Genesis and role of standards : theoretical foundations and socio-economical model for the construction and use of standards

A key issue for the economic development and for performance of organizations is the existence of standards. As their definitions and control are source of power, it seems to be important to understand the concept and to wonder about the representations authorized by the concept which give their direction and their legitimacy. The difficulties of classical microeconomics of establishing a theory of standardisation compatible with its fundamental axiomatic are underlined. We propose to reconsider the problem by carrying out the opposite way: to question the theoretical base, by reformulating assumptions on the autonomy of the choice of the actors. The theory of conventions will offer us both a theoretical framework and tools, enabling us to understand the systemic dimension and dynamic structure of standards seen as special case of conventions. This work aims thus to provide a sound basis and promote a better consciousness in the development of global project management standards, aiming also to underline that social construction is not a matter of copyright but a matter of open minds, collective cognitive process and freedom for the common wealth.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Rethinking prefabricated construction management using the VP-based IKEA model in Hong Kong

Prefabricated construction is regarded by many as an effective and efficient approach to improving construction processes and productivity, ensuring construction quality and reducing time and cost in the construction industry. However, many problems occur with this approach in practice, including higher risk levels and cost or time overruns. In order to solve such problems, it is proposed that the IKEA model of the manufacturing industry and VP technology are introduced into a prefabricated construction process. The concept of the IKEA model is identified in detail and VP technology is briefly introduced. In conjunction with VP technology, the applications of the IKEA model are presented in detail, i.e. design optimization, production optimization and installation optimization. Furthermore, through a case study of a prefabricated hotel project in Hong Kong, it is shown that the VP-based IKEA model can improve the efficiency and safety of prefabricated construction as well as reducing cost and time.

A review of models and model usage scenarios for an airport complex system

Airports represent the epitome of complex systems with multiple stakeholders, multiple jurisdictions and complex interactions between many actors. The large number of existing models that capture different aspects of the airport are a testament to this. However, these existing models do not consider in a systematic sense modelling requirements nor how stakeholders such as airport operators or airlines would make use of these models. This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult. This paper develops from the Concept of Operations (CONOPS) framework a methodology to help structure the review and development of modelling capabilities and usage scenarios. The method is applied to the review of existing airport terminal passenger models. It is found that existing models can be broadly categorised according to four usage scenarios: capacity planning, operational planning and design, security policy and planning, and airport performance review. The models, the performance metrics that they evaluate and their usage scenarios are discussed. It is found that capacity and operational planning models predominantly focus on performance metrics such as waiting time, service time and congestion whereas performance review models attempt to link those to passenger satisfaction outcomes. Security policy models on the other hand focus on probabilistic risk assessment. However, there is an emerging focus on the need to be able to capture trade-offs between multiple criteria such as security and processing time. Based on the CONOPS framework and literature findings, guidance is provided for the development of future airport terminal models.

A context sensitive model for querying linked scientific data

This thesis provides a query model suitable for context sensitive access to a wide range of distributed linked datasets which are available to scientists using the Internet. The model is designed based on scientific research standards which require scientists to provide replicable methods in their publications. Although there are query models available that provide limited replicability, they do not contextualise the process whereby different scientists select dataset locations based on their trust and physical location. In different contexts, scientists need to perform different data cleaning actions, independent of the overall query, and the model was designed to accommodate this function. The query model was implemented as a prototype web application and its features were verified through its use as the engine behind a major scientific data access site, Bio2RDF.org. The prototype showed that it was possible to have context sensitive behaviour for each of the three mirrors of Bio2RDF.org using a single set of configuration settings. The prototype provided executable query provenance that could be attached to scientific publications to fulfil replicability requirements. The model was designed to make it simple to independently interpret and execute the query provenance documents using context specific profiles, without modifying the original provenance documents. Experiments using the prototype as the data access tool in workflow management systems confirmed that the design of the model made it possible to replicate results in different contexts with minimal additions, and no deletions, to query provenance documents.

A continuum model of the growth of engineered epidermal skin substitutes

We present a porous medium model of the growth and deterioration of the viable sublayers of an epidermal skin substitute. It consists of five species: cells, intracellular and extracellular calcium, tight junctions, and a hypothesised signal chemical emanating from the stratum corneum. The model is solved numerically in Matlab using a finite difference scheme. Steady state calcium distributions are predicted that agree well with the experimental data. Our model also demonstrates epidermal skin substitute deterioration if the calcium diffusion coefficient is reduced compared to reported values in the literature.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

What explains the association between socioeconomic status and depression among Vietnamese adults?

