Power, concession and cooperation in freight distribution chains subject to distance-based user charges

Freight transport plays an important role within the functions of the road network, yet little is understood about the potential impacts of some travel demand management strategies on freight transport activity. This arises, in part, due to the interdependent nature of decision making within supply chains. To contribute to this shortcoming, this paper offers empirical results from a method designed to estimate attribute-specific measures of relative influence within decision making groups. A choice modelling framework is utilised to consider the relative concession decision makers are willing to make toward the preferences of other group members when attempting to reach group choice equilibrium. The estimated influence measures highlight the relative power each type of decision maker holds with respect to each attribute within the candidate alternatives from which to choose. The alternatives represent supply chain strategies for adjusting to a hypothetical distancebased road user charging system in Sydney, Australia. The measures can be utilised in subsequent transport distribution models to account for the impact each decision maker may have on the decisions made at the group (i.e., supply chain) level in response to a given policy. The results are also useful in gaining a greater normative understanding of the decision-making dynamics within transporter-shipper dyads

Ecosystemic Evolution Feeded by Smart Systems

Information Society is advancing along a route of ecosystemic evolution. ICT and Internet advancements, together with the progression of the systemic approach for enhancement and application of Smart Systems, are grounding such an evolution. The needed approach is therefore expected to evolve by increasingly fitting into the basic requirements of a significant general enhancement of human and social well-being, within all spheres of life (public, private, professional). This implies enhancing and exploiting the net-living virtual space, to make it a virtuous beneficial integration of the real-life space. Meanwhile, contextual evolution of smart cities is aiming at strongly empowering that ecosystemic approach by enhancing and diffusing net-living benefits over our own lived territory, while also incisively targeting a new stable socio-economic local development, according to social, ecological, and economic sustainability requirements. This territorial focus matches with a new glocal vision, which enables a more effective diffusion of benefits in terms of well-being, thus moderating the current global vision primarily fed by a global-scale market development view. Basic technological advancements have thus to be pursued at the system-level. They include system architecting for virtualization of functions, data integration and sharing, flexible basic service composition, and end-service personalization viability, for the operation and interoperation of smart systems, supporting effective net-living advancements in all application fields. Increasing and basically mandatory importance must also be increasingly reserved for human–technical and social–technical factors, as well as to the associated need of empowering the cross-disciplinary approach for related research and innovation. The prospected eco-systemic impact also implies a social pro-active participation, as well as coping with possible negative effects of net-living in terms of social exclusion and isolation, which require incisive actions for a conformal socio-cultural development. In this concern, speed, continuity, and expected long-term duration of innovation processes, pushed by basic technological advancements, make ecosystemic requirements stricter. This evolution requires also a new approach, targeting development of the needed basic and vocational education for net-living, which is to be considered as an engine for the development of the related ‘new living know-how’, as well as of the conformal ‘new making know-how’

Behavioural responses of freight transporters and shippers to road user charging schemes: An empirical assessment

Heavy goods vehicles not only have a non-marginal impact on the performance of the road network in terms of traffic congestion, exposure to risk and accidents, they also provide an essential service in the distribution chain. Both sellers and purchasers of goods rely on an efficient transport system to ensure that goods are available at a time and location that meets the demands of end users. As congestion on the road network grows, especially in urban areas, the calls for ‘solutions’ increase. Although many of the suggestions to resolve delays due to traffic avoid the call for reform of road pricing, there is a growing recognition that user charges have to be more closely aligned to user cost and user benefit. Aiding this call is a technological capability now in place to facilitate a fine tuning of variable users charges that is inter-operable across networks and almost seamless to the customer. The major challenge we face is behavioural – a need to understand more fully the role that specific charging regimes might play in the distribution of freight and who in the supply chain is affected by specific charges in terms of willingness to pay for the gains in network efficiency. This chapter investigates the potential influence of variable user charges, relative to fuel prices (the current main source of charging), in the freight distribution chain. A choice modelling framework is presented that identifies potential responses from the freight distribution sector to variable user charging within the context of the wider spectrum of costs imposed on the sector, as well as the potential benefits (e.g. time savings) from alternative pricing regimes. We highlight the role that agents in the distribution chain play in influencing sensitivity to variable user charges

