Towards an integrated maturity model of asset management capabilities

Asset service organisations often recognize asset management as a core competence to deliver benefits to their business. But how do organizations know whether their asset management processes are adequate? Asset management maturity models, which combine best practices and competencies, provide a useful approach to test the capacity of organisations to manage their assets. Asset management frameworks are required to meet the dynamic challenges of managing assets in contemporary society. Although existing models are subject to wide variations in their implementation and sophistication, they also display a distinct weakness in that they tend to focus primarily on the operational and technical level and neglect the levels of strategy, policy and governance as well as the social and human resources – the people elements. Moreover, asset management maturity models have to respond to the external environmental factors, including such as climate change and sustainability, stakeholders and community demand management. Drawing on five dimensions of effective asset management – spatial, temporal, organisational, statistical, and evaluation – as identified by Amadi Echendu et al. [1], this paper carries out a comprehensive comparative analysis of six existing maturity models to identify the gaps in key process areas. Results suggest incorporating these into an integrated approach to assess the maturity of asset-intensive organizations. It is contended that the adoption of an integrated asset management maturity model will enhance effective and efficient delivery of services.

Intrusion detection in distributed systems, an approach based on taint marking

This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

A novel method for finding similarities between unordered trees using matrix data model

Trees are capable of portraying the semi-structured data which is common in web domain. Finding similarities between trees is mandatory for several applications that deal with semi-structured data. Existing similarity methods examine a pair of trees by comparing through nodes and paths of two trees, and find the similarity between them. However, these methods provide unfavorable results for unordered tree data and result in yielding NP-hard or MAX-SNP hard complexity. In this paper, we present a novel method that encodes a tree with an optimal traversing approach first, and then, utilizes it to model the tree with its equivalent matrix representation for finding similarity between unordered trees efficiently. Empirical analysis shows that the proposed method is able to achieve high accuracy even on the large data sets.

A model for research supervision of international students in engineering and information technology disciplines

A large proportion (over 12 per cent) of international and non-English speaking background (NESB) postgraduate research students enrol in engineering and information technology (IT) programs in Australian universities. They find themselves in an advanced research culture, and are technically and scientifically challenged early in their programs. This is in addition to cultural, social and religious isolation and linguistic barriers they have to contend with. The project team surveyed this cohort at QUT and UWA, on the hypothesis that they face challenges that are more discipline-specific. The results of the survey indicate that existing supervisory frameworks which are limited to linguistic contexts are not fully assisting these students and supervisors to achieve high quality research. The goal of this project is to extend these supervisory frameworks to a holistic model that will address the unique needs and supervisory issues these students face in engineering and IT disciplines. The model will be useable by all other Australian universities.

Well-being, satisfaction and commitment : the substitutable nature of resources for maternity hospital nurses

Abstract Aims. To investigate the relationship between three types of organizational resources (job control, social support and organizational justice) and the impact of job demands on nurse’s well-being and attitudes towards their work. Background. The negative impact of work-related stress on nurse’s health and attitudes towards their work has been established. Increasingly, research is focusing on the role of organizational resources in reducing the impact of work related stress. Design. Cross-sectional survey. Method. Data collected in November 2008 from 226 Australian nurses and midwives were analysed using the full Job Strain Model with the addition of organizational justice variables. Multiple regression analyses explored the relationships among job control, job demands, three sources of social support and four types of organizational justice on well-being and work attitudes. Results. The overall regression models explained a significant amount of variance in well-being, job satisfaction and organizational commitment. Significant main effects were evident for support variables and organizational justice variables on well-being and job satisfaction. Interactions between job control and supervisor support and between job demands and supervisor support were evident for job satisfaction. Conclusions. Supervisor support and organizational justice have significant relationships with nurses’ well-being and job satisfaction. More broadly, the findings suggest that, in the triple-matching approach from a work-stressor to a resource to a work outcome, personal, supervisory and organizational resources may be substitutable. These findings provide nurse management with empirical endorsement for the development and delivery of the organization’s resources for nursing staff.

