Monitoring and modelling the morphodynamic evolution of a breached barrier beach system

Predicting the evolution of a coastal cell requires the identification of the key drivers of morphology. Soft coastlines are naturally dynamic but severe storm events and even human intervention can accelerate any changes that are occurring. However, when erosive events such as barrier breaching occur with no obvious contributory factors, a deeper understanding of the underlying coastal processes is required. Ideally conclusions on morphological drivers should be drawn from field data collection and remote sensing over a long period of time. Unfortunately, when the Rossbeigh barrier beach in Dingle Bay, County Kerry, began to erode rapidly in the early 2000’s, eventually leading to it breaching in 2008, no such baseline data existed. This thesis presents a study of the morphodynamic evolution of the Inner Dingle Bay coastal system. The study combines existing coastal zone analysis approaches with experimental field data collection techniques and a novel approach to long term morphodynamic modelling to predict the evolution of the barrier beach inlet system. A conceptual model describing the long term evolution of Inner Dingle Bay in 5 stages post breaching was developed. The dominant coastal processes driving the evolution of the coastal system were identified and quantified. A new methodology of long term process based numerical modelling approach to coastal evolution was developed. This method was used to predict over 20 years of coastal evolution in Inner Dingle Bay. On a broader context this thesis utilised several experimental coastal zone data collection and analysis methods such as ocean radar and grain size trend analysis. These were applied during the study and their suitability to a dynamic coastal system was assessed.

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

Sex offender risk assessment and management in Ireland

This research examined sex offender risk assessment and management in Ireland. It focused on the statutory agencies with primary responsibility (Garda Síochána and the Probation Service). The goal was to document the historical, contextual and current systems, in addition to identifying areas of concern/improvements. The research was a mixed-methods approach. Eight studies were conducted. This incorporated documentary reviews of four Commission to Inquire Reports, qualitative interviews/focus groups with Garda staff, Probation Service staff, statutory agencies, community stakeholders, various Non-Governmental Organisations (NGOs) and sex offenders. Quantitative questionnaires were also administered to Garda staff. In all over 70 interviews were conducted and questionnaires were forwarded to 270 Garda members. The overall findings are: •Sex offender management in Ireland has become formal only since 2001. Knowledge, skills and expertise is in its infancy and is still evolving. •Mixed reviews and questions regarding fitness for purpose of currently used risk assessments tools were noted. •The Sex Offender Act 2001 requires additional elements to ensure safe sex offender monitoring and public protection. A judicial review of the Sex Offender Act 2001 was recommended by many respondents. •Interagency working under SORAM was hugely welcomed. The sharing of information has been welcomed by managing agencies as the key benefit to improving sex offender management. •Respondents reported that in practice, sex offender management in Ireland is fragmented and unevenly implemented. The research concluded that an independent National Sex Offender Authority should be established as an oversight and regulatory body for policy, strategy and direction in sex offender management. Further areas of research were also highlighted: ongoing evaluation and audits of the joint agency process and systems in place; recidivism studies tracking the risk assessment ratings and subsequent offending; and an evaluation of the current status of sex offender housing in Ireland.

Improving the care of preterm infants: before, during, and after, stabilisation in the delivery room

Introduction Up to 10% of infants require stabilisation during transition to extrauterine life. Enhanced monitoring of cardiorespiratory parameters during this time may improve stabilisation outcomes. In addition, technology may facilitate improved preparation for delivery room stabilisation as well as NICU procedures, through educational techniques. Aim To improve infant care 1) before birth via improved training, 2) during stabilisation via enhanced physiological monitoring and improved practice, and 3) after delivery, in the neonatal intensive care unit (NICU), via improved procedural care. Methods A multifaceted approach was utilised including; a combination of questionnaire based surveys, mannequin-based investigations, prospective observational investigations, and a randomised controlled trial involving preterm infants less than 32 weeks in the delivery room. Forms of technology utilised included; different types of mannequins including a CO2 producing mannequin, qualitative end tidal CO2 (EtCO2) detectors, a bespoke quantitative EtCO2 detector, and annotated videos of infant stabilisation as well as NICU procedures Results Manual ventilation improved with the use of EtCO2 detection, and was positively assessed by trainees. Quantitative EtCO2 detection in the delivery room is feasible, EtCO2 increased over the first 4 minutes of life in preterm infants, and EtCO2 was higher in preterm infants who were intubated. Current methods of heart rate assessment were found to be unreliable. Electrocardiography (ECG) application warrants further evaluation. Perfusion index (PI) monitoring utilised in the delivery room was feasible. Video recording technology was utilised in several ways. This technology has many potential benefits, including debriefing and coaching in procedural healthcare, and warrants further evaluation. Parents would welcome the introduction of webcams in the NICU. Conclusions I have evaluated new methods of improving infant care before, during, and after stabilisation in the DR. Specifically, I have developed novel educational tools to facilitate training, and evaluated EtCO2, PI, and ECG during infant stabilisation. I have identified barriers in using webcams in the NICU, to now be addressed prior to webcam implementation.

A pro-active and dynamic prediction assistance using BaranC framework

Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic; it is dynamic both in responding to the current context, and also in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Axle bearing damage with possible catastrophic failures can cause severe disruptions or even dangerous derailments, potentially causing loss of human life and leading to significant costs for railway infrastructure managers and rolling stock operators. Consequently the axle bearing damage process has safety and economic implications on the exploitation of railways systems. Therefore it has been the object of intense attention by railway authorities as proved by the selection of this topic by the European Commission in calls for research proposals. The MAXBE Project (http://www.maxbeproject.eu/), an EU-funded project, appears in this context and its main goal is to develop and to demonstrate innovative and efficient technologies which can be used for the onboard and wayside condition monitoring of axle bearings. The MAXBE (interoperable monitoring, diagnosis and maintenance strategies for axle bearings) project focuses on detecting axle bearing failure modes at an early stage by combining new and existing monitoring techniques and on characterizing the axle bearing degradation process. The consortium for the MAXBE project comprises 18 partners from 8 member states, representing operators, railway administrations, axle bearing manufactures, key players in the railway community and experts in the field of monitoring, maintenance and rolling stock. The University of Porto is coordinating this research project that kicked-off in November 2012 and it is completed on October 2015. Both on-board and wayside systems are explored in the project since there is a need for defining the requirement for the onboard equipment and the range of working temperatures of the axle bearing for the wayside systems. The developed monitoring systems consider strain gauges, high frequency accelerometers, temperature sensors and acoustic emission. To get a robust technology to support the decision making of the responsible stakeholders synchronized measurements from onboard and wayside monitoring systems are integrated into a platform. Also extensive laboratory tests were performed to correlate the in situ measurements to the status of the axle bearing life. With the MAXBE project concept it will be possible: to contribute to detect at an early stage axle bearing failures; to create conditions for the operational and technical integration of axle bearing monitoring and maintenance in different European railway networks; to contribute to the standardization of the requirements for the axle bearing monitoring, diagnosis and maintenance. Demonstration of the developed condition monitoring systems was performed in Portugal in the Northern Railway Line with freight and passenger traffic with a maximum speed of 220 km/h, in Belgium in a tram line and in the UK. Still within the project, a tool for optimal maintenance scheduling and a smart diagnostic tool were developed. This paper presents a synthesis of the most relevant results attained in the project. The successful of the project and the developed solutions have positive impact on the reliability, availability, maintainability and safety of rolling stock and infrastructure with main focus on the axle bearing health.