Determining WWW User's Next Access and Its Application to Pre-fetching

World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Techniques like pre-fetching are likely to help users to personalize their needs, reducing their waiting times. However, pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Otherwise, pre-fetching will only waste bandwidth. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determining user's next move. One model uses Random Walk approximation and the other is based on Digital Signal Processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing.

Irish Times coverage of Irish relief and development nongovernmental organisations, legitimacy and accountability, 1994-2009: analysis and implications for the role of nongovernmental organisations

The overall aim of this study was to investigate the extent to which and ways in which Irish relief and development nongovernmental organisations (NGOs) were linked with the concepts of legitimacy and accountability in Irish Times newspaper coverage between 1994 and 2009. This research was based on a quantitative content analysis of 215 Irish Times articles and the results were analysed using statistical methods. Key findings of the research included that NGO accountability received significantly more coverage than NGO legitimacy, "principal-agent" approaches to NGO accountability received significantly more coverage than "stakeholder" approaches to NGO accountability, and questioning of NGOs based on either their accountability or legitimacy was very limited. It is suggested that these findings may indicate both a failure by Irish NGOs to promote "development literacy" and global solidarity among the Irish public, and a limited degree of "development literacy" and global solidarity among the Irish public.

Climate and energy scenarios for Ireland to 2050 using the Irish TIMES energy systems model

Due to growing concerns regarding the anthropogenic interference with the climate system, countries across the world are being challenged to develop effective strategies to mitigate climate change by reducing or preventing greenhouse gas (GHG) emissions. The European Union (EU) is committed to contribute to this challenge by setting a number of climate and energy targets for the years 2020, 2030 and 2050 and then agreeing effort sharing amongst Member States. This thesis focus on one Member State, Ireland, which faces specific challenges and is not on track to meet the targets agreed to date. Before this work commenced, there were no projections of energy demand or supply for Ireland beyond 2020. This thesis uses techno-economic energy modelling instruments to address this knowledge gap. It builds and compares robust, comprehensive policy scenarios, providing a means of assessing the implications of different future energy and emissions pathways for the Irish economy, Ireland’s energy mix and the environment. A central focus of this thesis is to explore the dynamics of the energy system moving towards a low carbon economy. This thesis develops an energy systems model (the Irish TIMES model) to assess the implications of a range of energy and climate policy targets and target years. The thesis also compares the results generated from the least cost scenarios with official projections and target pathways and provides useful metrics and indications to identify key drivers and to support both policy makers and stakeholder in identifying cost optimal strategies. The thesis also extends the functionality of energy system modelling by developing and applying new methodologies to provide additional insights with a focus on particular issues that emerge from the scenario analysis carried out. Firstly, the thesis develops a methodology for soft-linking an energy systems model (Irish TIMES) with a power systems model (PLEXOS) to improve the interpretation of the electricity sector results in the energy system model. The soft-linking enables higher temporal resolution and improved characterisation of power plants and power system operation Secondly, the thesis develops a methodology for the integration of agriculture and energy systems modelling to enable coherent economy wide climate mitigation scenario analysis. This provides a very useful starting point for considering the trade-offs between the energy system and agriculture in the context of a low carbon economy and for enabling analysis of land-use competition. Three specific time scale perspectives are examined in this thesis (2020, 2030, 2050), aligning with key policy target time horizons. The results indicate that Ireland’s short term mandatory emissions reduction target will not be achieved without a significant reassessment of renewable energy policy and that the current dominant policy focus on wind-generated electricity is misplaced. In the medium to long term, the results suggest that energy efficiency is the first cost effective measure to deliver emissions reduction; biomass and biofuels are likely to be the most significant fuel source for Ireland in the context of a low carbon future prompting the need for a detailed assessment of possible implications for sustainability and competition with the agri-food sectors; significant changes are required in infrastructure to deliver deep emissions reductions (to enable the electrification of heat and transport, to accommodate carbon capture and storage facilities (CCS) and for biofuels); competition between energy and agriculture for land-use will become a key issue. The purpose of this thesis is to increase the evidence-based underpinning energy and climate policy decisions in Ireland. The methodology is replicable in other Member States.