Service-oriented architecture integration within enterprise architecture : a-priori model

This paper proposes that critical realism can provide a useful theoretical foundation to study enterprise architecture (EA) evolution. Specifically it will investigate the practically relevant and academically challenging question of how EAs integrate the Service-oriented Architecture (SOA). Archer’s Morphogenetic theory is used as an analytical approach to distinguish the architectural conditions under which SOA is introduced, to study the relationships between these conditions and SOA introduction, and to reflect on EA evolution (elaborations) that then take place. The focus lies on the reasons why EA evolution takes place (or not) and what architectural changes happen. This paper uses the findings of a literature review to build an a-priori model informed by Archer’s theory to understand EA evolution in a field that often lacks a solid theoretical groundwork. The findings are threefold. First, EA can evolve on different levels (different integration outcomes). Second, the integration outcomes are classified into three levels: business architecture, information systems architecture and technology architecture. Third, the analytical separation using Archer’s theory is helpful in order to understand how these different integration outcomes are generated.

Single-agent versus combination chemotherapy in patients with advanced non-small cell lung cancer and a performance status of 2 : prognostic factors and treatment selection based on two large randomized clinical trials

Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

Thymidylate synthase expression and outcome of patients receiving pemetrexed for advanced nonsquamous non-small-cell lung cancer in a prospective blinded assessment phase II clinical trial

INTRODUCTION In retrospective analyses of patients with nonsquamous non-small-cell lung cancer treated with pemetrexed, low thymidylate synthase (TS) expression is associated with better clinical outcomes. This phase II study explored this association prospectively at the protein and mRNA-expression level. METHODS Treatment-naive patients with nonsquamous non-small-cell lung cancer (stage IIIB/IV) had four cycles of first-line chemotherapy with pemetrexed/cisplatin. Nonprogressing patients continued on pemetrexed maintenance until progression or maximum tolerability. TS expression (nucleus/cytoplasm/total) was assessed in diagnostic tissue samples by immunohistochemistry (IHC; H-scores), and quantitative reverse-transcriptase polymerase chain reaction. Cox regression was used to assess the association between H-scores and progression-free/overall survival (PFS/OS) distribution estimated by the Kaplan-Meier method. Maximal χ analysis identified optimal cutpoints between low TS- and high TS-expression groups, yielding maximal associations with PFS/OS. RESULTS The study enrolled 70 patients; of these 43 (61.4%) started maintenance treatment. In 60 patients with valid H-scores, median (m) PFS was 5.5 (95% confidence interval [CI], 3.9-6.9) months, mOS was 9.6 (95% CI, 7.3-15.7) months. Higher nuclear TS expression was significantly associated with shorter PFS and OS (primary analysis IHC, PFS: p < 0.0001; hazard ratio per 1-unit increase: 1.015; 95%CI, 1.008-1.021). At the optimal cutpoint of nuclear H-score (70), mPFS in the low TS- versus high TS-expression groups was 7.1 (5.7-8.3) versus 2.6 (1.3-4.1) months (p = 0.0015; hazard ratio = 0.28; 95%CI, 0.16-0.52; n = 40/20). Trends were similar for cytoplasm H-scores, quantitative reverse-transcriptase polymerase chain reaction and other clinical endpoints (OS, response, and disease control). CONCLUSIONS The primary endpoint was met; low TS expression was associated with longer PFS. Further randomized studies are needed to explore nuclear TS IHC expression as a potential biomarker of clinical outcomes for pemetrexed treatment in larger patient cohorts. © 2013 by the International Association for the Study of Lung Cancer.

