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Supplemental Material, sj-pdf-1-ajh-10.1177_10499091211005735 for An Instrument to Assess Self-Perceived Competencies in End-of-Life Care for Health Care Professionals: The End-of-Life Care Questionnaire by Marcos Montagnini, Heather M. Smith, Deborah M. Price, Linda Strodtman and Bidisha Ghosh in American Journal of Hospice and Palliative Medicine��

Underwater inspections stand to gain from using stereo imaging systems to collect three-dimensional measurements. Although many stereo-matching algorithms have been devised to solve the correspondence problem, that is, find the same points in multiple images, these algorithms often perform poorly when applied to images of underwater scenes due to the poor visibility and the complex underwater light field. This article presents a new stereo-matching algorithm, called PaLPaBEL (Pyramidal Loopy Propagated BELief) that is designed to operate on challenging imagery. At its core, PaLPaBEL is a semiglobal method based on a loopy belief propagation message passing algorithm applied on a Markov random field. A pyramidal scheme is adopted that enables wide disparity ranges and high-resolution images to be handled efficiently. For performance evaluation, PaLPaBEL is applied to underwater stereo images captured under various visibility conditions in a laboratory setting, and to synthetic imagery created in a virtual underwater environment. The technique is also demonstrated on stereo images obtained from a real-world inspection. The successful results indicate that PaLPaBEL is well suited for underwater application and has value as a tool for the cost-effective inspection of marine structures. Science Foundation Ireland CAPACITES/IXEAD Society

We are presenting an evaluation of the outcomes of the FAIRMODE & AQUILA intercomparison exercise (IE) on spatial representativeness (SR). The assessment of the spatial representativeness (SR) of air quality monitoring stations is an important subject that is linked to several highly topical areas, including risk assessment and population exposure, the design of monitoring networks, model development, model evaluation and data assimilation. Nevertheless, European regulations lack a clear definition and provisions to determine the SR of the stations. Also in the scientific literature, there is no unified agreement to address this complex problem. In order to further explore this topic and to make progress in the harmonization of the related assessment procedures, the FAIRMODE (Forum for Air Quality Modelling in Europe) Cross-Cutting Activity group on SR organized a comprehensive intercomparison exercise (IE). The main objective of this IE was to evaluate the scattering of spatial representativeness results obtained by applying the range of different contemporary approaches to a jointly used example case study. In order to ensure a broad participation in this exercise, a collaborative effort has been established between FAIRMODE and AQUILA (the European Network of Air Quality Reference Laboratories). As a working basis, a shared dataset has been collected among a set of monitoring, emission and modelling data from the city of Antwerp. Within this IE, 11 different teams from 9 different countries provided their SR estimates for PM10 and NO2 at one traffic site, and for PM10, NO2 and O3 at two urban background sites. In order to narrow down the range of conceivable SR approaches and definitions, it was beforehand suggested to use the area of SR of the monitoring sites as a general concept to work with. During the course of the exercise, this concept of the SR area in fact turned out to be a useful indicator, and 10 of 11 teams were able to define shapes surrounding the stations under investigation, whereas one team rather worked towards a classification of the stations, as this was more common practice for SR evaluation in their member state. The resulting SR areas nevertheless revealed a considerable range of dissimilarity between the different teams - not only in terms of the extent and position of the SR perimeters, but also in the technical procedures and the extent of input data effectively used. These differences required detailed evaluations in order to identify the major factors triggering and controlling this spread, which can be found amongst (1) the basic principles of the methods, (2) the parameterization of the similarity criteria and thresholds, (3) the effective use of input data, and (4) the detailed conceptualization and definitions of SR. These outcomes do underline the need for (i) a more harmonized definition of the concept of “the area of representativeness” and (ii) consistent and transparent criteria used for its quantification. A comprehensive concluding section (chapter 10) is highlighting the challenges that the expert community working on spatial representativeness is currently facing. Recommendations are given for the directions to be focused on SR in the near to mid-term future. In this regards, we are outlining a roadmap towards a modular approach for better SR characterization. It is stressed that that for the aim of harmonization the concept of spatial representativeness will probably require a paradigm shift in its definition. Beyond the questions of harmonization, it should not be disregarded that alternative interpretations for the strong variability of the SR results might exist. The observed divergences in SR results could for example point us to some more fundamental discrepancies related to the evaluation of the air quality data. It is advised to take care, that in the endeavour for methodological harmonization such alternative explanations are not overlooked. An example could be a potential inconsistency within the input data coming from emission, monitoring and modelled data. Furthermore, the findings of this study are not only relevant with regard to the SR of a single monitoring station. It also gives evidence that questions need to be raised about what is the real representativeness of network monitoring data in general since it seems that there is no current consensus on its evaluation. Example given: Is there a need for the European Commission to check the criteria for the number and the siting of Air Quality Monitoring Stations set in the Air Quality Directive when a consensus on SR is reached?, JRC.C.5-Air and Climate