Background Depression is a major public health problem worldwide and is currently ranked second to heart disease for years lost due to disability. For many decades, international research has found that depressive symptoms occur more frequently among low socioeconomic (SES) individuals than their more-advantaged peers. However, the reasons as to why those of low socioeconomic groups suffer more depressive symptoms are not well understood. Studies investigating the prevalence of depression and its association with SES emanate largely from developed countries, with little research among developing countries. In particular, there is a serious dearth of research on depression and no investigation of its association with SES in Vietnam. The aims of the research presented in this Thesis are to: estimate the prevalence of depressive symptoms among Vietnamese adults, examine the nature and extent of the association between SES and depression and to elucidate causal pathways linking SES to depressive symptoms Methods The research was conducted between September 2008 and November 2009 in Hue city in central Vietnam and used a combination of qualitative (in-depth interviews) and quantitative (survey) data collection methods. The qualitative study contributed to the development of the theoretical model and to the refinement of culturally-appropriate data collection instruments for the quantitative study. The main survey comprised a cross-sectional population–based survey with randomised cluster sampling. A sample of 1976 respondents aged between 25-55 years from ten randomly-selected residential zones (quarters) of Hue city completed the questionnaire (response rate 95.5%). Measures SES was classified using three indicators: education, occupation and income. The Center for Epidemiologic Studies-Depression (CES-D) scale was used to measure depressive symptoms (range0-51, mean=11.0, SD=8.5). Three cut-off points for the CES-D scores were applied: ‘at risk for clinical depression’ (16 or above), ‘depressive symptoms’ (above 21) and ‘depression’ (above 25). Six psychosocial indicators: life time trauma, chronic stress, recent life events, social support, self esteem, and mastery were hypothesized to mediate the association between SES and depressive symptoms. Analyses The prevalence of depressive symptoms were analysed using bivariate analyses. The multivariable analytic phase comprised of ordinary least squares regression, in accordance with Baron and Kenny’s three-step framework for mediation modeling. All analyses were adjusted for a range of confounders, including age, marital status, smoking, drinking and chronic diseases and the mediation models were stratified by gender. Results Among these Vietnamese adults, 24.3% were at or above the cut-off for being ‘at risk for clinical depression’, 11.9% were classified as having depressive symptoms and 6.8% were categorised as having depression. SES was inversely related to depressive symptoms: the least educated those with low occupational status or with the lowest incomes reported more depressive symptoms. Socioeconomicallydisadvantaged individuals were more likely to report experiencing stress (life time trauma, chronic stress or recent life events), perceived less social support and reported fewer personal resources (self esteem and mastery) than their moreadvantaged counterparts. These psychosocial resources were all significantly associated with depressive symptoms independent of SES. Each psychosocial factor showed a significant mediating effect on the association between SES and depressive symptoms. This was found for all measures of SES, and for males and females. In particular, personal resources (mastery, self esteem) and chronic stress accounted for a substantial proportion of the variation in depressive symptoms between socioeconomic groups. Social support and recent life events contributed modestly to socioeconomic differences in depressive symptoms, whereas lifetime trauma contributed the least to these inequalities. Conclusion This is the first known study in Vietnam or any developing country to systematically examine the extent to which psychosocial factors mediate the relationship between SES and depression. The study contributes new evidence regarding the burden of depression in Vietnam. The findings have practical relevance for advocacy, for mental health promotion and health-care services, and point to the need for programs that focus on building a sense of personal mastery and self esteem. More broadly, the work presented in this Thesis contributes to the international scientific literature on the social determinants of depression.

A Context Space Model for Detecting Anomalous Behaviour in Video Surveillance

Having a good automatic anomalous human behaviour detection is one of the goals of smart surveillance systems’ domain of research. The automatic detection addresses several human factor issues underlying the existing surveillance systems. To create such a detection system, contextual information needs to be considered. This is because context is required in order to correctly understand human behaviour. Unfortunately, the use of contextual information is still limited in the automatic anomalous human behaviour detection approaches. This paper proposes a context space model which has two benefits: (a) It provides guidelines for the system designers to select information which can be used to describe context; (b)It enables a system to distinguish between different contexts. A comparative analysis is conducted between a context-based system which employs the proposed context space model and a system which is implemented based on one of the existing approaches. The comparison is applied on a scenario constructed using video clips from CAVIAR dataset. The results show that the context-based system outperforms the other system. This is because the context space model allows the system to considering knowledge learned from the relevant context only.

Social Media and Tacit Knowledge Sharing: Developing a Conceptual Model

With the advent of social web initiatives, some argued that these new emerging tools might be useful in tacit knowledge sharing through providing interactive and collaborative technologies. However, there is still a poverty of literature to understand how and what might be the contributions of social media in facilitating tacit knowledge sharing. Therefore, this paper is intended to theoretically investigate and map social media concepts and characteristics with tacit knowledge creation and sharing requirements. By conducting a systematic literature review, five major requirements found that need to be present in an environment that involves tacit knowledge sharing. These requirements have been analyzed against social media concepts and characteristics to see how they map together. The results showed that social media have abilities to comply some of the main requirements of tacit knowledge sharing. The relationships have been illustrated in a conceptual framework, suggesting further empirical studies to acknowledge findings of this study.

The traditional rationale of the arm’s length approach to transfer pricing : should the separate accounting model be maintained for modern multinational entities?

This article examines the current transfer pricing regime to consider whether it is a sound model to be applied to modern multinational entities. The arm's length price methodology is examined to enable a discussion of the arguments in favour of such a regime. The article then refutes these arguments concluding that, contrary to the very reason multinational entities exist, applying arm's length rules involves a legal fiction of imagining transactions between unrelated parties. Multinational entities exist to operate in a way that independent entities would not, which the arm's length rules fail to take into account. As such, there is clearly an air of artificiality in applying the arm's length standard. To demonstrate this artificiality with respect to modern multinational entities, multinational banks are used as an example. The article concluded that the separate entity paradigm adopted by the traditional transfer pricing regime is incongruous with the economic theory of modern multinational enterprises.

Loss and grief at the heart of text messages [REVIEW]

WHAT if you lost someone you loved? What if you had to let go for the sake of your own sanity? Lachlan Philpott's Colder and Dennis Kelly's Orphans, playing as part of La Boite's and Queensland Theatre Company's independents programs, are emotionally and textually dense theatrical works...

A behavioural car-following model that captures traffic oscillations

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

A study on the encryption model for numerical data

The encryption method is a well established technology for protecting sensitive data. However, once encrypted, the data can no longer be easily queried. The performance of the database depends on how to encrypt the sensitive data. In this paper we review the conventional encryption method which can be partially queried and propose the encryption method for numerical data which can be effectively queried. The proposed system includes the design of the service scenario, and metadata.