Social and demographic factors of young fathers in the UK and USA

Research on disadvantaged young fathers has been minimally addressed in the literature, particularly in the UK. In both countries teenage pregnancy rates are high and costly in terms of social policy and community provision. This paper explores 2 studies involving 24 young men with an average age of 17 on the transition to young fatherhood; one study was conducted in the UK with white young men and the other in the USA with black young men. The findings from both studies indicated common themes from their stories, particularly with regard to the high levels of disadvantage and social exclusion they had been exposed to in their demographic environments and the anti-social behaviour they described engaging in, prior to the birth of their child/ren. Specifically, a significant proportion of the young men described how they had been immersed in drug and gun crimes and how this shaped their lives and neighbourhoods. Becoming fathers is presented by both sets of young men as rescuing them from this criminal lifestyle.

Representing temporal relationships between events and their effects

Temporal relationships between events and their effects are complex. As the effects of a given event, a proposition may change its truth value immediately after the occurrence of the event and remain true until some other events occur, while another proposition may only become true/false from some time after the causal event has occurred. Expressing delayed effects of events has been a problematic question in most existing theories of action and change. This paper presents a new formalism for representing general temporal causal relationships between events and their effects. It allows expressions of both immediate and delayed effects of events, and supports common-sense assertions such as "effects cannot precede their causes".

Load sharing in cluster service provision

The factors that are driving the development and use of grids and grid computing, such as size, dynamic features, distribution and heterogeneity, are also pushing to the forefront service quality issues. These include performance, reliability and security. Although grid middleware can address some of these issues on a wider scale, it has also become imperative to ensure adequate service provision at local level. Load sharing in clusters can contribute to the provision of a high quality service, by exploiting both static and dynamic information. This paper is concerned with the presentation of a load sharing scheme, that can satisfy grid computing requirements. It follows a proactive, non preemptive and distributed approach. Load information is gathered continuously before it is needed, and a task is allocated to the most appropriate node for execution. Performance and reliability are enhanced by the decentralised nature of the scheme and the symmetric roles of the nodes. In addition, the scheme exhibits transparency characteristics that facilitate integration with the grid.

A design pattern approach to bitemporal data modeling

The importance of patterns in constructing complex systems has long been recognised in other disciplines. In software engineering, for example, well-crafted object-oriented architectures contain several design patterns. Focusing on mechanisms of constructing software during system development can yield an architecture that is simpler, clearer and more understandable than if design patterns were ignored or not properly applied. In this paper, we propose a model that uses object-oriented design patterns to develop a core bitemporal conceptual model. We define three core design patterns that form a core bitemporal conceptual model of a typical bitemporal object. Our framework is known as the Bitemporal Object, State and Event Modelling Approach (BOSEMA) and the resulting core model is known as a Bitemporal Object, State and Event (BOSE) model. Using this approach, we demonstrate that we can enrich data modelling by using well known design patterns which can help designers to build complex models of bitemporal databases.

Emergence: a paradigm for robust and scalable distributed applications

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

Self-adaptability and man-in-the-loop: a dilemma in autonomic computing systems

This paper addresses some controversial issues relating to two main questions. Firstly, we discuss 'man-in-the loop' issues in SAACS. Some people advocate this must always be so that man's decisions can override autonomic components. In this case, the system has two subsystems - man and machine. Can we, however, have a fully autonomic machine - with no man in sight; even for short periods of time? What kinds of systems require man to always be in the loop? What is the optimum balance in self-to-human control? How do we determine the optimum? How far can we go in describing self-behaviour? How does a SAACS system handle unexpected behaviour? Secondly, what are the challenges/obstacles in testing SAACS in the context of self/human dilemma? Are there any lesson to be learned from other programmes e.g. Star-wars, aviation and space explorations? What role human factors and behavioural models play whilst in interacting with SAACS?.

Natural inspiration for self-adaptive systems

The emergent behaviour of autonomic systems, together with the scale of their deployment, impedes prediction of the full range of configuration and failure scenarios; thus it is not possible to devise management and recovery strategies to cover all possible outcomes. One solution to this problem is to embed self-managing and self-healing abilities into such applications. Traditional design approaches favour determinism, even when unnecessary. This can lead to conflicts between the non-functional requirements. Natural systems such as ant colonies have evolved cooperative, finely tuned emergent behaviours which allow the colonies to function at very large scale and to be very robust, although non-deterministic. Simple pheromone-exchange communication systems are highly efficient and are a major contribution to their success. This paper proposes that we look to natural systems for inspiration when designing architecture and communications strategies, and presents an election algorithm which encapsulates non-deterministic behaviour to achieve high scalability, robustness and stability.

Requirements and design of an integrated European environmental information communication system, (IEEICS)

The needs for various forms of information systems relating to the European environment and ecosystem are reviewed, and limitations indicated. Existing information systems are reviewed and compared in terms of aims and functionalities. We consider TWO technical challenges involved in attempting to develop an IEEICS. First, there is the challenge of developing an Internet-based communication system which allows fluent access to information stored in a range of distributed databases. Some of the currently available solutions are considered, i.e. Web service federations. The second main challenge arises from the fact that there is general intra-national heterogeneity in the definitions adopted, and the measurement systems used throughout the nations of Europe. Integrated strategies are needed.

Models and tools for an integrated European environmental management and decision support system, (IEEMDSS)

This work proceeds from the assumption that a European environmental information and communication system (EEICS) is already established. In the context of primary users (land-use planners, conservationists, and environmental researchers) we ask what use may be made of the EEICS for building models and tools which is of use in building decision support systems for the land-use planner. The complex task facing the next generation of environmental and forest modellers is described, and a range of relevant modelling approaches are reviewed. These include visualization and GIS; statistical tabulation and database SQL, MDA and OLAP methods. The major problem of noncomparability of the definitions and measures of forest area and timber volume is introduced and the possibility of a model-based solution is considered. The possibility of using an ambitious and challenging biogeochemical modelling approach to understanding and managing European forests sustainably is discussed. It is emphasised that all modern methodological disciplines must be brought to bear, and a heuristic hybrid modelling approach should be used so as to ensure that the benefits of practical empirical modelling approaches are utilised in addition to the scientifically well-founded and holistic ecosystem and environmental modelling. The data and information system required is likely to end up as a grid-based-framework because of the heavy use of computationally intensive model-based facilities.

Self-optimising data farming for web applications

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.

On the persistence of computer dreams: an application framework for robust adaptive deployment

The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems – without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.

Quality balancing for parallel adaptive FEM

We present a dynamic distributed load balancing algorithm for parallel, adaptive finite element simulations using preconditioned conjugate gradient solvers based on domain-decomposition. The load balancer is designed to maintain good partition aspect ratios. It can calculate a balancing flow using different versions of diffusion and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. We show how to use information from the second step to guide the first. Experimental results using Bramble's preconditioner and comparisons to existing state-ot-the-art load balancers show the benefits of the construction.

Podcasting - delivering learning to the iTunes generation

The Guardian newspaper (21st October 2005) informed its readers that: "Stanford University in California is to make its course content available on iTunes...The service, Stanford on iTunes, will provide…downloads of faculty lectures, campus events, performances, book readings, music recorded by Stanford students and even podcasts of Stanford football games". The emergence of Podcasting as means of sending audio data to users has clearly excited educational technologists around the world. This paper will explore the technologies behind Podcasting and how this could be used to develop and deliver new E-Learning material. The paper refers to the work done to create Podcasts of lectures for University of Greenwich students.