Leisure and surveillance in Irish childhoods: A cross-class study of Cork city

This research provides an interpretive cross-class analysis of the leisure experience of children, aged between six and ten years, living in Cork city. This study focuses on the cultural dispositions underpinning parental decisions in relation to children’s leisure activities, with a particular emphasis on their child-surveillance practices. In this research, child-surveillance is defined as the adult monitoring of children by technological means, physical supervision, community supervision, or adult supervised activities (Nelson, 2010; Lareau, 2003; Fotel and Thomsen, 2004). This research adds significantly to understandings of Irish childhood by providing the first in-depth qualitative analysis of the surveillance of children’s leisure-time. Since the 1990s, international research on children has highlighted the increasingly structured nature of children’s leisure-time (Lareau, 2011; Valentine & McKendrick, 1997). Furthermore, research on child-surveillance has found an increase in the intensive supervision of children during their unstructured leisure-time (Nelson, 2010; Furedi, 2008; Fotel and Thomsen, 2004). This research bridges the gap between these two key bodies of literature, providing a more integrated overview of children’s experience of leisure in Ireland. Using Bourdieu’s (1992) model of habitus, field and capital, the dispositions that shape parents’ decisions about their children’s leisure time are interrogated. The holistic view of childhood adopted in this research echoes the ‘Whole Child Approach’ by analysing the child’s experience within a wider set of social relationships including family, school, and community. Underpinned by James and Prout’s (1990) paradigm on childhood, this study considers Irish children’s agency in negotiating with parents’ decisions regarding leisure-time. The data collated in this study enhances our understanding of the micro-interactions between parents and children and, the ability of the child to shape their own experience. Moreover, this is the first Irish sociological research to identify and discuss class distinctions in children’s agentic potential during leisure-time.

Design of miniaturized wireless sensor mote and actuator for building monitoring and control

In this paper, a wireless sensor network mote hardware design and implementation are introduced for building deployment application. The core of the mote design is based on the 8 bit AVR microcontroller, Atmega1281 and 2.4 GHz wireless communication chip, CC2420. The module PCB fabrication is using the stackable technology providing powerful configuration capability. Three main layers of size 25 mm2 are structured to form the mote; these are RF, sensor and power layers. The sensors were selected carefully to meet both the building monitoring and design requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks. Experiments show that the developed mote works effectively in giving stable data acquisition and owns good communication and power performance.

A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain

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.

Development of miniaturized wireless sensor nodes suitable for building energy management and modelling

Buildings consume 40% of Ireland's total annual energy translating to 3.5 billion (2004). The EPBD directive (effective January 2003) places an onus on all member states to rate the energy performance of all buildings in excess of 50m2. Energy and environmental performance management systems for residential buildings do not exist and consist of an ad-hoc integration of wired building management systems and Monitoring & Targeting systems for non-residential buildings. These systems are unsophisticated and do not easily lend themselves to cost effective retrofit or integration with other enterprise management systems. It is commonly agreed that a 15-40% reduction of building energy consumption is achievable by efficiently operating buildings when compared with typical practice. Existing research has identified that the level of information available to Building Managers with existing Building Management Systems and Environmental Monitoring Systems (BMS/EMS) is insufficient to perform the required performance based building assessment. The cost of installing additional sensors and meters is extremely high, primarily due to the estimated cost of wiring and the needed labour. From this perspective wireless sensor technology provides the capability to provide reliable sensor data at the required temporal and spatial granularity associated with building energy management. In this paper, a wireless sensor network mote hardware design and implementation is presented for a building energy management application. Appropriate sensors were selected and interfaced with the developed system based on user requirements to meet both the building monitoring and metering requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks associated with minimisation of energy consumption in the built environment and the development of appropriate Building information models(BIM)to enable the design and development of energy efficient spaces.

