport of insulin from plasma to muscle interstitium is a passive diffusional process or a saturable transport process regulated by the insulin receptor. Methods : To address this, here we directly measured the rate of 125I-labelled insulin uptake by rat hindlimb muscle and examined how that is affected by adding unlabelled insulin at high concentrations. We used mono-iodinated [125I]TyrA14-labelled insulin and short (5 min) exposure times, combined with trichloroacetic acid precipitation, to trace intact bioactive insulin. Results : Compared with saline, high concentrations of unlabelled insulin delivered either continuously (insulin clamp) or as a single bolus, significantly raised plasma 125I-labelled insulin, slowed the movement of 125I-labelled insulin from plasma into liver, spleen and heart (p < 0.05, for each) but increased kidney 125I-labelled insulin uptake. High concentrations of unlabelled insulin delivered either continuously (insulin clamp), or as a single bolus, significantly decreased skeletal muscle 125I-labelled insulin clearance (p < 0.01 for each). Increasing muscle perfusion by electrical stimulation did not prevent the inhibitory effect of unlabelled insulin on muscle 125I-labelled insulin clearance. Conclusions/interpretation : These results indicate that insulin's trans-endothelial movement within muscle is a saturable process, which is likely to involve the insulin receptor. Current findings, together with other recent reports, suggest that trans-endothelial insulin transport may be an important site at which muscle insulin action is modulated in clinical and pathological settings.

Minimizing impact of bounded uncertainty on McNaughton's scheduling algorithm via interval programming

Uncertainty of data affects decision making process as it increases the risk and the costs of the decision. One of the challenges in minimizing the impact of the bounded uncertainty on any scheduling algorithm is the lack of information, as only the upper bound and the lower bound are provided without any known probability or membership function. On the contrary, probabilistic uncertainty can use probability distributions and fuzzy uncertainty can use the membership function. McNaughton's algorithm is used to find the optimum schedule that minimizes the makespan taking into consideration the preemption of tasks. The challenge here is the bounded inaccuracy of the input parameters for the algorithm, namely known as bounded uncertain data. This research uses interval programming to minimise the impact of bounded uncertainty of input parameters on McNaughton’s algorithm, it minimises the uncertainty of the cost function estimate and increase its optimality. This research is based on the hypothesis that doing the calculations on interval values then approximate the end result will produce more accurate results than approximating each interval input then doing numerical calculations.

Developing an analytical framework to assess the uncertainty and flexibility mismatches across the supply chain

Purpose: The purpose of this paper is to discuss how decisions regarding organisational flexibility can be improved through targeted resource allocation, by focusing on the supply chain's level of uncertainty exposure. Specifically, the issue of where and in what ways flexibility has been incorporated across the organisation's supply chain is addressed. Design/methodology/approach: A two-phase methodology design based on literature review and case study was used. Using 83 journal articles in the areas of uncertainty and flexibility an analytical process for assessing uncertainty-flexibility mismatches was developed. Furthermore, results from ten interviews with senior/middle managers within the Australian manufacturing sector were used to provide preliminary insights on the usefulness and importance of the analytical process and its relationship with organisational practice. Findings: The paper emphasises the importance of having a systematic and encompassing view of uncertainty-flexibility mismatches across the supply chain, as well as the significance of socio-technical engagement. The paper both conceptually and empirically illustrates how, using a structured analytical process, flexibility requirements across the supply, process, control and demand segments of a supply chain might be assessed. A four-step analytical process was accordingly developed and, its application, usefulness and importance discussed using empirical data. Practical implications: The analytical process presented in this paper can assist managers to obtain a comprehensive overview of supply chain flexibility when dealing with situations involving uncertainty. This can facilitate and improve their decision-making with respect to prioritising attention on identified flexibility gaps in order to ensure stability of their performance. Originality/value: The paper presents a supply chain-wide discussion on the difficulties that uncertainty brings to organisations, and how organisational flexibility might serve to moderate those challenges for supply chain management. It discusses how to identify the flexibility gap and proposes an original analytical process for systematic assessment of uncertainty-flexibility mismatches. © Emerald Group Publishing Limited.

Extending scheduling algorithms to minimise the impact of bounded uncertainty using interval programming

 This research proposed a new methodology to extend algorithms to accept interval-based uncertain parameters. The methodology is applied on scheduling algorithms, including heuristic and meta-heuristic algorithms and produced optimal results with higher accuracy. The research outcomes are effective for decision making process using uncertain or predicted data.

Stochastic optimization models for energy management in carbonization process of carbon fiber production

Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.

Communication of scientific uncertainty: International case studies on the development of folate and vitamin D Dietary Reference Values

Objective Transparent evidence-based decision making has been promoted worldwide to engender trust in science and policy making. Yet, little attention has been given to transparency implementation. The degree of transparency (focused on how uncertain evidence was handled) during the development of folate and vitamin D Dietary Reference Values was explored in three a priori defined areas: (i) value request; (ii) evidence evaluation; and (iii) final values. Design Qualitative case studies (semi-structured interviews and desk research). A common protocol was used for data collection, interview thematic analysis and reporting. Results were coordinated via cross-case synthesis. Setting Australia and New Zealand, Netherlands, Nordic countries, Poland, Spain and UK. Subjects Twenty-one interviews were conducted in six case studies. Results Transparency of process was not universally observed across countries or areas of the recommendation setting process. Transparency practices were most commonly seen surrounding the request to develop reference values (e.g. access to risk manager/assessor problem formulation discussions) and evidence evaluation (e.g. disclosure of risk assessor data sourcing/evaluation protocols). Fewer transparency practices were observed to assist with handling uncertainty in the evidence base during the development of quantitative reference values. Conclusions Implementation of transparency policies may be limited by a lack of dedicated resources and best practice procedures, particularly to assist with the latter stages of reference value development. Challenges remain regarding the best practice for transparently communicating the influence of uncertain evidence on the final reference values. Resolving this issue may assist the evolution of nutrition risk assessment and better inform the recommendation setting process.

Making conservation decisions under uncertainty for the persistence of multiple species

Population models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but
they are inevitably uncertain. Is it possible to use population models in multiple-speciesconservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.