Reconnecting theory and practice in a pluralistic organizing context : issues and Aristotelian considerations

The overall purpose of this paper is to contribute to the theory - practice gap debate in organization studies, especially in pluralistic contexts such as project organizing. We briefly outline some of the current debates, i.e. modernist and postmodernist proposals, and the prevalent dichotomous thinking stance assumptions to better move beyond it, anchoring our contribution in the Aristotelian ethical and practical philosophy. We introduce the current state of the debate, part of the broad question of “science that matters”, and the various discourses between practice and academia within social sciences and more specifically organizational studies. We briefly critically summarize some main features of the two main philosophical stances (modernism, postmodernism), before presenting some key aspects, for the purpose of this paper, of the Aristotelian pre-modern practical and ethical philosophy. Then, we build on the foundations above established, discussing propositions to reconnect theory and practice according the Aristotelian ethical and practical philosophy, and some key implications for research notably in the following areas: roles played by practitioners and scholars, emancipatory praxeological style of reasoning, for closing the “phronetic gap” and reconnecting means and ends, facts and values, relation between collective praxis, development of “good practice” (standards), ethics and politics. We conclude highlighting the role of the suggested shift to an Aristotelian emancipatory style of reasoning for reconciling theory and practice.

Agent-based modelling simulation case study : assessment of airport check-in and evacuation process by considering group travel behaviour of air passengers

Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Diophantine equations as a context for technology-enhanced training in conjecturing and proving

Solving indeterminate algebraic equations in integers is a classic topic in the mathematics curricula across grades. At the undergraduate level, the study of solutions of non-linear equations of this kind can be motivated by the use of technology. This article shows how the unity of geometric contextualization and spreadsheet-based amplification of this topic can provide a discovery experience for prospective secondary teachers and information technology students. Such experience can be extended to include a transition from a computationally driven conjecturing to a formal proof based on a number of simple yet useful techniques.

The extended context of career : families negotiating education and career decisions

In families, decisions about parents’ and children’s education and career require an ongoing negotiation to reconcile the goals of all family members. This paper describes a project which investigates these decisions within families experiencing whole family relocation based on one adult’s work. Semi-structured interviews were conducted with professional workers with school-aged children living in six Australian rural and remote communities. The interview sample included four doctors, 10 teachers, four nurses and nine police. This qualitative phase informed the development of an online survey of a larger sample (n¼278) of the same professional groups, which constituted a second quantitative phase of the research. This paper reports on only one aspect of the survey, that is, the participants’ recording of two previous career location moves they had undertaken and the reasons for these. The data emphasise the family project evident in this decision-making process as the respondents deal with a large range of complex individual, family and broader systems’ influences in reconciling their own careers and their children’s educational opportunities.

A particle based model to simulate microscale morphological changes of plant tissues during drying

Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

Compressed sensing using hidden Markov models with application to vision based aircraft tracking

This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering performance is experimentally examined in the context of an important image based aircraft target tracking application. Surprisingly, tracking of dim small-sized targets (as small as 5-10 pixels, with local detectability/SNR as low as − 1.05 dB) was only mildly impacted by compressed sensing down to 15% of original image size.

Using collaborative and activity-based learning for engaging IT students

Active and collaborative learning are becoming essential strategies to attract, engage and retain students. These methods have been adopted within the Science and Engineering Faculty of Queensland University of Technology for use in its Science, Information Technology and Engineering degrees. This paper describes the adoption and application of these techniques in a specific first year unit in a new Bachelor of Information Technology degree which has majors in Computer Science and Information Systems. The paper reports on the design, development and implementation of this foundation subject and discusses how it uses active and collaborative learning to teach design thinking through a series of design challenges, and how it uses critiquing and reflection to ensure that students become more aware of design and team processes.

Online Gaming in Context : the Social and Cultural Significance of Online Games

There is little question of the social, cultural and economic importance of video games in the world today, with gaming now rivalling the movie and music sectors as a major leisure industry and pastime. The significance of video games within our everyday lives has certainly been increased and shaped by new technologies and gaming patterns, including the rise of home-based games consoles, advances in mobile telephone technology, the rise in more 'sociable' forms of gaming, and of course the advent of the Internet. This book explores the opportunities, challenges and patterns of gameplay and sociality afforded by the Internet and online gaming. Bringing together a series of original essays from both leading and emerging academics in the field of game studies, many of which employ new empirical work and innovative theoretical approaches to gaming, this book considers key issues crucial to our understanding of online gaming and associated social relations, including: patterns of play, legal and copyright issues, player production, identity construction, gamer communities, communication, patterns of social exclusion and inclusion around religion, gender and disability, and future directions in online gaming.

