Using process models to support design of airport terminals

The complex design process of airport terminal needs to support a wide range of changes in operational facilities for both usual and unusual/emergency events. Process model describes how activities within a process are connected and also states logical information flow of the various activities. The traditional design process overlooks the necessity of information flow from the process model to the actual building design, which needs to be considered as a integral part of building design. The current research introduced a generic method to obtain design related information from process model to incorporate with the design process. Appropriate integration of the process model prior to the design process uncovers the relationship exist between spaces and their relevant functions, which could be missed in the traditional design approach. The current paper examines the available Business Process Model (BPM) and generates modified Business Process Model(mBPM) of check-in facilities of Brisbane International airport. The information adopted from mBPM then transform into possible physical layout utilizing graph theory.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

First international workshop on theory and applications of process visualization

The representation of business process models has been a continuing research topic for many years now. However, many process model representations have not developed beyond minimally interactive 2D icon-based representations of directed graphs and networks, with little or no annotation for information over- lays. With the rise of desktop computers and commodity mobile devices capable of supporting rich interactive 3D environments, we believe that much of the research performed in computer human interaction, virtual reality, games and interactive entertainment has much potential in areas of BPM; to engage, pro- vide insight, and to promote collaboration amongst analysts and stakeholders alike. This initial visualization workshop seeks to initiate the development of a high quality international forum to present and discuss research in this field. Via this workshop, we intend to create a community to unify and nurture the development of process visualization topics as a continuing research area.

Spot the differences in traditional and social entrepreneurial intention : highlighting the role of human and social capital

There is general agreement in the scientific community that entrepreneurship plays a central role in the growth and development of an economy in rapidly changing environments (Acs & Virgill 2010). In particular, when business activities are regarded as a vehicle for sustainable growth at large, that goes beyond mere economic returns of singular entities, encompassing also social problems and heavily relying on collaborative actions, then we more precisely fall into the domain of ‘social entrepreneurship’(Robinson et al. 2009). In the entrepreneurship literature, prior studies demonstrated the role of intentionality as the best predictor of planned behavior (Ajzen 1991), and assumed that the intention to start a business derives from the perception of desirability and feasibility and from a propensity to act upon an opportunity (Fishbein & Ajzen 1975). Recognizing that starting a business is an intentional act (Krueger et al. 2000) and entrepreneurship is a planned behaviour (Katz & Gartner 1988), models of entrepreneurial intentions have substantial implications for intentionality research in entrepreneurship. The purpose of this paper is to explore the emerging practice of social entrepreneurship by comparing the determinants of entrepreneurial intention in general versus those leading to startups with a social mission. Social entrepreneurial intentions clearly merit to be investigated given that the opportunity identification process is an intentional process not only typical of for profit start-ups, and yet there is a lack of research examining opportunity recognition in social entrepreneurship (Haugh 2005). The key argument is that intentionality in both traditional and social entrepreneurs during the decision-making process of new venture creation is influenced by an individual's perceptions toward opportunities (Fishbein & Ajzen 1975). Besides opportunity recognition, at least two other aspects can substantially influence intentionality: human and social capital (Davidsson, 2003). This paper is set to establish if and to what extent the social intentions of potential entrepreneurs, at the cognitive level, are influenced by opportunities recognition, human capital, and social capital. By applying established theoretical constructs, the paper draws comparisons between ‘for-profit’ and ‘social’ intentionality using two samples of students enrolled in Economy and Business Administration at the University G. d’Annunzio in Pescara, Italy. A questionnaire was submitted to 310 potential entrepreneurs to test the robustness of the model. The collected data were used to measure the theoretical constructs of the paper. Reliability of the multi-item scale for each dimension was measured using Cronbach alpha, and for all the dimensions measures of reliability are above 0.70. We empirically tested the model using structural equation modeling with AMOS. The results allow us to empirically contribute to the argument regarding the influence of human and social cognitive capital on social and non-social entrepreneurial intentions. Moreover, we highlight the importance for further researchers to look deeper into the determinants of traditional and social entrepreneurial intention so that governments can one day define better polices and regulations that promote sustainable businesses with a social imprint, rather than inhibit their formation and growth.

