Gelatinisation of starch in mixtures of sugars. I. Dynamic rheological properties and behaviours of starch-honey systems

Dynamic rheological behaviour of starch-honey systems was studied using a strain-controlled rheometer. A dynamic temperature (30-130 degreesC) ramp test was used at 10 rad s(-1) frequency, 1% strain, 2 degreesC min(-1) ramp rate, 25 mm parallel plate, and 1.5 min gap, using Wheaten cornflour(TM) and five honeys to generate 25 formulations (0.34-0.80 g water/g dry starch). G', G, and eta* increased upon gelatinisation, and they reduced as the honey content was increased. For all the formulations, G' was higher than G, and tan 6 was generally less than 1.0. Key gelatinisation characterising temperatures (onset, peak and end) ranged from 96.0 to 122.3 degreesC, but did not vary much (CV < 5%) for each honey irrespective of the concentration. The influence of water, fructose and glucose, singly and in combination, on gelatinisation indices (temperature and rheological parameters) was investigated. An exponential equation was employed to describe the relationship, and relevant parameters were obtained. The consequences of the observations in the study are discussed particularly as they relate to extrusion of such systems, and possible interactions between fructose and glucose in the starch-honey systems. (C) 2003 Elsevier Ltd. All rights reserved.

Design and implementation of a windows-based parallel computing environment for large scale optimization

A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

Process systems modelling and applications in granulation: A review

Granulation is one of the fundamental operations in particulate processing and has a very ancient history and widespread use. Much fundamental particle science has occurred in the last two decades to help understand the underlying phenomena. Yet, until recently the development of granulation systems was mostly based on popular practice. The use of process systems approaches to the integrated understanding of these operations is providing improved insight into the complex nature of the processes. Improved mathematical representations, new solution techniques and the application of the models to industrial processes are yielding better designs, improved optimisation and tighter control of these systems. The parallel development of advanced instrumentation and the use of inferential approaches provide real-time access to system parameters necessary for improvements in operation. The use of advanced models to help develop real-time plant diagnostic systems provides further evidence of the utility of process system approaches to granulation processes. This paper highlights some of those aspects of granulation. (c) 2005 Elsevier Ltd. All rights reserved.

Investigations into MIMO systems from an electromagnetic perspective

The paper presents investigations into multiple input multiple output wireless communication systems, which are carried out from an electromagnetic perspective. The first part of the paper focuses on signal propagation models, which can be used for determining the MIMO system capacity or its performance when various space-time coding schemes are applied. Two types of models are considered. In the first model, array antennas are treated in an exact electromagnetic manner but interactions with scattering objects are incorporated using an approximate single bounce scattering approach. The other model is a simple but exact electromagnetic (EM) model, which takes into account EM interactions between antennas and scatterers. In this model, parallel wire dipoles represent antennas as well as scatterers. The second part of the paper reports on investigations into two types of MIMO testbeds. The first one is a simple transmit/receive diversity tested while the other one is a full MIMO testbed. The paper briefly describes the results obtained during the undertaken investigations

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

Verification and validation of autonomous systems

NASA is working on complex future missions that require cooperation between multiple satellites or rovers. To implement these systems, developers are proposing and using intelligent and autonomous systems. These autonomous missions are new to NASA, and the software development community is just learning to develop such systems. With these new systems, new verification and validation techniques must be used. Current techniques have been developed based on large monolithic systems. These techniques have worked well and reliably, but do not translate to the new autonomous systems that are highly parallel and nondeterministic.

Parallel geostatistics for sparse and dense datasets

Very large spatially-referenced datasets, for example, those derived from satellite-based sensors which sample across the globe or large monitoring networks of individual sensors, are becoming increasingly common and more widely available for use in environmental decision making. In large or dense sensor networks, huge quantities of data can be collected over small time periods. In many applications the generation of maps, or predictions at specific locations, from the data in (near) real-time is crucial. Geostatistical operations such as interpolation are vital in this map-generation process and in emergency situations, the resulting predictions need to be available almost instantly, so that decision makers can make informed decisions and define risk and evacuation zones. It is also helpful when analysing data in less time critical applications, for example when interacting directly with the data for exploratory analysis, that the algorithms are responsive within a reasonable time frame. Performing geostatistical analysis on such large spatial datasets can present a number of problems, particularly in the case where maximum likelihood. Although the storage requirements only scale linearly with the number of observations in the dataset, the computational complexity in terms of memory and speed, scale quadratically and cubically respectively. Most modern commodity hardware has at least 2 processor cores if not more. Other mechanisms for allowing parallel computation such as Grid based systems are also becoming increasingly commonly available. However, currently there seems to be little interest in exploiting this extra processing power within the context of geostatistics. In this paper we review the existing parallel approaches for geostatistics. By recognising that diffeerent natural parallelisms exist and can be exploited depending on whether the dataset is sparsely or densely sampled with respect to the range of variation, we introduce two contrasting novel implementations of parallel algorithms based on approximating the data likelihood extending the methods of Vecchia [1988] and Tresp [2000]. Using parallel maximum likelihood variogram estimation and parallel prediction algorithms we show that computational time can be significantly reduced. We demonstrate this with both sparsely sampled data and densely sampled data on a variety of architectures ranging from the common dual core processor, found in many modern desktop computers, to large multi-node super computers. To highlight the strengths and weaknesses of the diffeerent methods we employ synthetic data sets and go on to show how the methods allow maximum likelihood based inference on the exhaustive Walker Lake data set.

