Application of Resilience concept for enhanced management of water supply systems

This paper presents an approach to developing indicators for expressing resilience of a generic water supply system. The system is contextualised as a meta-system consisting of three subsystems to represent the water catchment and reservoir, treatment plant and the distribution system supplying the end-users. The level of final service delivery to end-users is considered as a surrogate measure of systemic resilience. A set of modelled relationships are used to explore relationships between system components when placed under simulated stress. Conceptual system behaviour of specific types of simulated pressure is created for illustration of parameters for indicator development. The approach is based on the hypothesis that an in-depth knowledge of resilience would enable development of decision support system capability which in turn will contribute towards enhanced management of a water supply system. In contrast to conventional water supply system management approaches, a resilience approach facilitates improvement in system efficiency by emphasising awareness of points-of-intervention where system managers can adjust operational control measures across the meta-system (and within subsystems) rather than expansion of the system in entirety in the form of new infrastructure development.

Improving self care of patients with chronic disease using online personal health record

BACKGROUND: Effective management of chronic diseases such as prostate cancer is important. Research suggests a tendency to use self-care treatment options such as over-the-counter (OTC) complementary medications among prostate cancer patients. The current trend in patient-driven recording of health data in an online Personal Health Record (PHR) presents an opportunity to develop new data-driven approaches for improving prostate cancer patient care. However, the ability of current online solutions to share patients' data for better decision support is limited. An informatics approach may improve online sharing of self-care interventions among these patients. It can also provide better evidence to support decisions made during their self-managed care. AIMS: To identify requirements for an online system and describe a new case-based reasoning (CBR) method for improving self-care of advanced prostate cancer patients in an online PHR environment. METHOD: A non-identifying online survey was conducted to understand self-care patterns among prostate cancer patients and to identify requirements for an online information system. The pilot study was carried out between August 2010 and December 2010. A case-base of 52 patients was developed. RESULTS: The data analysis showed self-care patterns among the prostate cancer patients. Selenium (55%) was the common complementary supplement used by the patients. Paracetamol (about 45%) was the commonly used OTC by the patients. CONCLUSION: The results of this study specified requirements for an online case-based reasoning information system. The outcomes of this study are being incorporated in design of the proposed Artificial Intelligence (Al) driven patient journey browser system. A basic version of the proposed system is currently being considered for implementation.

Modification of advanced programmatic risk analysis and management model for the whole project life cycle’s risks

The advanced programmatic risk analysis and management model (APRAM) is one of the recently developed methods that can be used for risk analysis and management purposes considering schedule, cost, and quality risks simultaneously. However, this model considers those failure risks that occur only over the design and construction phases of a project’s life cycle. While it can be sufficient for some projects for which the required cost during the operating life is much less than the budget required over the construction period, it should be modified in relation to infrastructure projects because the associated costs during the operating life cycle are significant. In this paper, a modified APRAM is proposed, which can consider potential risks that might occur over the entire life cycle of the project, including technical and managerial failure risks. Therefore, the modified model can be used as an efficient decision-support tool for construction managers in the housing industry in which various alternatives might be technically available. The modified method is demonstrated by using a real building project, and this demonstration shows that it can be employed efficiently by construction managers. The Delphi method was applied in order to figure out the failure events and their associated probabilities. The results show that although the initial cost of a cold-formed steel structural system is higher than a conventional construction system, the former’s failure cost is much lower than the latter’s

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Representation of assertions in clinical free-­text using SNOMED CT

Information retrieval (IR) by clinicians in the healthcare setting is critical for informing clinical decision-making. However, a large part of this information is in the form of free-text and inhibits clinical decision support and effective healthcare services. This makes meaningful use of clinical free-­text in electronic health records (EHRs) for patient care a difficult task. Within the context of IR, given a repository of free-­text clinical reports, one might want to retrieve and analyse data for patients who have a known clinical finding.

Reasoning about component similarity in building product models from the construction perspective

Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

ICT to enhance the triangle of life : the soil, the seed, and the life-giver farmer

This paper reports on the outcomes of an ICT enabled social sustainability project “Green Lanka1” trialled in the Wilgamuwa village, which is situated in the Dambulla district of Sri Lanka. The main goals of the project were focused towards the provision of information about market prices, transportation options, agricultural decision support and modern agriculture practices of the farmer communities to improve their livelihood with the effective use of technologies. The project used Web and Mobile (SMS) enabled systems. The Green Lanka project was sponsored by the Information Communication Technology Agency (ICTA) of Sri Lanka under the Institutional Capacity Building Programme (ICBP) grant scheme which was sponsored by the World Bank. Six hundred families in Wilgamuwa village participated in the project activities. The project was designed, executed and studied through an Action Research approach. The lessons learned through the project activities provide an important understanding of the complex interaction between different stakeholders in the process of implementation of ICT enabled solutions within digitally divided societies. The paper analyses the processes used to reduce the resistance to change and improved involvement of farmer communities in ICT enabled projects. It also analyses the interaction between stakeholders involved in design and implementation of the project activities to improve the chances of project success.

