A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

A new approach to control of MIMO processes with static nonlinearities using an extended IMC framework

In this paper, a new control design method is proposed for stable processes which can be described using Hammerstein-Wiener models. The internal model control (IMC) framework is extended to accommodate multiple IMC controllers, one for each subsystem. The concept of passive systems is used to construct the IMC controllers which approximate the inverses of the subsystems to achieve dynamic control performance. The Passivity Theorem is used to ensure the closed-loop stability. (c) 2005 Elsevier Ltd. All rights reserved.

A Research Agenda for Assessing the Potential Contribution of Genomic Medicine to Tobacco Control

This paper identifies research priorities in evaluating the ways in which "genomic medicine"-the use of genetic information to prevent and treat disease-may reduce tobacco-related harm by: (1) assisting more smokers to quit; (2) preventing non-smokers from beginning to smoke tobacco; and (3) reducing the harm caused by tobacco smoking. The method proposed to achieve the first aim is pharmacogenetics", the use of genetic information to optimise the selection of smoking-cessation programmes by screening smokers for polymorphisms that predict responses to different methods of smoking cessation. This method competes with the development of more effective forms of smoking cessation that involve vaccinating smokers against the effects of nicotine and using new pharmaceuticals (such as cannabinoid antagonists and nicotine agonists). The second and third aims are more speculative. They include: screening the population for genetic susceptibility to nicotine dependence and intervening (eg, by vaccinating children and adolescents against the effects of nicotine) to prevent smoking uptake, and screening the population for genetic susceptibility to tobacco-related diseases. A framework is described for future research on these policy options. This includes: epidemiological modelling and economic evaluation to specify the conditions under which these strategies are cost-effective; and social psychological research into the effect of providing genetic information on smokers' preparedness to quit, and the general views of the public on tobacco smoking.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Environmental control of potential yield of sunflower in the subtropics

A simple framework was used to analyse the determinants of potential yield of sunflower (Helianthus annuus L.) in a subtropical environment. The aim was to investigate the stability of the determinants crop duration, canopy light interception, radiation use efficiency (RUE), and harvest index (HI) at 2 sowing times and with 3 genotypes differing in crop maturity and stature. Crop growth, phenology, light interception, yield, prevailing temperature, and radiation were recorded and measured throughout the crop cycle. Significant differences in grain yield were found between the 2 sowings, but not among genotypes within each sowing. Mean yields (0% moisture) were 6 . 02 and 2 . 17 t/ha for the first sowing, on 13 September (S1), and the second sowing, on 5 March (S2), respectively. Exceptionally high yields in S1 were due to high biomass assimilation associated with the high radiation environment, high light interception owing to a greater leaf area index, and high RUE (1 . 47-1 . 62 g/MJ) across genotypes. It is proposed that the high RUE was caused by high levels of available nitrogen maintained during crop growth by frequent applications of fertiliser and sewage effluent as irrigation. In addition to differences in the radiation environment, the assimilate partitioned to grain was reduced in S2 associated with a reduction in the duration of grain-filling. Harvest index was 0 . 40 in S1 and 0 . 25 in S2. It is hypothesised that low minimum temperatures experienced in S2 reduced assimilate production and partitioning, causing premature maturation.

Differences between older volunteers and nonvolunteers - Attitudinal, normative, and control beliefs

It has been suggested that older people are a rich potential source of volunteers, as prior literature has highlighted the benefits and rewards of volunteering in later life. This article examines differences between volunteers and nonvolunteers in a random sample of older people resident in Brisbane, Australia. Using the theory of planned behavior as a framework, the article focuses on the beliefs that distinguish those who volunteer from those who do not. Findings from the study allowed for an assessment of both the costs and benefits associated with volunteering; beliefs about the support of others, including the broader community, to volunteer; and beliefs about the barriers that might prevent volunteering. The implications of these finding's to a country with an aging population are discussed.

A Framework of Fuzzy Diagnosis

Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent eLearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e. g., the fault diagnosis of student behaviors in the eLearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, Fuzzy Diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the Fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world eLearning case is described to demonstrate the application of our diagnostic framework.

