A tree-based decision model to support prediction of the severity of asthma exacerbations in children

This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool.

Web-based expert systems:benefits and challenges

Convergence of technologies in the Internet and the field of expert systems have offered new ways of sharing and distributing knowledge. However, there has been a general lack of research in the area of web-based expert systems (ES). This paper addresses the issues associated with the design, development, and use of web-based ES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional ES were reviewed and a knowledge engineering framework for developing them was revisited. The study considered three web-based ES: WITS-advisor - for e-business strategy development, Fish-Expert - for fish disease diagnosis, and IMIS - to promote intelligent interviews. The benefits and challenges in developing and using ES are discussed by comparing them with traditional standalone systems from development and application perspectives. © 2004 Elsevier B.V. All rights reserved.

A study of business user based information systems development, and modelling success factors

This thesis describes research into business user involvement in the information systems application building process. The main interest of this research is in establishing and testing techniques to quantify the relationships between identified success factors and the outcome effectiveness of 'business user development' (BUD). The availability of a mechanism to measure the levels of the success factors, and quantifiably relate them to outcome effectiveness, is important in that it provides an organisation with the capability to predict and monitor effects on BUD outcome effectiveness. This is particularly important in an era where BUD levels have risen dramatically, user centred information systems development benefits are recognised as significant, and awareness of the risks of uncontrolled BUD activity is becoming more widespread. This research targets the measurement and prediction of BUD success factors and implementation effectiveness for particular business users. A questionnaire instrument and analysis technique has been tested and developed which constitutes a tool for predicting and monitoring BUD outcome effectiveness, and is based on the BUDES (Business User Development Effectiveness and Scope) research model - which is introduced and described in this thesis. The questionnaire instrument is designed for completion by 'business users' - the target community being more explicitly defined as 'people who primarily have a business role within an organisation'. The instrument, named BUD ESP (Business User Development Effectiveness and Scope Predictor), can readily be used with survey participants, and has been shown to give meaningful and representative results.

The application of knowledge based expert systems to mechanical engineering design

Investigation of the different approaches used by Expert Systems researchers to solve problems in the domain of Mechanical Design and Expert Systems was carried out. The techniques used for conventional formal logic programming were compared with those used when applying Expert Systems concepts. A literature survey of design processes was also conducted with a view to adopting a suitable model of the design process. A model, comprising a variation on two established ones, was developed and applied to a problem within what are described as class 3 design tasks. The research explored the application of these concepts to Mechanical Engineering Design problems and their implementation on a microcomputer using an Expert System building tool. It was necessary to explore the use of Expert Systems in this manner so as to bridge the gap between their use as a control structure and for detailed analytical design. The former application is well researched into and this thesis discusses the latter. Some Expert System building tools available to the author at the beginning of his work were evaluated specifically for their suitability for Mechanical Engineering design problems. Microsynics was found to be the most suitable on which to implement a design problem because of its simple but powerful Semantic Net Knowledge Representation structure and the ability to use other types of representation schemes. Two major implementations were carried out. The first involved a design program for a Helical compression spring and the second a gearpair system design. Two concepts were proposed in the thesis for the modelling and implementation of design systems involving many equations. The method proposed enables equation manipulation and analysis using a combination of frames, semantic nets and production rules. The use of semantic nets for purposes other than for psychology and natural language interpretation, is quite new and represents one of the major contributions to knowledge by the author. The development of a purpose built shell program for this type of design problems was recommended as an extension of the research. Microsynics may usefully be used as a platform for this development.

A comparative study of cationic liposome and niosome-based adjuvant systems for protein subunit vaccines:characterisation, environmental scanning electron microscopy and immunisation studies in mice

Vesicular adjuvant systems composing dimethyldioctadecylammonium (DDA) can promote both cell-mediated and humoral immune responses to the tuberculosis vaccine fusion protein in mice. However, these DDA preparations were found to be physically unstable, forming aggregates under ambient storage conditions. Therefore there is a need to improve the stability of such systems without undermining their potent adjuvanticity. To this end, the effect of incorporating non-ionic surfactants, such as 1-monopalmitoyl glycerol (MP), in addition to cholesterol (Chol) and trehalose 6,6′-dibehenate (TDB), on the stability and efficacy of these vaccine delivery systems was investigated. Differential scanning calorimetry revealed a reduction in the phase transition temperature (T c) of DDA-based vesicles by ∼12°C when MP and cholesterol (1:1 molar ratio) were incorporated into the DDA system. Transmission electron microscopy (TEM) revealed the addition of MP to DDA vesicles resulted in the formation of multi-lamellar vesicles. Environmental scanning electron microscopy (ESEM) of MP-Chol-DDA-TDB (16:16:4:0.5 μmol) indicated that incorporation of antigen led to increased stability of the vesicles, perhaps as a result of the antigen embedding within the vesicle bilayers. At 4°C DDA liposomes showed significant vesicle aggregation after 28 days, although addition of MP-Chol or TDB was shown to inhibit this instability. Alternatively, at 25°C only the MP-based systems retained their original size. The presence of MP within the vesicle formulation was also shown to promote a sustained release of antigen in-vitro. The adjuvant activity of various systems was tested in mice against three subunit antigens, including mycobacterial fusion protein Ag85b-ESAT-6, and two malarial antigens (Merozoite surface protein 1, MSP1, and the glutamate rich protein, GLURP). The MP- and DDA-based systems induced antibody responses at comparable levels whereas the DDA-based systems induced more powerful cell-mediated immune responses. © 2006 The Authors.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Genie:supporting the model driven development of reflective, component-based adaptive systems

Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.

A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.

