Decision support system for contractor pre-qualification : artificial neural network model

The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

An effective approach to verbose queries using a limited dependencies language model

Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Conceptualisation and facilitation of SOA governance

As organisations strive to improve their capabilities in the areas of Service Management and Service-oriented Architectures (SOA), SOA Governance is becoming an increasingly important success factor. However, the concept of SOA Governance is complex and not well-understood, and the adoption of an adequate SOA Governance approach in an organisation can be difficult. Tools that support SOA Governance mostly have a technical bias and rarely address organisational aspects. In this paper, we contribute to the field by specifying a conceptual meta model for SOA Governance that integrates the structure of major IT and SOA Governance frameworks into one consolidated view. By presenting this conceptualisation and a corresponding prototypical implementation of a tool that supports SOA Governance maturity assessment, reference framework exploration and company-specific tailoring of SOA Governance, we provide insights into the first step of a Design Science research project, i.e. the development of an important IT artefact.

The role of self-efficacy in dental patients’ brushing and flossing: Testing an extended Health Belief Model

Objective: In an effort to examine the decreasing oral health trend of Australian dental patients, the Health Belief Model (HBM) was utilised to understand the beliefs underlying brushing and flossing self-care. The HBM states that perception of severity and susceptibility to inaction and an estimate of the barriers and benefits of behavioural performance influences people’s health behaviours. Self-efficacy, confidence in one’s ability to perform oral self-care, was also examined. Methods: In dental waiting rooms, a community sample (N = 92) of dental patients completed a questionnaire assessing HBM variables and self-efficacy, as well as their performance of the oral hygiene behaviours of brushing and flossing. Results: Partial support only was found for the HBM with barriers emerging as the sole HBM factor influencing brushing and flossing behaviours. Self-efficacy significantly predicted both oral hygiene behaviours also. Conclusion: Support was found for the control factors, specifically a consideration of barriers and self-efficacy, in the context of understanding dental patients’ oral hygiene decisions. Practice implications: Dental professionals should encourage patients’ self-confidence to brush and floss at recommended levels and discuss strategies that combat barriers to performance, rather than emphasising the risks of inaction or the benefits of oral self-care.

Creating an asset registry for railway electrical traction equipment with open standards

An asset registry arguably forms the core system that needs to be in place before other systems can operate or interoperate. Most systems have rudimentary asset registry functionality that store assets, relationships, or characteristics, and this leads to different asset management systems storing similar sets of data in multiple locations in an organisation. As organisations have been slowly moving their information architecture toward a service-oriented architecture, they have also been consolidating their multiple data stores, to form a “single point of truth”. As part of a strategy to integrate several asset management systems in an Australian railway organisation, a case study for developing a consolidated asset registry was conducted. A decision was made to use the MIMOSA OSA-EAI CRIS data model as well as the OSA-EAI Reference Data in building the platform due to the standard’s relative maturity and completeness. A pilot study of electrical traction equipment was selected, and the data sources feeding into the asset registry were primarily diagrammatic based. This paper presents the pitfalls encountered, approaches taken, and lessons learned during the development of the asset registry.

Competence in Intelligence Testing : A Training Model for Postgraduate Psychology Students

The assessment of intellectual ability is a core competency in psychology. The results of intelligence tests have many potential implications and are used frequently as the basis for decisions about educational placements, eligibility for various services, and admission to specific groups. Given the importance of intelligence test scores, accurate test administration and scoring are essential; yet there is evidence of unacceptably high rates of examiner error. This paper discusses competency and postgraduate training in intelligence testing and presents a training model for postgraduate psychology students. The model aims to achieve high levels of competency in intelligence testing through a structured method of training, practice and feedback that incorporates peer support, self-reflection and multiple methods for evaluating competency.

Practice briefing : Is BOT the best financing model to procure infrastructure projects? A case study of the Hong Kong-Shuhai-Macau Bridge

Abstract: Purpose – Several major infrastructure projects in the Hong Kong Special Administrative Region (HKSAR) have been delivered by the build-operate-transfer (BOT) model since the 1960s. Although the benefits of using BOT have been reported abundantly in the contemporary literature, some BOT projects were less successful than the others. This paper aims to find out why this is so and to explore whether BOT is the best financing model to procure major infrastructure projects. Design/methodology/approach – The benefits of BOT will first be reviewed. Some completed BOT projects in Hong Kong will be examined to ascertain how far the perceived benefits of BOT have been materialized in these projects. A highly profiled project, the Hong Kong-Zhuhai-Macau Bridge, which has long been promoted by the governments of the People's Republic of China, Macau Special Administrative Region and the HKSAR that BOT is the preferred financing model, but suddenly reverted back to the traditional financing model to be funded primarily by the three governments with public money instead, will be studied to explore the true value of the BOT financial model. Findings – Six main reasons for this radical change are derived from the analysis: shorter take-off time for the project; difference in legal systems causing difficulties in drafting BOT agreements; more government control on tolls; private sector uninterested due to unattractive economic package; avoid allegation of collusion between business and the governments; and a comfortable financial reserve possessed by the host governments. Originality/value – The findings from this paper are believed to provide a better understanding to the real benefits of BOT and the governments' main decision criteria in delivering major infrastructure projects.