A framework for diagnosing board effectiveness

Pressure on boards to improve corporate performance and management oversight has led to a series of inquiries and reports advocating governance reform. These reports largely reflect an agency perspective of governance and seek to ensure greater board independence from and control of management. While board independence is important to good governance, we contend that frameworks, models and advice centred on one element of governance ignore the complexity of how boards work. We develop a holistic board framework based upon the concept of board intellectual capital to address this concern. Our framework proposes a series of inputs (e.g. company history, company constitution, legal environment) that lead to a particular mix of board intellectual capital. We contend that the balance of the different elements of board intellectual capital will lead to a series of board behaviours. Further, the board needs to mobilise its intellectual capital to carry out a series of roles. The exact nature of these roles will depend on the company's requirements. Thus, the governance outputs of organisational performance, board effectiveness and director effectiveness will depend on the match between the board's intellectual capital and the roles required of it. We conclude by demonstrating the benefits of this framework as a diagnostic tool. We outline how boards wishing to improve their governance systems can diagnose common governance problems by evaluating their own board's capabilities in relation to the different components of the framework.

Adsorption of N-2, Ar, acetone, chloroform and acetone-chloroform mixture on carbon black in the framework of molecular layer structure theory (MLST)

Adsorption of pure nitrogen, argon, acetone, chloroform and acetone-chloroform mixture on graphitized thermal carbon black is considered at sub-critical conditions by means of molecular layer structure theory (MLST). In the present version of the MLST an adsorbed fluid is considered as a sequence of 2D molecular layers, whose Helmholtz free energies are obtained directly from the analysis of experimental adsorption isotherm of pure components. The interaction of the nearest layers is accounted for in the framework of mean field approximation. This approach allows quantitative correlating of experimental nitrogen and argon adsorption isotherm both in the monolayer region and in the range of multi-layer coverage up to 10 molecular layers. In the case of acetone and chloroform the approach also leads to excellent quantitative correlation of adsorption isotherms, while molecular approaches such as the non-local density functional theory (NLDFT) fail to describe those isotherms. We extend our new method to calculate the Helmholtz free energy of an adsorbed mixture using a simple mixing rule, and this allows us to predict mixture adsorption isotherms from pure component adsorption isotherms. The approach, which accounts for the difference in composition in different molecular layers, is tested against the experimental data of acetone-chloroform mixture (non-ideal mixture) adsorption on graphitized thermal carbon black at 50 degrees C. (C) 2005 Elsevier Ltd. All rights reserved.

Explaining landholders' decisions about riparian zone management: The role of behavioural, normative, and control beliefs

Water quality is a key concern in the current global environment, with the need to promote practices that help to protect water quality, such as riparian zone management, being paramount. The present study used the theory of planned behaviour as a framework for understanding how beliefs influence decisions about riparian zone management. Respondents completed a survey that assessed their behavioural, normative, and control beliefs in relation to intentions to manage riparian zones on their property. The results of the study showed that, overall, landholders with strong intentions to manage their riparian zones differed significantly in terms of their beliefs compared to landholders who had weak intentions to manage their riparian zones. Strong intentions to manage riparian zones were associated with a favourable cost-benefit analysis, greater perceptions of normative support for the practice and lower perceptions of the extent to which barriers would impede management of riparian zones. It was also evident that willingness to comply with the recommendations of salient referents, beliefs about the benefits of riparian zone management and perceptions of the extent to which barriers would impede riparian zone management were most important for determining intentions to manage riparian zones. Implications for policy and extension practice are discussed. (c) 2005 Elsevier Ltd. All rights reserved.

A software audit framework for spyware risk mitigation

Our research described in this paper identifies a three part premise relating to the spyware paradigm. Firstly the data suggests spyware is proliferating at an exponential rate. Secondly ongoing research confirms that spyware produces many security risks – including that of privacy/confidentiality breaches via illicit data collection and reporting. Thirdly, anti-spyware controls are improving but are still considered problematic for several reasons. Our research then concludes that control measures to counter this very significant challenge should merit compliance auditing – and this auditing may effectively target the vital message passing performed by all illicit data collection spyware. Our research then evolves into an experiment involving the design and implementation of a software audit tool to conduct the desired compliance auditing. The software audit tool is positioned at the protected network’s gateway. The software audit tool uses ‘phone-home’ IP addresses as spyware signatures to detect the presence of the offending software. The audit tool also has the capability to differentiate legitimate message passing software from that produced by spyware – and ‘learn’ both new spyware signatures and new legitimate message passing profiles. The testing stage of the software has proven successful – albeit using very limited levels of network message passing variety and frequency.