Subject identification via ECG fiducial-based systems:influence of the type of QT interval correction

Electrocardiography (ECG) has been recently proposed as biometric trait for identification purposes. Intra-individual variations of ECG might affect identification performance. These variations are mainly due to Heart Rate Variability (HRV). In particular, HRV causes changes in the QT intervals along the ECG waveforms. This work is aimed at analysing the influence of seven QT interval correction methods (based on population models) on the performance of ECG-fiducial-based identification systems. In addition, we have also considered the influence of training set size, classifier, classifier ensemble as well as the number of consecutive heartbeats in a majority voting scheme. The ECG signals used in this study were collected from thirty-nine subjects within the Physionet open access database. Public domain software was used for fiducial points detection. Results suggested that QT correction is indeed required to improve the performance. However, there is no clear choice among the seven explored approaches for QT correction (identification rate between 0.97 and 0.99). MultiLayer Perceptron and Support Vector Machine seemed to have better generalization capabilities, in terms of classification performance, with respect to Decision Tree-based classifiers. No such strong influence of the training-set size and the number of consecutive heartbeats has been observed on the majority voting scheme.

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

Using biomass-based fuels including pyrolysis liquids for power and CHP production

The use of biomass-derived liquids (in short: bioliquids) instead of solid biomass can help overcome some of the barriers hindering a wider use of biomass in smaller-scale CHP systems. Relevant bioliquids included biodiesel, vegetable oils as well straight and upgraded pyrolysis oil. In this joint EU-Russian research project Bioliquids-CHP prime movers (engines and turbines) will be developed and modified so that these can run efficiently on bioliquids. At the same time, bioliquids will be upgraded and blended in order to facilitate their use in prime movers. Preliminary results with regard to bioliquid selection, production, and characterisation; the selection and modification of a micro gas turbine; and the development of engines and components are discussed. The research also covers NOx emission reduction and control and an assessment of the benefits and economics of bioliquids-based CHP systems in EU and Russian markets.

Vaccine adjuvant systems: enhancing the efficacy of sub-unit protein antigens

Vaccination remains a key tool in the protection and eradication of diseases. However, the development of new safe and effective vaccines is not easy. Various live organism based vaccines currently licensed, exhibit high efficacy; however, this benefit is associated with risk, due to the adverse reactions found with these vaccines. Therefore, in the development of vaccines, the associated risk-benefit issues need to be addressed. Sub-unit proteins offer a much safer alternative; however, their efficacy is low. The use of adjuvanted systems have proven to enhance the immunogenicity of these sub-unit vaccines through protection (i.e. preventing degradation of the antigen in vivo) and enhanced targeting of these antigens to professional antigen-presenting cells. Understanding of the immunological implications of the related disease will enable validation for the design and development of potential adjuvant systems. Novel adjuvant research involves the combination of both pharmaceutical analysis accompanied by detailed immunological investigations, whereby, pharmaceutically designed adjuvants are driven by an increased understanding of mechanisms of adjuvant activity, largely facilitated by description of highly specific innate immune recognition of components usually associated with the presence of invading bacteria or virus. The majority of pharmaceutical based adjuvants currently being investigated are particulate based delivery systems, such as liposome formulations. As an adjuvant, liposomes have been shown to enhance immunity against the associated disease particularly when a cationic lipid is used within the formulation. In addition, the inclusion of components such as immunomodulators, further enhance immunity. Within this review, the use and application of effective adjuvants is investigated, with particular emphasis on liposomal-based systems. The mechanisms of adjuvant activity, analysis of complex immunological characteristics and formulation and delivery of these vaccines are considered.

A novel sensor interrogation technique using chirped fiber grating based sagnac loop

We demonstrate a novel and simple sensor interrogation scheme for fiber Bragg grating (FBG) based sensing systems. In this scheme, a chirped FBG based Sagnac loop is used as a wavelength-dependent receiver, and a stable and linear readout response is realised. It is a signijkant advantage of this scheme that the sensitivity and the measurement wavelength range can be easily adjhsted by controlling the chirp of the FBG or using an optical delay line in the Sagnac loop.

Environmental degradation of polyethylene-based plastics

The criteria involved in the degradation of polyethylene-based degradable polymer samples have been investigated, with a view to obtaining a clearer mechanism of photo-biodegradation. The compatibility of degradable polymer samples during materials recycling was also studied. Commercial and laboratory prepared degradable polymer samples were oxidised in different environments and the oxidation products formed were studied using various analytical chromatographic and spectroscopic techniques such as HPLC, FT-IR and NMR. It was found that commercial degradable polymer samples which are based on the ECO systems, degrade predominantly via the Norrish II process, whereas the other degradable systems studied (starch-filled polyethylene systems, transition metal systems, including metal carboxylate based polyethylene systems and the photoantioxidant-activator systems) photodegrade essentially via the Norrish I process. In all cases, the major photoxidation products extracted from the degradable polymer samples were found to be carboxylic acids, although, in the polymer itself a mixture of carbonyl containing products such as esters, lactones, ketones and aldehydes was observed. The study also found that the formation of these hydrophilic carbonyl products causes surface swelling of the polymer, thus making bioerosion possible. It was thus concluded that environmental degradation of LDPE is a two step process, the initiation stage being oxidation of the polymer which gives rise to bioassimilable products, which are consequently bioeroded in the second stage, (the biodegradation step). Recycling of the degradable polymer samples as 10% homogeneous and heterogeneous blends was carried out using a single screw extruder (180°C and 210°C) and an internal mixer (190°C). The study showed that commercial degradable polymer samples may be recycled with a minimal loss in their properties.