Career choice and the experience of project-based work

The nature and context of project-based work combines with sector characteristics to present both barriers and benefits that influence career choices and experiences. Using social cognitive career theory (SCCT) as a lens, this paper contributes to understanding of the relative involvement of women and men in project roles by exploring the ways they perceive the experience and opportunities of project based work. With such diverse outcomes for men and women on almost all measures it is obvious projects can be a nightmare of different treatment and different experiences for men and women. The question of how organisations can ensure equal opportunity of the benefits and the burdens of work in projects continues to grow.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Applying the Haddon Matrix in the context of work-related road safety

The Haddon Matrix was developed in the 1960s road safety arena, and has since been used in many public health settings. The literature and two specific case studies are reviewed to describe the background to the Haddon Matrix, identify how it has been critiqued and developed over time and practical applications in the work-related road safety context. Haddon’s original focus on the road, vehicle and driver has been extended and applied to include organisational safety culture, journey management and wider issues in society that affect occupational drivers and the communities in which they work. The paper shows that the Haddon Matrix has been applied in many projects and contexts. Practical work-related road safety applications include providing a comprehensive systems-based safety management framework to inform strategy. It has also been used to structure the review or gap analysis of current programs and processes, identify and develop prevention measures and as a tool for effective post-event investigations.

Ranking based clustering for social event detection

The problem of clustering a large document collection is not only challenged by the number of documents and the number of dimensions, but it is also affected by the number and sizes of the clusters. Traditional clustering methods fail to scale when they need to generate a large number of clusters. Furthermore, when the clusters size in the solution is heterogeneous, i.e. some of the clusters are large in size, the similarity measures tend to degrade. A ranking based clustering method is proposed to deal with these issues in the context of the Social Event Detection task. Ranking scores are used to select a small number of most relevant clusters in order to compare and place a document. Additionally,instead of conventional cluster centroids, cluster patches are proposed to represent clusters, that are hubs-like set of documents. Text, temporal, spatial and visual content information collected from the social event images is utilized in calculating similarity. Results show that these strategies allow us to have a balance between performance and accuracy of the clustering solution gained by the clustering method.

Short-data recursive HMM parameter estimation for rapid vision-based aircraft heading estimation

Rapid recursive estimation of hidden Markov Model (HMM) parameters is important in applications that place an emphasis on the early availability of reasonable estimates (e.g. for change detection) rather than the provision of longer-term asymptotic properties (such as convergence, convergence rate, and consistency). In the context of vision- based aircraft (image-plane) heading estimation, this paper suggests and evaluates the short-data estimation properties of 3 recursive HMM parameter estimation techniques (a recursive maximum likelihood estimator, an online EM HMM estimator, and a relative entropy based estimator). On both simulated and real data, our studies illustrate the feasibility of rapid recursive heading estimation, but also demonstrate the need for careful step-size design of HMM recursive estimation techniques when these techniques are intended for use in applications where short-data behaviour is paramount.

A BIM-based collaborative design platform for variegated specialty design

With the increase in complexity of engineering projects and design quality in the construction industry, the traditional two-dimensional "Information Island" approach to design is becoming less able to meet current design needs due to its lack of coordination and information sharing. Collaborative design using a Build Information Modeling (BIM) technology platform promises to provide an effective means of designing and communicating through networking and real-time data sharing. This paper first analyzes the shortcomings of the two-dimensional design process and the potential application of collaborative design. By combining the attributes of BIM, a preliminary BIM-based building design collaborative platform is developed to improve the design approach and support a more collaborative design process. A real-life case is presented to demonstrate the feasibility and validity of the platform and its use in practice. From this, it is shown that BIM has the potential to realize effective information sharing and reduce errors, thereby improving design quality. The BIM-based building design collaborative platform presented is expected to provide the support needed for the extensive application of BIM in collaborative design and promote a new attitude to project management.