The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

Modelling and linking transformations in EPCIS governing supply chain business processes

Supply chains comprise of complex processes spanning across multiple trading partners. The various operations involved generate large number of events that need to be integrated in order to enable internal and external traceability. Further, provenance of artifacts and agents involved in the supply chain operations is now a key traceability requirement. In this paper we propose a Semantic web/Linked data powered framework for the event based representation and analysis of supply chain activities governed by the EPCIS specification. We specifically show how a new EPCIS event type called "Transformation Event" can be semantically annotated using EEM - The EPCIS Event Model to generate linked data, that can be exploited for internal event based traceability in supply chains involving transformation of products. For integrating provenance with traceability, we propose a mapping from EEM to PROV-O. We exemplify our approach on an abstraction of the production processes that are part of the wine supply chain.

Inverse forecasting:a new approach for predictive modelling

In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large uses of linear programming in forecasting models there is no a single application of inverse optimization reported in the forecasting literature when the time series data is available. Thus the goal of this paper is to introduce inverse optimization into forecasting field, and to provide a streamlined approach to time series analysis and forecasting using inverse linear programming. An application has been used to demonstrate the use of inverse forecasting developed in this study. © 2007 Elsevier Ltd. All rights reserved.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Multiscale modelling:approaches and challenges

Multiscale systems that are characterized by a great range of spatial–temporal scales arise widely in many scientific domains. These range from the study of protein conformational dynamics to multiphase processes in, for example, granular media or haemodynamics, and from nuclear reactor physics to astrophysics. Despite the diversity in subject areas and terminology, there are many common challenges in multiscale modelling, including validation and design of tools for programming and executing multiscale simulations. This Theme Issue seeks to establish common frameworks for theoretical modelling, computing and validation, and to help practical applications to benefit from the modelling results. This Theme Issue has been inspired by discussions held during two recent workshops in 2013: ‘Multiscale modelling and simulation’ at the Lorentz Center, Leiden (http://www.lorentzcenter.nl/lc/web/2013/569/info.php3?wsid=569&venue=Snellius), and ‘Multiscale systems: linking quantum chemistry, molecular dynamics and microfluidic hydrodynamics’ at the Royal Society Kavli Centre. The objective of both meetings was to identify common approaches for dealing with multiscale problems across different applications in fluid and soft matter systems. This was achieved by bringing together experts from several diverse communities.

Prediction with Gaussian processes: from linear regression to linear prediction and beyond

The main aim of this paper is to provide a tutorial on regression with Gaussian processes. We start from Bayesian linear regression, and show how by a change of viewpoint one can see this method as a Gaussian process predictor based on priors over functions, rather than on priors over parameters. This leads in to a more general discussion of Gaussian processes in section 4. Section 5 deals with further issues, including hierarchical modelling and the setting of the parameters that control the Gaussian process, the covariance functions for neural network models and the use of Gaussian processes in classification problems.

Towards a framework for combining stochastic and deterministic descriptions of nonstationary financial time series

We present in this paper ideas to tackle the problem of analysing and forecasting nonstationary time series within the financial domain. Accepting the stochastic nature of the underlying data generator we assume that the evolution of the generator's parameters is restricted on a deterministic manifold. Therefore we propose methods for determining the characteristics of the time-localised distribution. Starting with the assumption of a static normal distribution we refine this hypothesis according to the empirical results obtained with the methods anc conclude with the indication of a dynamic non-Gaussian behaviour with varying dependency for the time series under consideration.

Simulation modelling for business

Simulation modelling has been used for many years in the manufacturing sector but has now become a mainstream tool in business situations. This is partly because of the popularity of business process re-engineering (BPR) and other process based improvement methods that use simulation to help analyse changes in process design. This textbook includes case studies in both manufacturing and service situations to demonstrate the usefulness of the approach. A further reason for the increasing popularity of the technique is the development of business orientated and user-friendly Windows-based software. This text provides a guide to the use of ARENA, SIMUL8 and WITNESS simulation software systems that are widely used in industry and available to students. Overall this text provides a practical guide to building and implementing the results from a simulation model. All the steps in a typical simulation study are covered including data collection, input data modelling and experimentation.