A comparative analysis of the integration of SOA elements in widely-used enterprise architecture frameworks

In recent years, enterprise architecture (EA) has captured increasing interest as a means to systematically consolidate and manage various enterprise artefacts in order to provide holistic decision support for business/IT alignment and business/IT landscapes management. To provide a holistic perspective on the enterprise over time, EA frameworks need to co-evolve with the changes in the enterprise and its IT over time. In this paper we focus on the emergence of Service-Oriented Architecture (SOA). There is a need to integrate SOA with EA to keep EA relevant and to use EA products to help drive successful SOA. This paper investigates and compares the integration of SOA elements in five widely used EA frameworks: Archimate, The Open Group Architecture Framework (TOGAF), Federal Enterprise Architecture Framework (FEAF), Department of Defence Architecture Framework (DoDAF) and the Ministry of Defence Architecture Framework (MODAF). It identifies what SOA elements are considered and their relative position in the overall structure. The results show that services and related elements are far from being well-integrated constructs in current EA frameworks and that the different EA frameworks integrated SOA elements in substantially different ways. Our results can support the academic EA and SOA communities with a closer and more consistent integration of EA and SOA and support practitioners in identifying an EA framework that provides the SOA support that matches their requirements.

How collaborative technology supports cognitive processes in collaborative process modeling : a capabilities-gains-outcome model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.

Evidence based healthcare planning in developing countries : an informatics perspective

Most of the national Health Information Systems (HIS) in resource limited developing countries do not serve the purpose of management support and thus the service is adversely affected. While emphasising the importance of timely and accurate health information in decision making in healthcare planning, this paper explains that Health Management Information System Failure is commonly seen in developing countries as well as the developed countries. It is suggested that the possibility of applying principles of Health Informatics and the technology of Decision Support Systems should be seriously considered to improve the situation. A brief scientific explanation of the evolution of these two disciplines is included.

Identification and evaluation of service bundles for governmental one-stop portals

Recent advances in the area of ‘Transformational Government’ position the citizen at the centre of focus. This paradigm shift from a department-centric to a citizen-centric focus requires governments to re-think their approach to service delivery, thereby decreasing costs and increasing citizen satisfaction. The introduction of franchises as a virtual business layer between the departments and their citizens is intended to provide a solution. Franchises are structured to address the needs of citizens independent of internal departmental structures. For delivering services online, governments pursue the development of a One-Stop Portal, which structures information and services through those franchises. Thus, each franchise can be mapped to a specific service bundle, which groups together services that are deemed to be of relevance to a specific citizen need. This study focuses on the development and evaluation of these service bundles. In particular, two research questions guide the line of investigation of this study: Research Question 1): What methods can be used by governments to identify service bundles as part of governmental One-Stop Portals? Research Question 2): How can the quality of service bundles in governmental One-Stop Portals be evaluated? The first research question asks about the identification of suitable service bundle identification methods. A literature review was conducted, to, initially, conceptualise the service bundling task, in general. As a consequence, a 4-layer model of service bundling and a morphological box were created, detailing characteristics that are of relevance when identifying service bundles. Furthermore, a literature review of Decision-Support Systems was conducted to identify approaches of relevance in different bundling scenarios. These initial findings were complemented by targeted studies of multiple leading governments in the e-government domain, as well as with a local expert in the field. Here, the aim was to identify the current status of online service delivery and service bundling in practice. These findings led to the conceptualising of two service bundle identification methods, applicable in the context of Queensland Government: On the one hand, a provider-driven approach, based on service description languages, attributes, and relationships between services was conceptualised. As well, a citizen-driven approach, based on analysing the outcomes from content identification and grouping workshops with citizens, was also conceptualised. Both methods were then applied and evaluated in practice. The conceptualisation of the provider-driven method for service bundling required the initial specification of relevant attributes that could be used to identify similarities between services called relationships; these relationships then formed the basis for the identification of service bundles. This study conceptualised and defined seven relationships, namely ‘Co-location’, ‘Resource’, ‘Co-occurrence’, ‘Event’, ‘Consumer’, ‘Provider’, and ‘Type’. The relationships, and the bundling method itself, were applied and refined as part of six Action Research cycles in collaboration with the Queensland Government. The findings show that attributes and relationships can be used effectively as a means for bundle identification, if distinct decision rules are in place to prescribe how services are to be identified. For the conceptualisation of the citizen-driven method, insights from the case studies led to the decision to involve citizens, through card sorting activities. Based on an initial list of services, relevant for a certain franchise, participating citizens grouped services according to their liking. The card sorting activity, as well as the required analysis and aggregation of the individual card sorting results, was analysed in depth as part of this study. A framework was developed that can be used as a decision-support tool to assist with the decision of what card sorting analysis method should be utilised in a given scenario. The characteristic features associated with card sorting in a government context led to the decision to utilise statistical analysis approaches, such as cluster analysis and factor analysis, to aggregate card sorting results. The second research question asks how the quality of service bundles can be assessed. An extensive literature review was conducted focussing on bundle, portal, and e-service quality. It was found that different studies use different constructs, terminology, and units of analysis, which makes comparing these models a difficult task. As a direct result, a framework was conceptualised, that can be used to position past and future studies in this research domain. Complementing the literature review, interviews conducted as part of the case studies with leaders in e-government, indicated that, typically, satisfaction is evaluated for the overall portal once the portal is online, but quality tests are not conducted during the development phase. Consequently, a research model which appropriately defines perceived service bundle quality would need to be developed from scratch. Based on existing theory, such as Theory of Reasoned Action, Expectation Confirmation Theory, and Theory of Affordances, perceived service bundle quality was defined as an inferential belief. Perceived service bundle quality was positioned within the nomological net of services. Based on the literature analysis on quality, and on the subsequent work of a focus group, the hypothesised antecedents (descriptive beliefs) of the construct and the associated question items were defined and the research model conceptualised. The model was then tested, refined, and finally validated during six Action Research cycles. Results show no significant difference in higher quality or higher satisfaction among users for either the provider-driven method or for the citizen-driven method. The decision on which method to choose, it was found, should be based on contextual factors, such as objectives, resources, and the need for visibility. The constructs of the bundle quality model were examined. While the quality of bundles identified through the citizen-centric approach could be explained through the constructs ‘Navigation’, ‘Ease of Understanding’, and ‘Organisation’, bundles identified through the provider-driven approach could be explained solely through the constructs ‘Navigation’ and ‘Ease of Understanding’. An active labelling style for bundles, as part of the provider-driven Information Architecture, had a larger impact on ‘Quality’ than the topical labelling style used in the citizen-centric Information Architecture. However, ‘Organisation’, reflecting the internal, logical structure of the Information Architecture, was a significant factor impacting on ‘Quality’ only in the citizen-driven Information Architecture. Hence, it was concluded that active labelling can compensate for a lack of logical structure. Further studies are needed to further test this conjecture. Such studies may involve building alternative models and conducting additional empirical research (e.g. use of an active labelling style for the citizen-driven Information Architecture). This thesis contributes to the body of knowledge in several ways. Firstly, it presents an empirically validated model of the factors explaining and predicting a citizen’s perception of service bundle quality. Secondly, it provides two alternative methods that can be used by governments to identify service bundles in structuring the content of a One-Stop Portal. Thirdly, this thesis provides a detailed narrative to suggest how the recent paradigm shift in the public domain, towards a citizen-centric focus, can be pursued by governments; the research methodology followed by this study can serve as an exemplar for governments seeking to achieve a citizen-centric approach to service delivery.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