Imaging‐based damage detection techniques are increasingly being utilized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of quantitative information for ensuring their continued safe and economic operation. However, there exists scope for significant development of improved damage detection algorithms that can characterize features of interest in challenging scenes with credibility. This article presents a new regionally enhanced multiphase segmentation (REMPS) technique that is designed to detect a broad range of damage forms on the surface of civil infrastructure. The technique is successfully applied to a corroding infrastructure component in a harbour facility. REMPS integrates spatial and pixel relationships to identify, classify, and quantify the area of damaged regions to a high degree of accuracy. The image of interest is preprocessed through a contrast enhancement and color reduction scheme. Features in the image are then identified using a Sobel edge detector, followed by subsequent classification using a clustering‐based filtering technique. Finally, support vector machines are used to classify pixels which are locally supplemented onto damaged regions to improve their size and shape characteristics. The performance of REMPS in different color spaces is investigated for best detection on the basis of receiver operating characteristics curves. The superiority of REMPS over existing segmentation approaches is demonstrated, in particular when considering high dynamic range imagery. It is shown that REMPS easily extends beyond the application presented and may be considered an effective and versatile standalone segmentation technique. Irish Research Council for Science, Engineering and Technology

We report a case of biphasic synovial sarcoma of the mediastinum, a very rare tumor, in a 12-year-old boy with left-sided chest pain of 3 years duration at presentation. Chest X-ray showed left-sided opacity with loss of cardiac silhouette and the mediastinum deviated to the opposite side. Computed tomography (CT) of thorax showed left-sided posterior mediastinal mass with left-sided pleural effusion and pleural thickening. CT guided fine needle aspiration cytology (FNAC) from the mass reported it as spindle cell variant of adenocarcinoma. Ultrasonography (USG) of the whole abdomen revealed no abnormality. The mediastinal tumor was resected by left thoracotomy and histopathological report confirmed it to be a biphasic synovial sarcoma with capsule invasion at places.

This paper presents the development of a new mobile application, Rothaím, as Ireland’s first adaptive route planner for cyclists. The mobile application is developed on an Android platform and is dependent on Global Positioning System (GPS) technology. The application is capable of tracking the behaviour, the motivation and the perceptions of cyclists in the Irish road network. Although Dublin is one of the upcoming cities in friendliness towards cycling, there has been very little data collected in this regard and the development of Rothaím is expected to remedy this deficiency to a significant extent. The impact of the application on urban mobility is immediate and it also creates a data repository to analyse the behaviour of cyclists in a mixed mode network. Consequently, Rothaím is expected to play a positive role in choosing cycling as a green and sustainable option, thereby offering a push towards a modal split to the advantage of urban cycling. Cycling is unique in terms of mode choice and the desired route may significantly vary from the least path. This application has the potential to quantify these varied options of route choice. The design of the application is discussed in detail. The development of the application, related practical issues and implementation are presented. The capability of the collected information to personalize data is demonstrated.

This book is the final report of the COST TU0702 'Real-time monitoring, surveillance and control of road networks under adverse weather conditions'. This project was initiated with the main objectives of better understanding impacts of adverse weather on freeways, motorways, or urban traffic operations and developing, promoting and implementing strategies and tools to mitigate those impacts.It provides a comprehensive analysis on how adverse weather impacts transport infrastructure and users behaviors, and how to manage a safer and more productive road networks under these inclement weather conditions. Finally, recommendations are provided on how road authorities can implement in an efficient manner weather sensitive-traffic management strategies for improved traffic safety.

