On model typing

Where object-oriented languages deal with objects as described by classes, model-driven development uses models, as graphs of interconnected objects, described by metamodels. A number of new languages have been and continue to be developed for this model- based paradigm, both for model transformation and for general programming using models. Many of these use single-object approaches to typing, derived from solutions found in object-oriented systems, while others use metamodels as model types, but without a clear notion of polymorphism. Both of these approaches lead to brittle and overly restrictive reuse characteristics. In this paper we propose a simple extension to object-oriented typing to better cater for a model-oriented context, including a simple strategy for typing models as a collection of interconnected objects. We suggest extensions to existing type system formalisms to support these concepts and their manipulation. Using a simple example we show how this extended approach permits more flexible reuse, while preserving type safety.

Generalised self-efficacy in relation to the life transitions of adult learners in a university setting : towards a narrative constructivist model of self-regulation

This paper demonstrates a model of self-regulation based on a qualitative research project with adult learners undertaking an undergraduate degree. The narrative about the participant’s life transitions, co-constructed with the researcher, yielded data about their generalised self-efficacy and resulted in a unique self-efficacy narrative for each participant. A model of self-regulation is proposed with potential applications for coaching, counselling and psychotherapy. A narrative method was employed to construct narratives about an individual’s self-efficacy in relation to their experience of learning and life transitions. The method involved a cyclical and iterative process using qualitative interviews to collect life history data from participants. In addition, research participants completed reflective homework tasks, and this data was included in the participant’s narratives. A highly collaborative method entailed narratives being co-constructed by researcher and research participants as the participants were guided in reflecting on their experience in relation to learning and life transitions; the reflection focused on behaviour, cognitions and emotions that constitute a sense of self-efficacy. The analytic process used was narrative analysis, in which life is viewed as constructed and experienced through the telling and retelling of stories and hence the analysis is the creation of a coherent and resonant story. The method of constructing self-efficacy narratives was applied to a sample of mature aged students starting an undergraduate degree. The research outcomes confirmed a three-factor model of self-efficacy, comprising three interrelated stages: initiating action, applying effort, and persistence in overcoming difficulties. Evaluation of the research process by participants suggested that they had gained an enhanced understanding of self-efficacy from their participation in the research process, and would be able to apply this understanding to their studies and other endeavours in the future. A model of self-regulation is proposed as a means for coaches, counsellors and psychotherapists working from a narrative constructivist perspective to assist clients facing life transitions by helping them generate selfefficacious cognitions, emotions and behaviour.

Validation of the MEASURE automobile emissions model : a statistical analysis

The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized emission rates for various motor vehicle groups as a function of the conditions under which the vehicles are operating. The validation of aggregate measurements, such as speed and acceleration profile, is performed on an independent data set using three statistical criteria. The MEASURE algorithms have proved to provide significant improvements in both average emission estimates and explanatory power over some earlier models for pollutants across almost every operating cycle tested.

Mineralized human primary osteoblast matrices as a model system to analyse interactions of prostate cancer cells with the bone microenvironment

Prostate cancer metastasis is reliant on the reciprocal interactions between cancer cells and the bone niche/micro-environment. The production of suitable matrices to study metastasis, carcinogenesis and in particular prostate cancer/bone micro-environment interaction has been limited to specific protein matrices or matrix secreted by immortalised cell lines that may have undergone transformation processes altering signaling pathways and modifying gene or receptor expression. We hypothesize that matrices produced by primary human osteoblasts are a suitable means to develop an in vitro model system for bone metastasis research mimicking in vivo conditions. We have used a decellularized matrix secreted from primary human osteoblasts as a model for prostate cancer function in the bone micro-environment. We show that this collagen I rich matrix is of fibrillar appearance, highly mineralized, and contains proteins, such as osteocalcin, osteonectin and osteopontin, and growth factors characteristic of bone extracellular matrix (ECM). LNCaP and PC3 cells grown on this matrix, adhere strongly, proliferate, and express markers consistent with a loss of epithelial phenotype. Moreover, growth of these cells on the matrix is accompanied by the induction of genes associated with attachment, migration, increased invasive potential, Ca2+ signaling and osteolysis. In summary, we show that growth of prostate cancer cells on matrices produced by primary human osteoblasts mimics key features of prostate cancer bone metastases and thus is a suitable model system to study the tumor/bone micro-environment interaction in this disease.