Hazard and early warning analysis based on domain specific modeling technologies

An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

Cancer related fatigue and self-care while undergoing chemotherapy: patients' perspectives

Background: Cancer related fatigue (CRF) is considered the most severe, debilitating and under-managed symptom of cancer. Patients receiving chemotherapy experience high levels of CRF which profoundly impacts on their lives. Aim: 1). To explore and measure CRF and determine the most effective self-care strategies used to combat CRF in a cohort of patients with a diagnosis of cancer (breast cancer, colorectal cancer, Hodgkin’s and Non-Hodgkin’s lymphoma) 2). To explore self-care agency and its relationship to CRF. Method: A mixed methods study which incorporated a descriptive, comparative, correlational design and qualitative descriptions of patients’ (n=362) experiences gleaned through open ended questions and use of a diary. The study utilised The Revised Pipers Fatigue Scale, the Appraisal of Self-Care Agency and a researcher developed Fatigue Visual Analogue Scale, Fatigue Self-Care Survey, and Diary. Findings: Having breast cancer, Hodgkin’s lymphoma, non-Hodgkin’s lymphoma; using the strategies of counselling, taking a 20–30 minute nap, resting and sleeping, self-monitoring and complementary therapies were all associated with increased odds of developing fatigue. Increased self-care agency; being in the divorced / separated cohort; being widowed; increased length of time since commencement of chemotherapy; engagement in exercise, and socializing were associated with a reduced risk of developing fatigue. Females had 20% higher fatigue levels than males (p=<.001). Receiving support was the strategy used most frequently and rated most effective. Fatigue was very problematic and distressing, four key qualitative categories emerged: the behavioural impact, affective impact, the sensory impact, and the cognitive impact. Keeping a diary was considered very beneficial and cathartic. Conclusions: Fatigue severely impacted on the daily lives of patients undergoing chemotherapy. There are a range of self-care strategies that patients should be encouraged to use e.g. exercise, socializing, and enhancement of psychological well-being. The enhancement of self-care agency and use of diaries should also be considered.

New phosphorescence based probes and techniques for the analysis of cellular oxygen and respiration

Real time monitoring of oxygenation and respiration is on the cutting edge of bioanalysis, including studies of cell metabolism, bioenergetics, mitochondrial function and drug toxicity. This thesis presents the development and evaluation of new luminescent probes and techniques for intracellular O2 sensing and imaging. A new oxygen consumption rate (OCR) platform based on the commercial microfluidic perfusion channel μ-slides compatible with extra- and intracellular O2 sensitive probes, different cell lines and measurement conditions was developed. The design of semi-closed channels allowed cell treatments, multiplexing with other assays and two-fold higher sensitivity to compare with microtiter plate. We compared three common OCR platforms: hermetically sealed quartz cuvettes for absolute OCRs, partially sealed with mineral oil 96-WPs for relative OCRs, and open 96-WPs for local cell oxygenation. Both 96-WP platforms were calibrated against absolute OCR platform with MEF cell line, phosphorescent O2 probe MitoXpress-Intra and time-resolved fluorescence reader. Found correlations allow tracing of cell respiration over time in a high throughput format with the possibility of cell stimulation and of changing measurement conditions. A new multimodal intracellular O2 probe, based on the phosphorescent reporter dye PtTFPP, fluorescent FRET donor and two-photon antennae PFO and cationic nanoparticles RL-100 was described. This probe, called MM2, possesses high brightness, photo- and chemical stability, low toxicity, efficient cell staining and high-resolution intracellular O2 imaging with 2D and 3D cell cultures in intensity, ratiometric and lifetime-based modalities with luminescence readers and FLIM microscopes. Extended range of O2 sensitive probes was designed and studied in order to optimize their spectral characteristics and intracellular targeting, using different NPs materials, delivery vectors, ratiometric pairs and IR dyes. The presented improvements provide useful tool for high sensitive monitoring and imaging of intracellular O2 in different measurement formats with wide range of physiological applications.