In a road network, cyclists are the group exposed to the maximum amount of risk. Route choice of a cyclist is often based on level of expertise, perceived or actual road risks, personal decisions, weather conditions and a number of other factors. Consequently, cycling tends to be the only significant travel mode where optimised route choice is not based on least-path or least-time. This paper presents an Android platform based mobile-app for personalised route planning of cyclists in Dublin. The mobile-app, apart from its immediate advantage to the cyclists, acts as the departure point for a number of research projects and aids in establishing some critical calibration values for the cycling network in Dublin.

The successful detection of change in a data or in any of its derivatives in the presence of noise is a critical component of structural health monitoring and damage detection. This sudden change can be brought about by a sudden change in the strain or the stress field of the structural system under consideration. Two very typical examples of such sudden changes are the sudden change in stiffness of a vibrating single degree of freedom system in time and the local perturbation of stress and strain fields of a beamlike structure in space due to the presence of an open crack. New methods and analysis techniques have become popular in the field of structural health monitoring to detect and characterise such changes. Time – frequency techniques, like wavelet analysis are being more widely used in this regard in the recent times for the detection of presence, location and the calibration of the extent of these changes. This paper presents the application of S transform for the successful detection and calibration of damage in time and in space in the presence of additive Gaussian white noise. The performance of S transform based detection is compared with wavelet based and statistics based methodologies. The application and use of S transform in the field of structural health monitoring is observed to be extremely promising.

PUBLISHED, Washington D.C., In ITS (Intelligent Transportation System) equipped urban transportation systems noncritical junctions are often ignored in short-term traffic condition prediction algorithms as the traffic data collection systems in these junctions are not adequate. The paper proposes a shortterm traffic volume model based on a combination of discrete wavelet transform (DWT) and Bayesian hierarchical methodology (BHM) applicable to non-critical junctions lacking continuous data collection systems. Unlike typical short-term traffic condition forecasting algorithms, large traffic flow datasets including information on current traffic scenarios are not required for the proposed model. In this model, a non-functional representation of the daily `trend? of urban traffic flow observations is achieved using DWT while the fluctuations in the traffic flow in addition to the variations represented by the `trend? are modeled as a stochastic process using BHM. The time-varying variance (within day) of these fluctuations over the `trend? in urban traffic flow observations at a signalized intersection has been estimated in the model. The effectiveness and the accuracy of the model have been compared with a conventional short-term traffic flow forecasting time-series model based on Holt-Winters Exponential Smoothing (HWES) technique. Both the models are applied at two signalized intersections at the city-centre of Dublin and their performances have been discussed., The research work is funded under the Program for Research in Third-Level Institutions (PRTLI), administered by the HEA.

PUBLISHED, Washington D.C., The traffic flow at an arterial intersection in a congested urban transportation network in the city of Dublin is modelled in this paper. Three different time-series models, viz. random walk model, Holt-Winters? exponential smoothing technique and seasonal ARIMA model are used for modeling of traffic flow in Dublin. Simulation and short-term forecasting of univariate traffic flow data are done using these models. The data used for modeling are obtained from loop-detectors at a certain junction in the city center of Dublin. Seasonal ARIMA and Holt-Winters? exponential smoothing technique give highly competitive forecasts and match considerably well with the observed traffic flow data during rush hours., The research work is funded under the Programme for Research in Third-Level Institutions (PRTLI), under the NDP, administered by the HEA.

Consuming about 60% of natural resources, construction industry recently has been under a continuous pressure to ensure an efficient consumption of natural resources. Recent decades have witnessed some valuable steps toward making the construction industry more sustainable. This includes the trials to change the linear life cycle model to cyclic one by the consideration of the 3Rs; recycling, reusing and reducing to help in closing the material loop. However, recent studies have showed that the reason for demolition is not really the end-of-life span of structures but actually the lack of adaptability, also, demolition and recycling demand huge energy. So that the possibility to dismantle/disassemble/demount an RC building in order to salvage its material for reuse has been under focus. This requires the design for deconstruction “DfD” to close the loop of materials similar to cradle-to-cradle model where “waste” is turned into “feed” in comparison with cradle-to-grave thinking. The structures should be designed as a prefabricated structures and elements should be joint in dry way. The current paper will review the concept of structure demountability in the context of the recent advances in building systems and the ongoing researches in the area. Some early real cases of demountable structures in Europe will be discussed and challenges including design requirements and future directions will be highlighted.