Designing the information architecture of governmental one-stop portals : on the application and analysis of card sorting

The latest paradigm shift in government, termed Transformational Government, puts the citizen in the centre of attention. Including citizens in the design of online one-stop portals can help governmental organisations to become more customer focussed. This study describes the initial efforts of an Australian state government to develop an information architecture to structure the content of their future one-stop portal. Hereby, card sorting exercises have been conducted and analysed, utilising contemporary approaches found in academic and non-scientific literature. This paper describes the findings of the card sorting exercises in this particular case and discusses the suitability of the applied approaches in general. These are distinguished into non-statistical, statistical, and hybrid approaches. Thus, on the one hand, this paper contributes to academia by describing the application of different card sorting approaches and discussing their strengths and weaknesses. On the other hand, this paper contributes to practice by explaining the approach that has been taken by the authors’ research partner in order to develop a customer-focussed governmental one-stop portal. Thus, they provide decision support for practitioners with regard to different analysis methods that can be used to complement recent approaches in Transformational Government.

Building knowledge capabilities : an organisational learning approach

The communal nature of knowledge production predicts the importance of creating learning organisations where knowledge arises out of processes that are personal, social, situated and active. It follows that workplaces must provide both formal and informal learning opportunities for interaction with ideas and among individuals. This grounded theory for developing contemporary learning organisations harvests insights from the knowledge management, systems sciences, and educational learning literatures. The resultant hybrid theoretical framework informs practical application, as reported in a case study that harnesses the accelerated information exchange possibilities enabled through web 2.0 social networking and peer production technologies. Through complementary organisational processes, 'meaning making' is negotiated in formal face-to-face meetings supplemented by informal 'boundary spanning' dialogue. The organisational capacity building potential of this participatory and inclusive approach is illustrated through the example of the Dr. Martin Luther King, Jr. Library in San Jose, California, USA. As an outcome of the strategic planning process at this joint city-university library, communication, decision-making, and planning structures, processes, and systems were re-invented. An enterprise- level redesign is presented, which fosters contextualising information interactions for knowledge sharing and community building. Knowledge management within this context envisions organisations as communities where knowledge, identity, and learning are situated. This framework acknowledges the social context of learning - i.e., that knowledge is acquired and understood through action, interaction, and sharing with others. It follows that social networks provide peer-to-peer enculturation through intentional exchange of tacit information made explicit. This, in turn, enables a dynamic process experienced as a continuous spiral that perpetually elevates collective understanding and enables knowledge creation.