Validating the IS-Impact model : two exploratory case studies in China and Malaysia

For over a decade, IT expenditure in China and Malaysia has shown a significant increase, as organisations in these countries are increasingly dependent on information systems (IS) for achieving strategic advantages and business benefits. However, there have been numerous reports of dissatisfaction with IS, and in some cases the effectiveness of the information systems have yet to be reviewed. Two exploratory case studies reported in this paper are the first phase of an overall research in validating the IS-Impact model introduced by Gable, Sedera and Chan in two countries: China and Malaysia. This validation research aims to produce a standard measuring model across different contexts. The purpose of this paper is to present preliminary findings from two exploratory case studies, attempt to test the feasibility of the research design and to investigate applicability of the IS-Impact model in Chinese and Malaysian organisations. Twenty-nine respondents from a Chinese private company and seventeen respondents from a state government in Malaysia were involved in these studies. Findings indicated that most of existing IS-Impact measures are applicable in the study contexts, however, there are some new measures informed by the respondents. Feedback from the case studies also suggested necessary modifications to the Mandarin instrument.

A robust reactive scheduling model for intensive care units

The ICU is an integral part of any hospital and is under great load from patient arrivals as well as resource limitations. Scheduling of patients in the ICU is complicated by the two general types; elective surgery and emergency arrivals. This complicated situation is handled by creating a tentative initial schedule and then reacting to uncertain arrivals as they occur. For most hospitals there is little or no flexibility in the number of beds that are available for use now or in the future. We propose an integer programming model to handle a parallel machine reacting system for scheduled and unscheduled arrivals.

Extending the IS-Impact Model into the higher education sector

The study addresses known limitations of what may be the most important dependent variable in Information Systems (IS) research; IS-Success or IS-Impact. The study is expected to force a deeper understanding of the broad notions of IS success and impact. The aims of the research are to: (1) enhance the robustness and minimize limitations of the IS-Impact model, and (2) introduce and operationalise a more rigorously validated IS Impact measurement model to Universities, as a reliable model for evaluating different Administrative Systems. In extending and further generalizing the IS-Impact model, the study will address contemporary validation issues.

Validating the IS-Impact Model At Queensland University Of Technology (QUT): Part A

The overall research aims to develop a standardised instrument to measure the impacts resulting from contemporary Information Systems (IS). The research adopts the IS-Impact measurement model, introduced by Gable et al, (2008), as its theoretical foundation, and applies the extension strategy described by Berthon et al. (2002); extending both theory and the context, where the new context is the Human Resource (HR) system. The research will be conducted in two phases, the exploratory phase and the specification phase. The purpose of this paper is to present the findings of the exploratory phase. 134 respondents from a major Australian University were involved in this phase. The findings have supported most of the existing IS-Impact model’s credibility. However, some textual data may suggest new measures for the IS-Impact model, while the low response rate or the averting of some may suggest the elimination of some measures from the model.

CTCombine : rotating and combining CT data with an accurate detector model, to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

Differences between students and non-students’ willingness to donate to a charitable organisation

This paper reports on a comparative study of students and non-students that investigates which psycho-social factors influence intended donation behaviour within a single organisation that offers multiple forms of donation activity. Additionally, the study examines which media channels are more important to encourage donation. A self-administered survey instrumentwas used and a sample of 776 respondents recruited. Logistic regressions and a Chow test were used to determine statistically significant differences between the groups. For donatingmoney, importance of charity and attitude towards charity influence students, whereas only importance of need significantly influences non-students. For donating time, no significant influences were found for non-students, however, importance of charity and attitude towards charity were significant for students. Importance of need was significant for both students and non-students for donating goods, with importance of charity also significant for students. Telephone and television channels were important for both groups. However, Internet, email and short messaging services were more important for students, providing opportunities to enhance this group’s perceptions of the importance of the charity, and the importance of the need, which ultimately impacts on their attitudes towards the charity. These differences highlight the importance of charities focussing on those motivations and attitudes that are important to a particular target segment and communicating through appropriate media channels for these segments.

Employee engagement : the development of a three dimensional model of engagement; and an exploration of its relationship with affective leader behaviours

This study was designed to examine affective leader behaviours, and their impact on cognitive, affective and behavioural engagement. Researchers (e.g., Cropanzano & Mitchell, 2005; Moorman et al., 1998) have called for more research to be directed toward modelling and testing sets of relationships which better approximate the complexity associated with contemporary organisational experience. This research has attempted to do this by clarifying and defining the construct of engagement, and then by examining how each of the engagement dimensions are impacted by affective leader behaviours. Specifically, a model was tested that identifies leader behaviour antecedents of cognitive, affective and behavioural engagement. Data was collected from five public-sector organisations. Structural equation modelling was used to identify the relationships between the engagement dimensions and leader behaviours. The results suggested that affective leader behaviours had a substantial direct impact on cognitive engagement, which in turn influenced affective engagement, which then influenced intent to stay and extra-role performance. The results indicated a directional process for engagement, but particularly highlighted the significant impact of affective leader behaviours as an antecedent to engagement. In general terms, the findings will provide a platform from which to develop a robust measure of engagement, and will be helpful to human resource practitioners interested in understanding the directional process of engagement and the importance of affective leadership as an antecedent to engagement.