Modelling of two-stage anaerobic digestion using the IWA Anaerobic Digestion Model No. 1 (ADM1)

The aim of the study presented was to implement a process model to simulate the dynamic behaviour of a pilot-scale process for anaerobic two-stage digestion of sewage sludge. The model implemented was initiated to support experimental investigations of the anaerobic two-stage digestion process. The model concept implemented in the simulation software package MATLAB(TM)/Simulink(R) is a derivative of the IWA Anaerobic Digestion Model No.1 (ADM1) that has been developed by the IWA task group for mathematical modelling of anaerobic processes. In the present study the original model concept has been adapted and applied to replicate a two-stage digestion process. Testing procedures, including balance checks and 'benchmarking' tests were carried out to verify the accuracy of the implementation. These combined measures ensured a faultless model implementation without numerical inconsistencies. Parameters for both, the thermophilic and the mesophilic process stage, have been estimated successfully using data from lab-scale experiments described in literature. Due to the high number of parameters in the structured model, it was necessary to develop a customised procedure that limited the range of parameters to be estimated. The accuracy of the optimised parameter sets has been assessed against experimental data from pilot-scale experiments. Under these conditions, the model predicted reasonably well the dynamic behaviour of a two-stage digestion process in pilot scale. (C) 2004 Elsevier Ltd. All rights reserved.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

Artificial pumping errors in the Kool-Parker scaling model of soil moisture hysteresis

Hysteresis models that eliminate the artificial pumping errors associated with the Kool-Parker (KP) soil moisture hysteresis model, such as the Parker-Lenhard (PL) method, can be computationally demanding in unsaturated transport models since they need to retain the wetting-drying history of the system. The pumping errors in these models need to be eliminated for correct simulation of cyclical systems (e.g. transport above a tidally forced watertable, infiltration and redistribution under periodic irrigation) if the soils exhibit significant hysteresis. A modification is made here to the PL method that allows it to be more readily applied to numerical models by eliminating the need to store a large number of soil moisture reversal points. The modified-PL method largely eliminates any artificial pumping error and so essentially retains the accuracy of the original PL approach. The modified-PL method is implemented in HYDRUS-1D (version 2.0), which is then used to simulate cyclic capillary fringe dynamics to show the influence of removing artificial pumping errors and to demonstrate the ease of implementation. Artificial pumping errors are shown to be significant for the soils and system characteristics used here in numerical experiments of transport above a fluctuating watertable. (c) 2005 Elsevier B.V. All rights reserved.

Parallel 3D Simulation of a Fault Gouge using the Lattice Solid Model

Despite the insight gained from 2-D particle models, and given that the dynamics of crustal faults occur in 3-D space, the question remains, how do the 3-D fault gouge dynamics differ from those in 2-D? Traditionally, 2-D modeling has been preferred over 3-D simulations because of the computational cost of solving 3-D problems. However, modern high performance computing architectures, combined with a parallel implementation of the Lattice Solid Model (LSM), provide the opportunity to explore 3-D fault micro-mechanics and to advance understanding of effective constitutive relations of fault gouge layers. In this paper, macroscopic friction values from 2-D and 3-D LSM simulations, performed on an SGI Altix 3700 super-cluster, are compared. Two rectangular elastic blocks of bonded particles, with a rough fault plane and separated by a region of randomly sized non-bonded gouge particles, are sheared in opposite directions by normally-loaded driving plates. The results demonstrate that the gouge particles in the 3-D models undergo significant out-of-plane motion during shear. The 3-D models also exhibit a higher mean macroscopic friction than the 2-D models for varying values of interparticle friction. 2-D LSM gouge models have previously been shown to exhibit accelerating energy release in simulated earthquake cycles, supporting the Critical Point hypothesis. The 3-D models are shown to also display accelerating energy release, and good fits of power law time-to-failure functions to the cumulative energy release are obtained.

RatSLAM: A hippocampal model for simultaneous localisation and mapping

The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.

A case study in specification and implementation testing

Achieving consistency between a specification and its implementation is an important part of software development In previous work, we have presented a method and tool support for testing a formal specification using animation and then verifying an implementation of that specification. The method is based on a testgraph, which provides a partial model of the application under test. The testgraph is used in combination with an animator to generate test sequences for testing the formal specification. The same testgraph is used during testing to execute those same sequences on the implementation and to ensure that the implementation conforms to the specification. So far, the method and its tool support have been applied to software components that can be accessed through an application programmer interface (API). In this paper, we use an industrially-based case study to discuss the problems associated with applying the method to a software system with a graphical user interface (GUI). In particular, the lack of a standardised interface, as well as controllability and observability problems, make it difficult to automate the testing of the implementation. The method can still be applied, but the amount of testing that can be carried on the implementation is limited by the manual effort involved.