Field measurement of wheel-rail impact force at insulated rail joint

When wheels pass over insulated rail joints (IRJs) a vertical impact force is generated. The ability to measure the impact force is valuable as the force signature helps understand the behaviour of the IRJs, in particular their potential for failure. The impact forces are thought to be one of the main factors that cause damage to the IRJ and track components. Study of the deterioration mechanism helps finding new methods to improve the service life of IRJs in track. In this research, the strain-gage-based wheel load detector, for the first time, is employed to measure the wheel–rail contact-impact force at an IRJ in a heavy haul rail line. In this technique, the strain gages are installed within the IRJ assembly without disturbing the structural integrity of IRJ and arranged in a full wheatstone bridge to form a wheel load detector. The instrumented IRJ is first tested and calibrated in the lab and then installed in the field. For comparison purposes, a reference rail section is also instrumented with the same strain gage pattern as the IRJ. In this paper the measurement technique, the process of instrumentation, and tests as well as some typical data obtained from the field and the inferences are presented.

Modeling heat and mass transfer process during convection drying of fruit

Fruit drying is a process of removing moisture to preserve fruits by preventing microbial spoilage. It increases shelf life, reduce weight and volume thus minimize packing, storage, and transportation cost and enable storage of food under ambient environment. But, it is a complex process which involves combination of heat and mass transfer and physical property change and shrinkage of the material. In this background, the aim of this paper to develop a mathematical model to simulate coupled heat and mass transfer during convective drying of fruit. This model can be used predict the temperature and moisture distribution inside the fruits during drying. Two models were developed considering shrinkage dependent and temperature dependent moisture diffusivity and the results were compared. The governing equations of heat and mass transfer are solved and a parametric study has been done with Comsol Multiphysics 4.3. The predicted results were validated with experimental data.

Comparative study of depth-dependent characteristics of equine and human osteochondral tissue from the medial and lateral femoral condyles

Articular cartilage defects are common after joint injuries. When left untreated, the biomechanical protective function of cartilage is gradually lost, making the joint more susceptible to further damage, causing progressive loss of joint function and eventually osteoarthritis (OA). In the process of translating promising tissue-engineering cartilage repair approaches from bench to bedside, pre-clinical animal models including mice, rabbits, goats, and horses, are widely used. The equine species is becoming an increasingly popular model for the in vivo evaluation of regenerative orthopaedic approaches. As there is also an increasing body of evidence suggesting that successful lasting tissue reconstruction requires an implant that mimics natural tissue organization, it is imperative that depth-dependent characteristics of equine osteochondral tissue are known, to assess to what extent they resemble those in humans. Therefore, osteochondral cores (4-8 mm) were obtained from the medial and lateral femoral condyles of equine and human donors. Cores were processed for histology and for biochemical quantification of DNA, glycosaminoglycan (GAG) and collagen content. Equine and human osteochondral tissues possess similar geometrical (thickness) and organizational (GAG, collagen and DNA distribution with depth) features. These comparable trends further underscore the validity of the equine model for the evaluation of regenerative approaches for articular cartilage.

Damage assessment in reinforced concrete flexural members using modal strain energy based method

Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

Empirical analysis of knowledge management activities in construction organisations

Knowledge is a commodity. It is a by-product of learning that involves the creation, sharing, processing and possible use of information in the mind of an individual. Knowledge management (KM) is, therefore, concerned with the effective implementation of such activities within the organisation. It is simply the process of leveraging organisational knowledge to deliver a long-term competitive advantage. This paper presents the results of an empirical research investigation into the interaction between different KM activities within the context of construction contracting organisations. The different KM activities include: responsiveness to the knowledge of business environment, knowledge acquisition, knowledge dissemination, and knowledge application. A questionnaire survey was administered to investigate the opinions of construction professionals regarding the intensity of activities currently implemented by their organisations to facilitate knowledge capturing, sharing and application. A total of 149 responses were then used to statistically examine the inter-relationships between the different KM activities as practised by contracting organisations in Hong Kong. The paper presents and discusses the survey findings and proposes recommendations for improving the effectiveness of current KM practices.