It Takes Two to Tango: Entrepreneurship and Creativity in Troubled Times – Vietnam 2012

Strikingly, most literature suggests that market competition will push firms to take creativity/innovation seriously as matter of death or survival. Using the data, we examined creativity methods (Napier and Nilsson, 2008; Napier, 2010) in conjunction with three influential cultural values – namely risk tolerance, relationship, and dependence on resources – to assess how they influence decisions of entrepreneurs.The primary objective of this study focuses on perceived values of entrepreneurship and creativity in business conducted within a turbulent environment. Our initial hypothesis is that a typical entrepreneurial process carries with it “creativity-enabling elements.” In a normal situation, when businesses focus more on optimizing their resources for commercial gains, perceptions about values of entrepreneurial creativity are usually vague. However, in difficult times and harsh competition, the difference between survival and failure may be creativity. This paper also examines many previous findings on both entrepreneurship and creativity and suggests a highly possible “organic growth” of creativity in an entrepreneurial environment and reinforcing value of entrepreneurship when creativity power is present. In other words, we see each idea reinforcing the other. We use data from a survey of sample Vietnamese firms during the chaotic economic year 2012 to learn about the ‘entrepreneurshipcreativity nexus.’ A data set of 137 responses qualified for a statistical examination was obtained from an online survey, which started on February 16 and ended May 24, 2012, sent to local entrepreneurs and corporate managers using social networks. The authors employed categorical data analysis (Agresti, 2002; Azen & Walker, 2011). Statistical analyses confirm that for business operation, the creativity and entrepreneurial spirit could hardly be separate; and, this is not only correct with entrepreneurial firm, but also well established companies. The single most important factor before business startup and during early implementation in Vietnam is what we call “connection/relationship.” However, businesspeople are increasingly aware of the need of creativity/innovation. In fact, we suggest that creativity and entrepreneurial spirit cannot be separated in entrepreneurial firms as well as established companies.

Applications of DNP-NMR for the measurement of heteronuclear T1 relaxation times

Measurement of heteronuclear spin-lattice relaxation times is hampered by both low natural abundance and low detection sensitivity. Combined with typically long relaxation times, this results in extended acquisition times which often renders the experiment impractical. Recently a variant of dynamic nuclear polarisation has been demonstrated in which enhanced nuclear spin polarisation, generated in the cryo-solid state, is transferred to the liquid state for detection. Combining this approach with small flip angle pulse trains, similar to the FLASH-T(1) imaging sequence, allows the rapid determination of spin-lattice relaxation times. In this paper we explore this method and its application to the measurement of T(1) for both carbon-13 and nitrogen-15 at natural abundance. The effects of RF inhomogeneity and the influence of proton decoupling in the context of this experiment are also investigated.

Modulated temperature differential scanning calorimetry and its application to freeze-drying

MTDSC is a software modification of the traditional DSC thermal analysis technique that allows more accurate determination of the glass transition as well as measurement of the endothermic relaxation that often accompanies the transition. The glass transition is an essential parameterboth of the original frozen solution and of the end product. Measurement of endothermic relaxation allows the determination of molecularrelaxation times in the freeze-dried product that may be useful in predicting the effect of formulation variables and storage conditions on physical stability.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times

The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

An Introduction to the Special issue - Housing in Hard Times: Marginality, Inequality and Class, with Kim McKee

‘Housing in Hard Times’ was the theme of the Housing Studies Association annual conference in April 2011. The papers featured in this special issue are drawn from that conference. They examine the uneven impact of economic change on housing policy and related areas, with reference to conceptual ideas pertaining to urban marginality, inequality and class. Whilst the empirical focus of the papers is the UK, their intellectual contribution represents an attempt to ‘bring class back in’ to the housing studies literature and encourage more critical, theoretically informed scholarship.

The application of the ecological footprint in two Irish urban areas: Limerick and Belfast

The ecological footprint is now a widely accepted indicator of sustainable
development. Footprinting translates resource consumption into the land area
required to sustain it, and allows for an average per capita footprint for a region
or nation to be compared with the global average. This paper reports on a project
in which footprints were calculated for two Irish cities, namely Belfast in
Northern Ireland and Limerick in the Republic of Ireland for the year 2001. As
is frequently the case at sub-national scale, data quality and availability were
often problematic, and in general data gaps were filled by means of population
proxies or national averages. A range of methods was applied to convert
resource flows to land areas. Both footprints suggest that the lifestyles of citizens
of the cities use several times more land than their global share, as has been
found for other cities.

Rapid design of application specific FFT cores

Methods are presented for developing synthesizable FFT cores. These are based on a modular approach in which parameterized commutator and processor blocks are cascaded to implement the computations required in many important FFT signal flow graphs. In addition, it is shown how the use of a digital serial data organization can be used to produce systems that offer 100% processor utilization along with reductions in storage requirements. The approach has been used to create generators for the automated synthesis of FFT cores that are portable across a broad range of silicon technologies. Resulting chip designs are competitive with ones created using manual methods but with significant reductions in design times.