Proportionality in Age Discrimination Cases - a Model Suitable for Socially Embedded Rights

This chapter discusses the use of proportionality in age discrimination cases before the Court of Justice of the European Union. It argues that the Court does not use this concept systematically - indeed it exposes some contradiction that make the case law seem arbitrary - and proposes a more fruitful use of the principle, which is in line with a modern conception of human rights. The chapter argues that the principle of proportionality stems from the time when human rights served the recently liberated burgeois elite in guarding their rights to property and liberty against the state. Today, states not only respect human rights (which is fully sufficient for this elite, who can rely on their inherited wealth to fend for themselves). They also protect and promote human rights, and these activities are a precondition for human rights to be practically relevant for the whole population. This also means that state activity, which is experienced as a limitation of rights to property and liberty by some, may constitute a measure to promote and protect human rights of others. In employment law - the only field where the EU ban on age discrimination is applied - this is a typical situation. If such a situation occurs, the principle of proportionality must be applied in a bifurcated way.It is not sufficient that the limitation of property rights is proportionate for the achievement of a public policy aim. If the aim of public policy is to enable the effective use of human rights, the limitation of the state action must be proportionate to the protection and promotion of those human rights. It is argued that the principle of proportionality is superior to less structures balancing acts (e.g. the Wednesbury principle), if it is applied both ways. Going over to the field of age discrimination, the chapter identifies a number of potentially colliding aims pursued in this field. Banning age discrimination may relate to genuine aims of anti-discrimination law if bias against older or very young workers is addressed. However, the EU ban of discrimination against all ages also serves to restructure employment law and policy to the age of flexibilisation, replacing the synchronisation principle that has been predominant for the welfare states of the 20th century. The former aim is related to human rights protection, while the latter aim is not (at least not always). This has consequences for applying the proportionality test. The chapter proposes different ways to argue the most difficult age discrimination cases, where anti-discrimination rationales and flexibilisation rationales clash

Insights into molecular and cellular events involved in normal and pathological vertebral development and fusion using zebrafish as model organism

The vertebral column and its units, the vertebrae, are fundamental features, characteristic of all vertebrates. Developmental segregation of the vertebral bodies as articulated units is an intrinsic requirement to guarantee the proper function of the spine. Whenever these units become fused either during development or postsegmentation, movement is affected in a more or less severe manner, depending on the number of vertebrae affected. Nevertheless, fusion may occur as part of regular development and as a physiological requirement, like in the tetrapod sacrum or in fish posterior vertebrae forming the urostyle. In order to meet the main objective of this PhD project, which aimed to better understand the molecular and cellular events underlying vertebral fusion under physiological and pathological conditions, a detailed characterization of the vertebral fusion occurring in zebrafish caudal fin region was conducted. This showed that fusion in the caudal fin region comprised 5 vertebral bodies, from which, only fusion between [PU1++U1] and ural2 [U2+] was still traceable during development. This involved bone deposition around the notochord sheath while fusion within the remaining vertebral bodies occur at the level of the notochord sheath, as during the early establishment of the vertebral bodies. A comparison approach between the caudal fin vertebrae and the remaining vertebral column showed conserved features such as the presence of mineralization related proteins as Osteocalcin were identified throughout the vertebral column, independently on the mineralization patterns. This unexpected presence of Osteocalcin in notochord sheath, here identified as Oc1, suggested that this gene, opposing to Oc2, generally associated with bone formation and mature osteoblast activity, is potentially associated with early mineralization events including chordacentrum formation. Nevertheless, major differences between caudal fin region and anterior vertebral bodies considering arch histology and mineralization patterns, led us to use RA as an inductive factor for vertebral fusion, allowing a direct comparison of equivalent structures under normal and fusion events. This fusion phenotype was associated with notochord sheath ectopic mineralization instead of ectopic perichordal bone formation related with increased osteoblast activity, as suggested in previous reports. Additionally, alterations in ECM content, cell adhesion and blood coagulation were discussed as potentially related with the fusion phenotype. Finally, Matrix gla protein, upregulated upon RA treatment and shown to be associated with chordacentrum mineralization sites in regular development, was further described considering its potential function in vertebral formation and pathological fusion. Therefore with this work we propose zebrafish caudal fin vertebral fusion as a potential model to study both congenital and postsegmentation fusion and we present candidate factors and genes that may be further explored in order to clarify whether we can prevent vertebral fusion.

