An investigation of container train service provision and load factors in Great Britain

The continued growth in the volume of international trade poses considerable economic and sustainability challenges, particularly as transport routes become more congested and concern grows about the role of transport movements in accelerating climate change. Rail freight plays a major role in the inland transport of containers passing through the main British container ports, and potentially could play a more significant role in the future. However, there is little detailed understanding of the nature of this particular rail market, especially in terms its current operating efficiency. This paper examines container train service provision to/from the four main ports, based on analysis of a representative survey of more than 500 container trains between February and August 2007. The extent to which the existing capacity is utilised is presented, and scenarios by which the number of containers carried could be increased without requiring additional train service provision are modelled, to identify the theoretical potential for greater rail volumes. Finally, the paper identifies the challenges involved in achieving higher load factors, emphasising the importance both of wider supply chain considerations and government policy decision-making.

Distributed Agent-Based Load Balancer for Cloud Computing

In this paper we present a concept of an agent-based strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. To provide a base for our research we specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. We also present an early version of simulation environment and a prototype of agent-based load balancer implemented in functional language Scala and Akka framework.

Rights, Rationality and Reproduction: Balancing Interests in the Abortion Debate

As medical technology has advanced, so too have our attitudes towards the level of control we can or should expect to have over our procreative capacities. This creates a multidimensional problem for the law and family planning services in terms of access to services – whether to avoid conception or terminate a pregnancy – and the negligent provision of these services. These developments go to the heart of our perception of autonomy. Unsurprisingly, these matters also raise a moral dilemma for the law. Distinctively, discourse in this area is dominated by assertions of subjective moral value; in relation to life, to personal choice and to notions of the archetypal family. Against this, I stress that a model of objective morality can answer these challenging questions and resolve the inherent problems of legal regulation. Therefore, I argue that notions of autonomy must be based on a rational, action-based understanding of what it means to be a ‘moral agent’. I claim that from this we might support a legal standard, based on objective rational morality, which can frame our constitutional norms and our conception of justice in these contentious areas. This paper claims that the current regulation of abortion is outdated and requires radical reform. It proposes a scheme that would shift the choice towards the mother (and the father), remove the unnecessarily broad disability ground and involve doctors having a role of counsel (rather than gatekeeper).

A Meta-Heuristic Load Balancer for Cloud Computing Systems

This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.