WebAIRS - A case study : how the multidisciplinarity of IS can save lives

This paper presents a case study chronicling the development of WebAIRS, an Australasian national anaesthetic incident reporting database for health care practitioners. WebAIRS is an example of the multidisciplinary nature of the IS discipline, incorporating IS theories, tools and principles in the creation of an IT artefact with significant real world application. This case study introduces the background of the project and the motivations for its conception including the need for critical incident reporting in anaesthesia, the process of its development using IT students and the problems identified following its national release among the anaesthetic community. The paper demonstrates the evolution of contemporary IS research and the IT artefact, and how each can be crucial foundations for hospitals of the future

Anisotropic damage mechanics as a novel approach to improve pre-and post-failure borehole stability analysis

Anisotropic damage distribution and evolution have a profound effect on borehole stress concentrations. Damage evolution is an irreversible process that is not adequately described within classical equilibrium thermodynamics. Therefore, we propose a constitutive model, based on non-equilibrium thermodynamics, that accounts for anisotropic damage distribution, anisotropic damage threshold and anisotropic damage evolution. We implemented this constitutive model numerically, using the finite element method, to calculate stress–strain curves and borehole stresses. The resulting stress–strain curves are distinctively different from linear elastic-brittle and linear elastic-ideal plastic constitutive models and realistically model experimental responses of brittle rocks. We show that the onset of damage evolution leads to an inhomogeneous redistribution of material properties and stresses along the borehole wall. The classical linear elastic-brittle approach to borehole stability analysis systematically overestimates the stress concentrations on the borehole wall, because dissipative strain-softening is underestimated. The proposed damage mechanics approach explicitly models dissipative behaviour and leads to non-conservative mud window estimations. Furthermore, anisotropic rocks with preferential planes of failure, like shales, can be addressed with our model.

Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

The impact of organisational culture in project selection process : case of public infrastructure project in Indonesia

The thesis develops an Organisational Culture (OC) based framework for potentially improving the current practice of the infrastructure project selection process (PSP) in Indonesia, particularly for regional road projects. This framework is developed to address the suggestion emanating from the research that there is a need for strengthening the relevant organisational culture dimensions and making changes to current organisational culture profiles to support the effectiveness of the decision-making process of the current PSP. The findings not only benefit existing knowledge but also provide practical contributions for those decision-makers within the Indonesian regional government that are involved in PSP, i.e. by raising the awareness of the influence and the role of organisational culture.

Second international workshop on theory and applications of process visualization

The representation of business process models has been a continuing research topic for many years now. However, many process model representations have not developed beyond minimally interactive 2D icon-based representations of directed graphs and networks, with little or no annotation for information overlays. In addition, very few of these representations have undergone a thorough analysis or design process with reference to psychological theories on data and process visualization. This dearth of visualization research, we believe, has led to problems with BPM uptake in some organizations, as the representations can be difficult for stakeholders to understand, and thus remains an open research question for the BPM community. In addition, business analysts and process modeling experts themselves need visual representations that are able to assist with key BPM life cycle tasks in the process of generating optimal solutions. With the rise of desktop computers and commodity mobile devices capable of supporting rich interactive 3D environments, we believe that much of the research performed in computer human interaction, virtual reality, games and interactive entertainment have much potential in areas of BPM; to engage, provide insight, and to promote collaboration amongst analysts and stakeholders alike. We believe this is a timely topic, with research emerging in a number of places around the globe, relevant to this workshop. This is the second TAProViz workshop being run at BPM. The intention this year is to consolidate on the results of last year's successful workshop by further developing this important topic, identifying the key research topics of interest to the BPM visualization community.

Identifying important success factors in new venture creation

This paper seeks to uncover the factors that lead to a successful entrepreneurial experience and or venture. Findings of interest in this paper include: • A venture’s initial aspirations are a double edged sword. Ambition may lead to improved performance by striving to reach harder goals. Harder goals are more difficult therefore this may lead to some dissatisfaction, and possibly abandonment of the venture. • Venture legitimacy is important to establish where possible. Firms that formalize their legal form are more successful, as are those set up a shop-front in order to makes sales. • Increased use of technology and higher levels of novelty does not guarantee success early on. Firms of this nature have longer processes, and attempting to create brand new markets is difficult to achieve. At the same time developing your own technology and securing this intellectual property is important for success. • Having goals to work towards and business planning may be useful, but only if the plan is actively revised. Just having a business plan does not matter. Business plans are more useful as a thinking tool than as a blueprint for action. It is the process of thinking through while reviewing the plan that provides the benefit, not following its instruction to the letter.