Virtual Model Control of a Hexapod Walking Robot

Since robots are typically designed with an individual actuator at each joint, the control of these systems is often difficult and non-intuitive. This thesis explains a more intuitive control scheme called Virtual Model Control. This thesis also demonstrates the simplicity and ease of this control method by using it to control a simulated walking hexapod. Virtual Model Control uses imagined mechanical components to create virtual forces, which are applied through the joint torques of real actuators. This method produces a straightforward means of controlling joint torques to produce a desired robot behavior. Due to the intuitive nature of this control scheme, the design of a virtual model controller is similar to the design of a controller with basic mechanical components. The ease of this control scheme facilitates the use of a high level control system which can be used above the low level virtual model controllers to modulate the parameters of the imaginary mechanical components. In order to apply Virtual Model Control to parallel mechanisms, a solution to the force distribution problem is required. This thesis uses an extension of Gardner`s Partitioned Force Control method which allows for the specification of constrained degrees of freedom. This virtual model control technique was applied to a simulated hexapod robot. Although the hexapod is a highly non-linear, parallel mechanism, the virtual models allowed text-book control solutions to be used while the robot was walking. Using a simple linear control law, the robot walked while simultaneously balancing a pendulum and tracking an object.

Predicting worsted spinning performance with an artificial neural network model

For a given fiber spun to pre-determined yarn specifications, the spinning performance of the yarn usually varies from mill to mill. For this reason, it is necessary to develop an empirical model that can encompass all known processing variables that exist in different spinning mills, and then generalize this information and be able to accurately predict yarn quality for an individual mill. This paper reports a method for predicting worsted spinning performance with an artificial neural network (ANN) trained with backpropagation. The applicability of artificial neural networks for predicting spinning performance is first evaluated against a well established prediction and benchmarking tool (Sirolan YarnspecTM). The ANN is then subsequently trained with commercial mill data to assess the feasibility of the method as a mill-specific performance prediction tool. Incorporating mill-specific data results in an improved fit to the commercial mill data set, suggesting that the proposed method has the ability to predict the spinning performance of a specific mill accurately.

A conceptual model for graphical authentication

Reasons for the adoption of smart cards and biometric authentication mechanisms have been discussed in the past, yet many organisations are still resorting to traditional methods of authentication. Passwords possess several encumbrances not the least of which includes the difficulty some users have in remembering them. Often users inadvertently write difficult passwords down near the workstation, which negates any security password authentication, may provide and opens the floodgates to identity theft. In the current mainstream authentication paradigm, system administrators must ensure all users are educated on the need for a password policy, and implement it strictly. This paper discusses a conceptual framework for an alternative authentication paradigm. The framework attempts to reduce complexity for the user as well as increase security at the network and application levels.

A model of student satisfaction : international postgraduate students from Asia

The internationalisation of higher education remains one of the major challenges faced by universities with the increasing mobility and rising expectations of a highly diversified student community worldwide. With the competitiveness of the industry, universities will need to focus on factors influencing student satisfaction to improve service quality where required. This paper draws on the theory of cognitive dissonance dealining with disconformation of expectations that results in customer satisfaction and using structural equation modelling, investigates factors that influence satisfaction of international postgraduate students from Asian countries studying in Australia and concludes with strategic implications for universities.

Risk allocation in public-private partnership projects : an innovative model with an intelligent approach

Both the increasing private participation in public projects and the critical importance of appropriate risk allocation to the success of Public-private partnership (PPP) projects justify specific research on how to establish effective risk allocation strategies in PPP projects. Partner’s risk management capability is currently the main concern to risk allocation in PPP projects. Following the transaction cost economics, it is argued that factors such as partner’s commitment and risk management structure should be considered simultaneously in order to develop effective risk allocation strategies. Based on the holistic capability-commitment governance-driven view, this paper proposed a model for generating an optimal risk allocation strategy in PPP projects. The model is demonstrated and described. An artificial intelligent technique integrated with fuzzy logic for model testing and validation is then introduced and justified. The innovative model is expected to provide a logical and complete understanding of the risk allocation strategy selection process, and to provide stakeholders with a richer framework than previously existing ones to guide their decision-making on risk allocation strategies.