Multi-agent-based DDoS detection on big data systems

The Hadoop framework has become the most deployed platform for processing Big Data. Despite its advantages, Hadoop s infrastructure is still deployed within the secured network perimeter because the framework lacks adequate inherent security mechanisms against various security threats. However, this approach is not sufficient for providing adequate security layer against attacks such as Distributed Denial of Service. Furthermore, current work to secure Hadoop s infrastructure against DDoS attacks is unable to provide a distributed node-level detection mechanism. This thesis presents a software agent-based framework that allows distributed, real-time intelligent monitoring and detection of DDoS attack at Hadoop s node-level. The agent s cognitive system is ingrained with cumulative sum statistical technique to analyse network utilisation and average server load and detect attacks from these measurements. The framework is a multi-agent architecture with transducer agents that interface with each Hadoop node to provide real-time detection mechanism. Moreover, the agents contextualise their beliefs by training themselves with the contextual information of each node and monitor the activities of the node to differentiate between normal and anomalous behaviours. In the experiments, the framework was exposed to TCP SYN and UDP flooding attacks during a legitimate MapReduce job on the Hadoop testbed. The experimental results were evaluated regarding performance metrics such as false-positive ratio, false-negative ratio and response time to attack. The results show that UDP and TCP SYN flooding attacks can be detected and confirmed on multiple nodes in nineteen seconds with 5.56% false-positive ration, 7.70% false-negative ratio and 91.5% success rate of detection. The results represent an improvement compare to the state-of the-ar

How does rumination impact cognition? A first mechanistic model.

Rumination is a process of uncontrolled, narrowly-foused neg- ative thinking that is often self-referential, and that is a hall- mark of depression. Despite its importance, little is known about its cognitive mechanisms. Rumination can be thought of as a specific, constrained form of mind-wandering. Here, we introduce a cognitive model of rumination that we devel- oped on the basis of our existing model of mind-wandering. The rumination model implements the hypothesis that rumina- tion is caused by maladaptive habits of thought. These habits of thought are modelled by adjusting the number of memory chunks and their associative structure, which changes the se- quence of memories that are retrieved during mind-wandering, such that during rumination the same set of negative memo- ries is retrieved repeatedly. The implementation of habits of thought was guided by empirical data from an experience sam- pling study in healthy and depressed participants. On the ba- sis of this empirically-derived memory structure, our model naturally predicts the declines in cognitive task performance that are typically observed in depressed patients. This study demonstrates how we can use cognitive models to better un- derstand the cognitive mechanisms underlying rumination and depression

An investigation into hazard-centric analysis of complex autonomous systems

This thesis proposes a hypothesis that a conventional, and essentially manual, HAZOP process can be improved with information obtained with model-based dynamic simulation, using a Monte Carlo approach, to update a Bayesian Belief model representing the expected relations between cause and effects – and thereby produce an enhanced HAZOP. The work considers how the expertise of a hazard and operability study team might be augmented with access to behavioural models, simulations and belief inference models. This incorporates models of dynamically complex system behaviour, considering where these might contribute to the expertise of a hazard and operability study team, and how these might bolster trust in the portrayal of system behaviour. With a questionnaire containing behavioural outputs from a representative systems model, responses were collected from a group with relevant domain expertise. From this it is argued that the quality of analysis is dependent upon the experience and expertise of the participants but this might be artificially augmented using probabilistic data derived from a system dynamics model. Consequently, Monte Carlo simulations of an improved exemplar system dynamics model are used to condition a behavioural inference model and also to generate measures of emergence associated with the deviation parameter used in the study. A Bayesian approach towards probability is adopted where particular events and combinations of circumstances are effectively unique or hypothetical, and perhaps irreproducible in practice. Therefore, it is shown that a Bayesian model, representing beliefs expressed in a hazard and operability study, conditioned by the likely occurrence of flaw events causing specific deviant behaviour from evidence observed in the system dynamical behaviour, may combine intuitive estimates based upon experience and expertise, with quantitative statistical information representing plausible evidence of safety constraint violation. A further behavioural measure identifies potential emergent behaviour by way of a Lyapunov Exponent. Together these improvements enhance the awareness of potential hazard cases

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education