Evaluating approaches to product design and sourcing decisions in multinational companies

Product design and sourcing decisions are among the most difficult and important of all decisions facing multinational manufacturing companies, yet associated decision support and evaluation systems tend to be myopic in nature. Design for manufacture and assembly techniques, for example, generally focuses on manufacturing capability and ignores capacity although both should be considered. Similarly, most modelling and evaluation tools available to examine the performance of various solution and improvement techniques have a narrower scope than desired. A unique collaboration, funded by the US National Science Foundation, between researchers in the USA and the UK currently addresses these problems. This paper describes a technique known as Design For the Existing Environment (DFEE) and an holistic evaluation system based on enterprise simulation that was used to demonstrate the business benefits of DFEE applied in a simple product development and manufacturing case study. A project that will extend these techniques to evaluate global product sourcing strategies is described along with the practical difficulties of building an enterprise simulation on the scale and detail required.

Toward the discovery of vaccine adjuvants:coupling in silico screening and in vitro analysis of antagonist binding to human and mouse CCR4 receptors

Background Adjuvants enhance or modify an immune response that is made to an antigen. An antagonist of the chemokine CCR4 receptor can display adjuvant-like properties by diminishing the ability of CD4+CD25+ regulatory T cells (Tregs) to down-regulate immune responses. Methodology Here, we have used protein modelling to create a plausible chemokine receptor model with the aim of using virtual screening to identify potential small molecule chemokine antagonists. A combination of homology modelling and molecular docking was used to create a model of the CCR4 receptor in order to investigate potential lead compounds that display antagonistic properties. Three-dimensional structure-based virtual screening of the CCR4 receptor identified 116 small molecules that were calculated to have a high affinity for the receptor; these were tested experimentally for CCR4 antagonism. Fifteen of these small molecules were shown to inhibit specifically CCR4-mediated cell migration, including that of CCR4+ Tregs. Significance Our CCR4 antagonists act as adjuvants augmenting human T cell proliferation in an in vitro immune response model and compound SP50 increases T cell and antibody responses in vivo when combined with vaccine antigens of Mycobacterium tuberculosis and Plasmodium yoelii in mice.

A methodology for the generation and evaluation of biorefinery process chains, in order to identify the most promising biorefineries for the EU

The topic of bioenergy, biofuels and bioproducts remains at the top of the current political and research agenda. Identification of the optimum processing routes for biomass, in terms of efficiency, cost, environment and socio-economics is vital as concern grows over the remaining fossil fuel resources, climate change and energy security. It is known that the only renewable way of producing conventional hydrocarbon fuels and organic chemicals is from biomass, but the problem remains of identifying the best product mix and the most efficient way of processing biomass to products. The aim is to move Europe towards a biobased economy and it is widely accepted that biorefineries are key to this development. A methodology was required for the generation and evaluation of biorefinery process chains for converting biomass into one or more valuable products that properly considers performance, cost, environment, socio-economics and other factors that influence the commercial viability of a process. In this thesis a methodology to achieve this objective is described. The completed methodology includes process chain generation, process modelling and subsequent analysis and comparison of results in order to evaluate alternative process routes. A modular structure was chosen to allow greater flexibility and allowing the user to generate a large number of different biorefinery configurations The significance of the approach is that the methodology is defined and is thus rigorous and consistent and may be readily re-examined if circumstances change. There was the requirement for consistency in structure and use, particularly for multiple analyses. It was important that analyses could be quickly and easily carried out to consider, for example, different scales, configurations and product portfolios and so that previous outcomes could be readily reconsidered. The result of the completed methodology is the identification of the most promising biorefinery chains from those considered as part of the European Biosynergy Project.

Characterization of heparin-binding site of tissue transglutaminase:its importance in cell surface targeting, matrix deposition, and cell signaling

Tissue transglutaminase (TG2) is a multifunctional Ca2+ activated protein crosslinking enzyme secreted into the extracellular matrix (ECM), where it is involved in wound healing and scarring, tissue fibrosis, celiac disease and metastatic cancer. Extracellular TG2 can also facilitate cell adhesion important in wound healing through a non-transamidating mechanism via its association with fibronectin (FN), heparan sulphates (HS) and integrins. Regulating the mechanism how TG2 is translocated into the ECM therefore provides a strategy for modulating these physiological and pathological functions of the enzyme. Here, through molecular modelling and mutagenesis we have identified the HS binding site of TG2 202KFLKNAGRDCSRRSSPVYVGR222. We demonstrate the requirement of this binding site for translocation of TG2 into the ECM through a mechanism involving cell surface shedding of HS. By synthesizing a peptide NPKFLKNAGRDCSRRSS corresponding to the HS binding site within TG2, we also demonstrate how this mimicking peptide can in isolation compensate the RGD-induced loss of cell adhesion on FN via binding to syndecan-4, leading to activation of PKCa, pFAK-397 and ERK1/2 and the subsequent formation of focal adhesions and actin cytoskeleton organization. A novel regulatory mechanism for TG2 translocation into the extracellular compartment that depends upon TG2 conformation and the binding of HS is proposed.