The role of management incentives in successful information systems development and implementation

Because organizations are making large investments in Information systems (IS), efficient IS project management has been found critical to success. This study examines how the use of incentives can improve the project success. Agency theory is used to: identify motivational factors of project success, help the IS owners to understand to what extent management incentives can improve IS development and implementation (ISD/I). The outcomes will help practitioners and researchers to build on theoretical model of project management elements which lead to project success. Given the principal-agent nature of most significant scale of IS development, insights that will allow for greater alignment of the agent’s goals with those of the principal through incentive contracts, will serve to make ISD/I both more efficient and more effective, leading to more successful IS projects.

How does your model grow? An empirical investigation of the effects of ontological clarity and application domain size on query performance

Semantic data models provide a map of the components of an information system. The characteristics of these models affect their usefulness for various tasks (e.g., information retrieval). The quality of information retrieval has obvious important consequences, both economic and otherwise. Traditionally, data base designers have produced parsimonious logical data models. In spite of their increased size, ontologically clearer conceptual models have been shown to facilitate better performance for both problem solving and information retrieval tasks in experimental settings. The experiments producing evidence of enhanced performance for ontologically clearer models have, however, used application domains of modest size. Data models in organizational settings are likely to be substantially larger than those used in these experiments. This research used an experiment to investigate whether the benefits of improved information retrieval performance associated with ontologically clearer models are robust as the size of the application domains increase. The experiment used an application domain of approximately twice the size as tested in prior experiments. The results indicate that, relative to the users of the parsimonious implementation, end users of the ontologically clearer implementation made significantly more semantic errors, took significantly more time to compose their queries, and were significantly less confident in the accuracy of their queries.

Verifying metamodel coverage of model transformations

Since the object management group (OMG) commenced its model driven architecture (MDA) initiative, there has been considerable activity proposing and building automatic model transformation systems to help implement the MDA concept. Much less attention has been given to the need to ensure that model transformations generate the intended results. This paper explores one aspect of validation and verification for MDA: coverage of the source and/or target metamodels by a set of model transformations. The paper defines the property of metamodel coverage and some corresponding algorithms. This property helps the user assess which parts of a source (or target) metamodel are referenced by a given model transformation set. Some results are presented from a prototype implementation that is built on the eclipse modeling framework (EMF).

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

Policy into practice:a study of public policy implementation and the role of learning

Public policy becomes managerial practice through a process of implementation. There is an established literature within Implementation Studies which explains the variables and some of the processes involved in implementation, but less attention has been focused upon how public service managers convert new policy initiatives into practice. The research proposes that managers and their organisations have to go through a process of learning in order to achieve the implementation of public policy. Data was collected over a five year period from four case studies of capital investment appraisal in the British National Health Service. Further data was collected from taped interviews by key actors within the case studies. The findings suggest that managers do learn to implement policy and four factors are important in this learning process. These are; (i) the nature of bureaucratic responsibility; (ii) the motivation of actors towards learning; (iii) the passage of time which allows for the development of competence and (iv) the use of project team structures. The research has demonstrated that the conversion of policy into practice occurs through the operationalisation of solutions to policy problems via job tasks. As such it suggests that in understanding how policy is implemented, technical learning is more important than cultural learning, in this context. In conclusion, a "Model of Learned Implementation" is presented, together with a discussion of some of the implications of the research. These are the possible use of more pilot projects for new policy initiatives and the more systematic diffusion of knowledge about implementation solutions.

Risk based decision support system for effective implementation of projects

Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Introduction: improving manufacturing performance through technology diffusion, implementation and management