Creativity, knowledge, engagement : keys to finding the right governance model for a regional community precinct

This paper investigates the Cooroy Mill community precinct (Sunshine Coast, Queensland), as a case study, seeking to understand the way local dynamics interplay and work with the community strengths to build a governance model of best fit. As we move to an age of ubiquitous computing and creative economies, the definition of public place and its governance take on new dimensions, which – while often utilizing models of the past – will need to acknowledge and change to the direction of the future. This paper considers a newly developed community precinct that has been built on three key principles: to foster creative expression with new media, to establish a knowledge economy in a regional area, and to subscribe to principles of community engagement. The study involved qualitative interviews with key stakeholders and a review of common practice models of governance along a spectrum from community control to state control. The paper concludes with a call for governance structures that are locally situated and tailored, inclusive, engaging, dynamic and flexible in order to build community capacity, encourage creativity, and build knowledge economies within emerging digital media cityscapes.

Investigating the effects of preinduction on human adipose-derived precursor cells in an athymic rat model

The osteogenic potential of human adipose-derived precursor cells seeded on medical-grade polycaprolactone-tricalcium phosphate scaffolds was investigated in this in vivo study. Three study groups were investigated: (1) induced—stimulated with osteogenic factors only after seeding into scaffold; (2) preinduced—induced for 2 weeks before seeding into scaffolds; and (3) uninduced—cells without any introduced induction. For all groups, scaffolds were implanted subcutaneously into the dorsum of athymic rats. The scaffold/cell constructs were harvested at the end of 6 or 12 weeks and analyzed for osteogenesis. Gross morphological examination using scanning electron microscopy indicated good integration of host tissue with scaffold/cell constructs and extensive tissue infiltration into the scaffold interior. Alizarin Red histology and immunostaining showed a heightened level of mineralization and an increase in osteonectin, osteopontin, and collagen type I protein expression in both the induced and preinduced groups compared with the uninduced groups. However, no significant differences were observed in these indicators when compared between the induced and preinduced groups.

Construction, application and validation of selection evaluation model (SEM) for intelligent HVAC control system

Design teams are confronted with the quandary of choosing apposite building control systems to suit the needs of particular intelligent building projects, due to the availability of innumerable ‘intelligent’ building products and a dearth of inclusive evaluation tools. This paper is organised to develop a model for facilitating the selection evaluation for intelligent HVAC control systems for commercial intelligent buildings. To achieve these objectives, systematic research activities have been conducted to first develop, test and refine the general conceptual model using consecutive surveys; then, to convert the developed conceptual framework into a practical model; and, finally, to evaluate the effectiveness of the model by means of expert validation. The results of the surveys are that ‘total energy use’ is perceived as the top selection criterion, followed by the‘system reliability and stability’, ‘operating and maintenance costs’, and ‘control of indoor humidity and temperature’. This research not only presents a systematic and structured approach to evaluate candidate intelligent HVAC control system against the critical selection criteria (CSC), but it also suggests a benchmark for the selection of one control system candidate against another.

Beyond a battery hen model? : a computer laboratory, micropolitics and educational change

This paper investigates what happened in one Australian primary school as part of the establishment, use and development of a computer laboratory over a period of two years. As part of a school renewal project, the computer lab was introduced as an ‘innovative’ way to improve the skills of teachers and children in information and communication technologies (ICT) and to lead to curriculum change. However, the way in which the lab was conceptualised and used worked against achieving these goals. The micropolitics of educational change and an input-output understanding of computers meant that change remained structural rather pedagogical or philosophical.

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

Accident prediction model for railway-highway interfaces

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes. Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Business Process Model Merging : An Approach to Business Process Consolidation

This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

Reliability prediction using the non-parametric explicit hazard model : a case study

Survival probability prediction using covariate-based hazard approach is a known statistical methodology in engineering asset health management. We have previously reported the semi-parametric Explicit Hazard Model (EHM) which incorporates three types of information: population characteristics; condition indicators; and operating environment indicators for hazard prediction. This model assumes the baseline hazard has the form of the Weibull distribution. To avoid this assumption, this paper presents the non-parametric EHM which is a distribution-free covariate-based hazard model. In this paper, an application of the non-parametric EHM is demonstrated via a case study. In this case study, survival probabilities of a set of resistance elements using the non-parametric EHM are compared with the Weibull proportional hazard model and traditional Weibull model. The results show that the non-parametric EHM can effectively predict asset life using the condition indicator, operating environment indicator, and failure history.