Design and development of a time of flight fast scattering spectrometer : a quantitative surface analysis technique and a new approach towards the experimental investigation of the surface particle interactions

A new surface analysis technique has been developed which has a number of benefits compared to conventional Low Energy Ion Scattering Spectrometry (LEISS). A major potential advantage arising from the absence of charge exchange complications is the possibility of quantification. The instrumentation that has been developed also offers the possibility of unique studies concerning the interaction between low energy ions and atoms and solid surfaces. From these studies it may also be possible, in principle, to generate sensitivity factors to quantify LEISS data. The instrumentation, which is referred to as a Time-of-Flight Fast Atom Scattering Spectrometer has been developed to investigate these conjecture in practice. The development, involved a number of modifications to an existing instrument, and allowed samples to be bombarded with a monoenergetic pulsed beam of either atoms or ions, and provided the capability to analyse the spectra of scattered atoms and ions separately. Further to this a system was designed and constructed to allow incident, exit and azimuthal angles of the particle beam to be varied independently. The key development was that of a pulsed, and mass filtered atom source; which was developed by a cyclic process of design, modelling and experimentation. Although it was possible to demonstrate the unique capabilities of the instrument, problems relating to surface contamination prevented the measurement of the neutralisation probabilities. However, these problems appear to be technical rather than scientific in nature, and could be readily resolved given the appropriate resources. Experimental spectra obtained from a number of samples demonstrate some fundamental differences between the scattered ion and neutral spectra. For practical non-ordered surfaces the ToF spectra are more complex than their LEISS counterparts. This is particularly true for helium scattering where it appears, in the absence of detailed computer simulation, that quantitative analysis is limited to ordered surfaces. Despite this limitation the ToFFASS instrument opens the way for quantitative analysis of the 'true' surface region to a wider range of surface materials.

Combined bioreaction and separation in a simulated counter-current chromatographic bioreactor-separator system

The objective of this work has been to investigate the principle of combined bioreaction and separation in a simulated counter-current chromatographic bioreactor-separator system (SCCR-S). The SCCR-S system consisted of twelve 5.4cm i.d x 75cm long columns packed with calcium charged cross-linked polystyrene resin. Three bioreactions, namely the saccharification of modified starch to maltose and dextrin using the enzyme maltogenase, the hydrolysis of lactose to galactose and glucose in the presence of the enzyme lactase and the biosynthesis of dextran from sucrose using the enzyme dextransucrase. Combined bioreaction and separation has been successfully carried out in the SCCR-S system for the saccharification of modified starch to maltose and dextrin. The effects of the operating parameters (switch time, eluent flowrate, feed concentration and enzyme activity) on the performance of the SCCR-S system were investigated. By using an eluent of dilute enzyme solution, starch conversions of up to 60% were achieved using lower amounts of enzyme than the theoretical amount required by a conventional bioreactor to produce the same amount of maltose over the same time period. Comparing the SCCR-S system to a continuous annular chromatograph (CRAC) for the saccharification of modified starch showed that the SCCR-S system required only 34.6-47.3% of the amount of enzyme required by the CRAC. The SCCR-S system was operated in the batch and continuous modes as a bioreactor-separator for the hydrolysis of lactose to galactose and glucose. By operating the system in the continuous mode, the operating parameters were further investigated. During these experiments the eluent was deionised water and the enzyme was introduced into the system through the same port as the feed. The galactose produced was retarded and moved with the stationary phase to be purge as the galactose rich product (GalRP) while the glucose moved with the mobile phase and was collected as the glucose rich product (GRP). By operating at up to 30%w/v lactose feed concentrations, complete conversions were achieved using only 48% of the theoretical amount of enzyme required by a conventional bioreactor to hydrolyse the same amount of glucose over the same time period. The main operating parameters affecting the performance of the SCCR-S system operating in the batch mode were investigated and the results compared to those of the continuous operation of the SCCR-S system. . During the biosynthesis of dextran in the SCCR-S system, a method of on-line regeneration of the resin was required to operate the system continuously. Complete conversion was achieved at sucrose feed concentrations of 5%w/v with fructose rich. products (FRP) of up to 100% obtained. The dextran rich products were contaninated by small amounts of glucose and levan formed during the bioreaction. Mathematical modelling and computer simulation of the SCCR-S. system operating in the continuous mode for the hydrolysis of lactose has been carried out. .