The role of technology management in achieving improved manufacturing performance has been receiving increased attention as enterprises are becoming more exposed to competition from around the world. In the modern market for manufactured goods the demand is now for more product variety, better quality, shorter delivery and greater flexibility, while the financial and environmental cost of resources has become an urgent concern to manufacturing managers. This issue of the International Journal of Technology Management addresses the question of how the diffusion, implementation and management of technology can improve the performance of manufacturing industries. The authors come from a large number of different countries and their contributions cover a wide range of topics within this general theme. Some papers are conceptual, others report on research carried out in a range of different industries including steel production, iron founding, electronics, robotics, machinery, precision engineering, metal working and motor manufacture. In some cases they describe situations in specific countries. Several are based on presentations made at the UK Operations Management Association's Sixth International Conference held at Aston University at which the conference theme was 'Achieving Competitive Edge: Getting Ahead Through Technology and People'. The first two papers deal with questions of advanced manufacturing technology implementation and management. Firstly Beatty describes a three year longitudinal field study carried out in ten Canadian manufacturing companies using CADICAM and CIM systems. Her findings relate to speed of implementation, choice of system type, the role of individuals in implementation, organization and job design. This is followed by a paper by Bessant in which he argues that a more a strategic approach should be taken towards the management of technology in the 1990s and beyond. Also considered in this paper are the capabilities necessary in order to deploy advanced manufacturing technology as a strategic resource and the way such capabilities might be developed within the firm. These two papers, which deal largely with the implementation of hardware, are supplemented by Samson and Sohal's contribution in which they argue that a much wider perspective should be adopted based on a new approach to manufacturing strategy formulation. Technology transfer is the topic of the following two papers. Pohlen again takes the case of advanced manufacturing technology and reports on his research which considers the factors contributing to successful realisation of AMT transfer. The paper by Lee then provides a more detailed account of technology transfer in the foundry industry. Using a case study based on a firm which has implemented a number of transferred innovations a model is illustrated in which the 'performance gap' can be identified and closed. The diffusion of technology is addressed in the next two papers. In the first of these, by Lowe and Sim, the managerial technologies of 'Just in Time' and 'Manufacturing Resource Planning' (or MRP 11) are examined. A study is described from which a number of factors are found to influence the adoption process including, rate of diffusion and size. Dahlin then considers the case of a specific item of hardware technology, the industrial robot. Her paper reviews the history of robot diffusion since the early 1960s and then tries to predict how the industry will develop in the future. The following two papers deal with the future of manufacturing in a more general sense. The future implementation of advanced manufacturing technology is the subject explored by de Haan and Peters who describe the results of their Dutch Delphi forecasting study conducted among a panel of experts including scientists, consultants, users and suppliers of AMT. Busby and Fan then consider a type of organisational model, 'the extended manufacturing enterprise', which would represent a distinct alternative pure market-led and command structures by exploiting the shared knowledge of suppliers and customers. The three country-based papers consider some strategic issues relating manufacturing technology. In a paper based on investigations conducted in China He, Liff and Steward report their findings from strategy analyses carried out in the steel and watch industries with a view to assessing technology needs and organizational change requirements. This is followed by Tang and Nam's paper which examines the case of machinery industry in Korea and its emerging importance as a key sector in the Korean economy. In his paper which focuses on Venezuela, Ernst then considers the particular problem of how this country can address the problem of falling oil revenues. He sees manufacturing as being an important contributor to Venezuela's future economy and proposes a means whereby government and private enterprise can co-operate in development of the manufacturing sector. The last six papers all deal with specific topics relating to the management manufacturing. Firstly Youssef looks at the question of manufacturing flexibility, introducing and testing a conceptual model that relates computer based technologies flexibility. Dangerfield's paper which follows is based on research conducted in the steel industry. He considers the question of scale and proposes a modelling approach determining the plant configuration necessary to meet market demand. Engstrom presents the results of a detailed investigation into the need for reorganising material flow where group assembly of products has been adopted. Sherwood, Guerrier and Dale then report the findings of a study into the effectiveness of Quality Circle implementation. Stillwagon and Burns, consider how manufacturing competitiveness can be improved individual firms by describing how the application of 'human performance engineering' can be used to motivate individual performance as well as to integrate organizational goals. Finally Sohal, Lewis and Samson describe, using a case study example, how just-in-time control can be applied within the context of computer numerically controlled flexible machining lines. The papers in this issue of the International Journal of Technology Management cover a wide range of topics relating to the general question of improving manufacturing performance through the dissemination, implementation and management of technology. Although they differ markedly in content and approach, they have the collective aim addressing the concepts, principles and practices which provide a better understanding the technology of manufacturing and assist in achieving and maintaining a competitive edge.

Addressing the project implementation challenges in the Saudi Arabian power supply industry: an investigative approach towards improving project delivery

For many decades, the Kingdom of Saudi Arabia has been widely known for being a reliable oil exporter. This fact, however, has not exempted it from facing significant domestic energy challenges. One of the most pressing of these challenges involves bridging the widening electricity supply-demand gap where, currently, the demand is growing at a very fast rate. One crucial means to address this challenge is through delivering power supply projects with maximum efficiency. Project delivery delay, however, is not uncommon in this highly capital-intensive industry, indicating electricity supplies are not coping with the demand increases. To provide a deeper insight into the challenges of project implementation and efficient practice, this research adopts a pragmatic approach by triangulating literature, questionnaires and semi-structured interviews. The research was conducted in the Saudi Arabian power supply industry – Western Operating Area. A total of 105 usable questionnaires were collected, and 28 recorded, semi-structured interviews were conducted, analysed and synthesised to produce a conceptual model of what constitutes the project implementation challenges in the investigated industry. This was achieved by conducting a comprehensive ranking analysis applied to all 58 identified and surveyed factors which, according to project practitioners in the investigated industry, contribute to project delay. 28 of these project delay factors were selected as the "most important" ones. Factor Analysis was employed to structure these 28 most important project delay factors into the following meaningful set of 7 project implementation challenges: Saudi Electricity Company's contractual commitments, Saudi Electricity Company's communication and coordination effectiveness, contractors' project planning and project control effectiveness, consultant-related aspects, manpower challenges and material uncertainties, Saudi Electricity Company's tendering system, and lack of project requirements clarity. The study has implications for industry policy in that it provides a coherent assessment of the key project stakeholders' central problems. From this analysis, pragmatic recommendations are proposed that, if enacted, will minimise the significance of the identified problems on future project outcomes, thus helping to ensure the electricity supply-demand gap is diminished.