Longitudinal evaluation of a risk-factor model for adolescent suicidality

This research developed two best-fitting structural equation models of risk factors for adolescent depression and suicidality: a core model, which included parenting factors, gender, depression, and suicidality, and an extended model, which also encompassed personality traits (Introversion and Impulsivity) and mood factors (Anxiety and Anger). Further, this research investigated the consistency of model fit across time (Le., 1 month & 12 months) and samples, and explored the effectiveness of the ReachOut! Internet site as a psychoeducational prevention strategy for adolescent depression and suicidality. Gender, age, and location differences were also explored. Participants were 185 Year-9 students and 93 Year-10 students aged 14 - 16 years, from seven secondary schools in regional and rural Victoria. Students were given a survey which included the Parental Bonding Instrument (Parker, Tupling, & Brown, 1979), the Millon Adolescent Personality Inventory (Millon, Green, & Meagher, 1982), the Profile of Mood States Inventory (McNair & Lorr, 1964), items on suicidal behaviour including some questions from the Revised Adolescent Suicide Questionnaire (Pearce & Martin, 1994), and questions on loss and general demographics. Results supported an indirect model of risk factors, with family factors directly influencing personality factors, which in turn influenced mood factors, including depression, which then influenced suicidality. At the theoretical level, results supported Attachment Theory (Bowlby, 1969), demonstrating that perceived parenting styles that are warm and not overly controlling are more conducive to an adolescent's emotional well-being than are parenting styles that are cold and controlling. Further, results supported Millon's theory of personality (1981), demonstrating that parenting style influences a child's personality. Short-term intervention effects from the internet site were a decrease in Introversion for the full sample, and decreased Inhibition and Suicidality for a high-risk subgroup. Long-term age effects were decreased Inhibition and increased Anxiety for the fall sample. There was also a probable intervention effect for Depression for the high-risk subgroup. No location differences for the risk factors were found between regional and rural areas.

A hypothesised model of disordered eating in overweight women

This thesis found that predicted risk factors for disordered eating were similar for overweight and non-overweight women. However, overweight women reported more stigmatisation and body shame, had a higher risk for developing an eating disorder, and were twice as likely to be diagnosed with a subclinical/clinical eating disorder than non-overweight women. The portfolio presents four case studies demonstrating the considerations and challenges of psychologically assessing and treating individuals with chronic health conditions.

Hybrid neural-evolutionary model for electricity price forecasting

Evolving artificial neural networks has attracted much attention among researchers recently, especially in the fields where plenty of data exist but explanatory theories and models are lacking or based upon too many simplifying assumptions. Financial time series forecasting is one of them. A hybrid model is used to forecast the hourly electricity price from the California Power Exchange. A collaborative approach is adopted to combine ANN and evolutionary algorithm. The main contributions of this thesis include: Investigated the effect of changing values of several important parameters on the performance of the model, and selected the best combination of these parameters; good forecasting results have been obtained with the implemented hybrid model when the best combination of parameters is used. The lowest MAPE through a single run is 5. 28134%. And the lowest averaged MAPE over 10 runs is 6.088%, over 30 runs is 6.786%; through the investigation of the parameter period, it is found that by including future values of the homogenous moments of the instant being forecasted into the input vector, forecasting accuracy is greatly enhanced. A comparison of results with other works reported in the literature shows that the proposed model gives superior performance on the same data set.

Hybrid neural network—finite element river flow model

Results obtained from a hybrid neural network—finite element model are reported in this paper. The hybrid model incorporates artificial neural network (ANN) nodes into a numerical scheme, which solves the two-dimensional shallow water equations using finite elements (FE). First, numerical computations are carried out on the entire numerical model, using a larger mesh. The results from this computation are then used to train several preselected ANN nodes. The ANN nodes model the response for a part of the entire numerical model by transferring the system reaction to the location where both models are connected in real time. This allows a smaller mesh to be used in the hybrid ANN-FE model, resulting in savings in computation time. The hybrid model was developed for a river application, using the computational nodes located at the open boundaries to be the ANN nodes for the ANN-FE hybrid model. Real-time coupling between the ANN and FE models was achieved, and a reduction is CPU time of more than 25% was obtained.

Teaching a digital performing agent: artificial neural network and hidden Markov Model for recognising and performing dance movement

For a Digital Performing Agent to be able to perform live with a human dancer, it would be useful for the agent to be able to contextualize the movement the dancer is performing and to have a suitable movement vocabulary with which to contribute to the performance. In this paper we will discuss our research into the use of Artificial Neural Networks (ANN) as a means of allowing a software agent to learn a shared vocabulary of movement from a dancer. The agent is able to use the learnt movements to form an internal representation of what the dancer is performing, allowing it to follow the dancer, generate movement sequences based on the dancer's current movement and dance independently of the dancer using a shared movement vocabulary. By combining the ANN with a Hidden Markov Model (HMM) the agent is able to recognize short full body movement phrases and respond when the dancer performs these phrases. We consider the relationship between the dancer and agent as a means of supporting the agent's learning and performance, rather than developing the agent's capability in a self-contained fashion.