A composite framework for the strategic alignment of information systems development

Information systems are corporate resources, therefore information systems development must be aligned with corporate strategy. This thesis proposes that effective strategic alignment of information systems requires information systems development, information systems planning and strategic management to be united. Literature in these areas is examined, breaching the academic boundaries which separate these areas, to contribute a synthesised approach to the strategic alignment of information systems development. Previous work in information systems planning has extended information systems development techniques, such as data modelling, into strategic planning activities, neglecting techniques of strategic management. Examination of strategic management in this thesis, identifies parallel trends in strategic management and information systems development; the premises of the learning school of strategic management are similar to those of soft systems approaches to information systems development. It is therefore proposed that strategic management can be supported by a soft systems approach. Strategic management tools and techniques frame individual views of a strategic situation; soft systems approaches can integrate these diverse views to explore the internal and external environments of an organisation. The information derived from strategic analysis justifies the need for an information system and provides a starting point for information systems development. This is demonstrated by a composite framework which enables each information system to be justified according to its direct contribution to corporate strategy. The proposed framework was developed through action research conducted in a number of organisations of varying types. This suggests that the framework can be widely used to support the strategic alignment of information systems development, thereby contributing to organisational success.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

User interface design support for the development of knowledge-based systems

The present scarcity of operational knowledge-based systems (KBS) has been attributed, in part, to an inadequate consideration shown to user interface design during development. From a human factors perspective the problem has stemmed from an overall lack of user-centred design principles. Consequently the integration of human factors principles and techniques is seen as a necessary and important precursor to ensuring the implementation of KBS which are useful to, and usable by, the end-users for whom they are intended. Focussing upon KBS work taking place within commercial and industrial environments, this research set out to assess both the extent to which human factors support was presently being utilised within development, and the future path for human factors integration. The assessment consisted of interviews conducted with a number of commercial and industrial organisations involved in KBS development; and a set of three detailed case studies of individual KBS projects. Two of the studies were carried out within a collaborative Alvey project, involving the Interdisciplinary Higher Degrees Scheme (IHD) at the University of Aston in Birmingham, BIS Applied Systems Ltd (BIS), and the British Steel Corporation. This project, which had provided the initial basis and funding for the research, was concerned with the application of KBS to the design of commercial data processing (DP) systems. The third study stemmed from involvement on a KBS project being carried out by the Technology Division of the Trustees Saving Bank Group plc. The preliminary research highlighted poor human factors integration. In particular, there was a lack of early consideration of end-user requirements definition and user-centred evaluation. Instead concentration was given to the construction of the knowledge base and prototype evaluation with the expert(s). In response to this identified problem, a set of methods was developed that was aimed at encouraging developers to consider user interface requirements early on in a project. These methods were then applied in the two further projects, and their uptake within the overall development process was monitored. Experience from the two studies demonstrated that early consideration of user interface requirements was both feasible, and instructive for guiding future development work. In particular, it was shown a user interface prototype could be used as a basis for capturing requirements at the functional (task) level, and at the interface dialogue level. Extrapolating from this experience, a KBS life-cycle model is proposed which incorporates user interface design (and within that, user evaluation) as a largely parallel, rather than subsequent, activity to knowledge base construction. Further to this, there is a discussion of several key elements which can be seen as inhibiting the integration of human factors within KBS development. These elements stem from characteristics of present KBS development practice; from constraints within the commercial and industrial development environments; and from the state of existing human factors support.

Generalized mean field approximation for parallel dynamics of the Ising model

The dynamics of the non-equilibrium Ising model with parallel updates is investigated using a generalized mean field approximation that incorporates multiple two-site correlations at any two time steps, which can be obtained recursively. The proposed method shows significant improvement in predicting local system properties compared to other mean field approximation techniques, particularly in systems with symmetric interactions. Results are also evaluated against those obtained from Monte Carlo simulations. The method is also employed to obtain parameter values for the kinetic inverse Ising modeling problem, where couplings and local field values of a fully connected spin system are inferred from data. © 2014 IOP Publishing Ltd and SISSA Medialab srl.

Evolutionary market agents for resource allocation in decentralised systems

We introduce self-interested evolutionary market agents, which act on behalf of service providers in a large decentralised system, to adaptively price their resources over time. Our agents competitively co-evolve in the live market, driving it towards the Bertrand equilibrium, the non-cooperative Nash equilibrium, at which all sellers charge their reserve price and share the market equally. We demonstrate that this outcome results in even load-balancing between the service providers. Our contribution in this paper is twofold; the use of on-line competitive co-evolution of self-interested service providers to drive a decentralised market towards equilibrium, and a demonstration that load-balancing behaviour emerges under the assumptions we describe. Unlike previous studies on this topic, all our agents are entirely self-interested; no cooperation is assumed. This makes our problem a non-trivial and more realistic one.

Static Analysis of Usefulness States in Transition P Systems

Transition P Systems are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations that are determined by the membrane structure and multisets present inside membranes. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of evolution rules. But, to establish the rules to be applied, it is required the previous calculation of useful, applicable and active rules. Hence, computation of useful evolution rules is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in every evolution step. This work defines usefulness states through an exhaustive analysis of the P system for every membrane and for every possible configuration of the membrane structure during the computation. Moreover, this analysis can be done in a static way; therefore membranes only have to check their usefulness states to obtain their set of useful rules during execution.

Networks of Evolutionary Processors (NEP) as Decision Support Systems

This paper presents the application of Networks of Evolutionary Processors to Decision Support Systems, precisely Knowledge-Driven DSS. Symbolic information and rule-based behavior in Networks of Evolutionary Processors turn out to be a great tool to obtain decisions based on objects present in the network. The non-deterministic and massive parallel way of operation results in NP-problem solving in linear time. A working NEP example is shown.