EGFR expression as a predictor of survival for first-line chemotherapy plus cetuximab in patients with advanced non-small-cell lung cancer : analysis of data from the phase 3 FLEX study

Background: Findings from the phase 3 First-Line ErbituX in lung cancer (FLEX) study showed that the addition of cetuximab to first-line chemotherapy significantly improved overall survival compared with chemotherapy alone (hazard ratio [HR] 0·871, 95% CI 0·762-0·996; p=0·044) in patients with advanced non-small-cell lung cancer (NSCLC). To define patients benefiting most from cetuximab, we studied the association of tumour EGFR expression level with clinical outcome in FLEX study patients. Methods: We used prospectively collected tumour EGFR expression data to generate an immunohistochemistry score for FLEX study patients on a continuous scale of 0-300. We used response data to select an outcome-based discriminatory threshold immunohistochemistry score for EGFR expression of 200. Treatment outcome was analysed in patients with low (immunohistochemistry score <200) and high (≥200) tumour EGFR expression. The primary endpoint in the FLEX study was overall survival. We analysed patients from the FLEX intention-to-treat (ITT) population. The FLEX study is registered with ClinicalTrials.gov, number NCT00148798. Findings: Tumour EGFR immunohistochemistry data were available for 1121 of 1125 (99·6%) patients from the FLEX study ITT population. High EGFR expression was scored for 345 (31%) evaluable patients and low for 776 (69%) patients. For patients in the high EGFR expression group, overall survival was longer in the chemotherapy plus cetuximab group than in the chemotherapy alone group (median 12·0 months [95% CI 10·2-15·2] vs 9·6 months [7·6-10·6]; HR 0·73, 0·58-0·93; p=0·011), with no meaningful increase in side-effects. We recorded no corresponding survival benefit for patients in the low EGFR expression group (median 9·8 months [8·9-12·2] vs 10·3 months [9·2-11·5]; HR 0·99, 0·84-1·16; p=0·88). A treatment interaction test assessing the difference in the HRs for overall survival between the EGFR expression groups suggested a predictive value for EGFR expression (p=0·044). Interpretation: High EGFR expression is a tumour biomarker that can predict survival benefit from the addition of cetuximab to first-line chemotherapy in patients with advanced NSCLC. Assessment of EGFR expression could offer a personalised treatment approach in this setting. Funding: Merck KGaA. © 2012 Elsevier Ltd.

Indexing and efficient instance-based retrieval of process models using untanglings

Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.

A higher education quality assurance model for small states : the Maldives case study

Increasing globalisation and local expansion of Higher Education presents challenges to manage quality of the education services. This study investigated key stakeholders' perspectives on what constitutes key elements and attributes of an effective Quality Assurance (QA) system in Higher Education. The findings highlighted the need for: i) legislation to support a strong QA regulatory framework, ii) independence of the QA agency, iii) development of minimum quality standards through broad stakeholder involvement, and iv) a cyclical approach. The findings of this study proposed a QA model which has implications for strengthening of HE QA systems of Small State.

A time-based quantitative approach for selecting lean strategies for manufacturing organisations

Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.

Experience of being an advanced practice nurse within Australian acute care settings : a systematic review of qualitative evidence

Background Nationally and internationally, advanced practice nurses are working under various titles and in different contexts to address gaps within healthcare systems. Analysis of advanced practice roles in different countries has been undertaken, but due to variations in cultural, geographical and professional factors, it is difficult and perhaps ineffectual to compare roles between countries. Contextual factors may also affect the actual experience of being an advanced practice nurse. A systematic review was therefore undertaken of qualitative evidence on the experience of being an advanced practice nurse in Australia, to provide deeper understanding of the role in the defined context. Methods The review followed the method for qualitative synthesis as per the Joanna Briggs Institute. An extensive search was undertaken of databases and online resources to find published and unpublished studies. Papers from 1990 to October 2011 which met specified inclusion criteria were appraised using the Joanna Briggs Institute Qualitative Assessment and Review Instrument. Results Three published studies and one unpublished dissertation were included in the review. From these studies, 216 findings were extracted and these were formed into 18 categories. Six meta-syntheses grouped under the headings of expert knowledge, confidence, education, relationships, negative experiences and patient-centred experience were created. Organisational factors impact greatly on the experience, professionally and personally. Conclusions Heterogeneity of role titles makes synthesis a difficult process, but contextualising the population provides a pragmatic approach to informing the status of the advanced practice nurse discourse. The review identifies positive and negative experiences of being an advanced practice nurse in Australian acute care settings with overlapping and intertwining findings that reinforce the complexity of the role.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Locally weighted learning model predictive control for nonlinear and time varying dynamics

This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.