The continual inspection, assessment and maintenance of bridges requires a multidisciplinary approach. Beyond a good understanding of structural engineering, a bridge inspector must have a good knowledge and appreciation of geotechnics, hydraulics, hydrology, materials and even transport management. A number of international standards and guidelines exist based on experience, historical events and best practice in industry. However, the risk-informed decision-making process in bridge monitoring is complex. Thus, the application of intelligent assessment measures built using Bayesian Logic controls can assist in ensuring a failsafe bridge inspection programme. This paper provides a review of some existing bridge assessment, maintenance and monitoring guidelines and standards. In addition, the Self- Informed Bridge Inspection, Assessment and Maintenance Management Tool (SIBIAM) developed using a Bayesian Logic approach is presented. SIBIAM uses a GIS (Geographic Information Systems) specialised software tool. The purpose of SIBIAM is to provide for bridge owners, an up-to-date inventory of bridge condition and maintenance information by collecting and monitoring relevant bridge and river parameters for input to a management database.

Under EU Directive 2009/28/EC on Renewable Energy each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including an increase in the use of biofuels in transport by 3% by 2010 and ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. Electric vehicles (EVs) do not emit exhaust fumes in the same manner as traditional internal combustion engine (ICE) vehicles. The optimal benefits of EVs can only be truly achieved if EVs are deployed effectively, so that exhaust pipe gaseous emissions are not fully displaced to the electricity sector. This paper examines the potential contributions that Plug in Hybrid Electric Vehicles can make in reducing carbon dioxide. The paper presents the results of the generation expansion model for Northern Ireland and the Republic of Ireland built using the dynamic programming based long term generation expansion planning tool called the Wien Automatic System Planning IV tool. The model optimizes power dispatch using hourly electricity demand curves for each year up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. In order to simulate the effect of PHEV, two distinct charging scenarios are applied based on a peak tariff and an off peak tariff. The importance and influence of the charging regime on the amount of energy used and gaseous emissions displaced is determined and briefly discussed.

In 2008, renewable energy accounted for less than 1% of final energy consumption in the Irish transport sector. In order to increase this share to 10% by 2020 as required under EU directive 2009/28/EC, the Irish government has introduced two specific measures: 10% of the transport fleet is to be powered by electricity by 2020, and an obligation on road transport fuel suppliers that biofuels account for a certain portion of their fuel sales. This study forecasts the impact of these existing measures towards meeting the 10% RES-T target by 2020, focussing on private car transport. The methodology presented is derived from a forecast of private car fuel demand based on a technological stock model of Ireland’s fleet. This paper demonstrates the use of this as a tool firstly as an energy forecasting technique and secondly as a method for evaluating the effects of policy measures on the technological composition and consequent renewable energy demand and related CO2emissions of private cars. Technological scenarios examined in this light are electric vehicles, compressed natural gas vehicles and biofuel blending

In 2009 the European Union (EU) Directive on Renewable Energy placed an obligation on each Member State to ensure that 10% of transport energy (excluding aviation and marine transport) come from renewable sources by 2020. The Irish Government intends to achieve part of this target by making sure that 10% of all vehicles in its transport fleet are powered by electricity by 2020. Stakeholder groups include but are not limited to policy makers, the public, regulatory bodies, participants in the electricity retail market, the transmission and distribution system grid operators, the automotive industry, private enterprise, civil engineers, electrical engineers, electricians, architects, builders, building owners, building developers, building managers, fleet managers and EV owners. Currently it appears both internationally and Nationally the automotive industry is focused on EV manufacture, governments and policy makers have highlighted the potential environmental and job creation opportunities while the electricity sector is preparing for an additional electrical load on the grid system. The focus of this paper is to produce an international EV roadmap. A review of current international best practice and guidelines under consideration or recommended is presented. An update on any EV infrastructure charging equipment standards is also provided. Finally the regulatory modifications to existing National legislation as well as additional infrastructure items which may need control via new regulations are identified.