Review of the area planning process (a)

The area planning process continues and formal recommendations arising from it are now being brought forward as development proposals to amalgamate or close schools. At this point in the process the Education Committee requested some comment on five different aspects of the process: the impact of Area Planning to date; the validity of the surplus school vacancy calculation methodology; the Annual Area Profile information; the Needs Model (including as appropriate the implications of the Drumragh judgement); possible enhancements to the consultation and communication process;the facilitation of alternative cross-sectoral or cross-border solutions. This paper offers high level comment on each of these issues. In addition, the Education Committee facilitated a stakeholder consultation meeting in Parliament Buildings on 4 February, 2015. The broad themes that emerged in that discussion will also be mentioned in this paper.

Towards agent-oriented model-driven architecture

Model Driven Architecture supports the transformation from reusable models to executable software. Business representations, however, cannot be fully and explicitly represented in such models for direct transformation into running systems. Thus, once business needs change, the language abstractions used by MDA (e.g. Object Constraint Language / Action Semantics), being low level, have to be edited directly. We therefore describe an Agent-oriented Model Driven Architecture (AMDA) that uses a set of business models under continuous maintenance by business people, reflecting the current business needs and being associated with adaptive agents that interpret the captured knowledge to behave dynamically. Three contributions of the AMDA approach are identified: 1) to Agent-oriented Software Engineering, a method of building adaptive Multi-Agent Systems; 2) to MDA, a means of abstracting high level business-oriented models to align executable systems with their requirements at runtime; 3) to distributed systems, the interoperability of disparate components and services via the agent abstraction.

Resource access needs and capabilities as mediators of the relationship between VC firm size and syndication

Drawing from the resource-based view and transaction costs economics, we develop a theoretical framework to explain why small and large firms face different levels of resource access needs and resource access capabilities, which mediate the relationship between firm size and hybrid governance. Employing a sample of 317 venture capital firms, drawn across six European countries, we empirically assess our framework in the context of venture capital syndication. We estimate a path model using structural equation modeling and find, consistent with our theoretical framework, mediating effects of different types of resource access needs and resource access capabilities between VC firm size and syndication frequency. These findings advance the small business literature by highlighting the trade-offs that size imposes on firms that seek to manage their access to external resources through hybrid governance strategies.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

The technical merits of turbogenerating shown through the design, validation and implementation of a 1 dimensional engine model

Turbocompounding is the process of recovering a proportion of an engine’s fuel energy that would otherwise be lost in the exhaust process and adding it to the output power. This was first seen in the 1930s and is carried out by coupling an exhaust gas turbine to the crankshaft of a reciprocating engine. It has since been recognised that coupling the power turbine to an electrical generator instead of the crankshaft has the potential to reduce the fuel consumption further with the added flexibility of being able to decide how this recovered energy is used. The electricity generated can be used in automotive applications to assist the crankshaft using a flywheel motor generator or to power ancillaries that would otherwise have run off the crankshaft. In the case of stationary power plants, it can assist the electrical power output. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimise the specific fuel consumption for different engine operating conditions. This method of energy recapture is termed ‘turbogenerating’.

This paper gives a brief history of turbocompounding and its thermodynamic merits. It then moves on to give an account of the validation of a turbogenerated engine model. The model is then used to investigate what needs to be done to an engine when a turbogenerator is installed. The engine being modelled is used for stationary power generation and is fuelled by an induced biogas with a small portion of palm oil being injected into the cylinder to initiate combustion by compression ignition. From these investigations, optimum settings were found that result in a 10.90% improvement in overall efficiency. These savings relate to the same engine without a turbogenerator installed operating with fixed fuelling.

A design model: the Autism Spectrum Disorder Classroom Design Kit

Architects and designers have a responsibility to provide an inclusive built environment. However for those with a diagnosis of Autism Spectrum Disorder (ASD), the built environment can be a frightening and confusing place, difficult to negotiate and tolerate. The challenge of integrating more fully into society is denied by an alienating built environment. For ASD pupils in a poorly designed school, their environment can distance them from learning. Instead, if more at ease in their surroundings, in an ASD-friendly environment, the ASD pupil stands a greater chance of doing better.

However a difficulty exists in that most architects are not knowledgeable in designing for those with ASD. Any available design guidelines for architects tend, because of the inherent difficulties associated with a spectrum, to be general in their information. Therefore, if wanting to provide an ASD-friendly learning environment, there is a need to ensure that teachers, as the experts, can most clearly and effectively impart their knowledge and requirements to architects.

This paper sets out the challenges and difficulties inherent in the design process when designing for ASD. It then sets out an alternative strategy to the usual method of drawing-centric dialogue between teacher and architect by using models instead as a basis for a more common language. An ASD Classroom Design Kit was designed and developed by Queen’s University of Belfast Architecture students. It was then used by ASD teaching staff from the Southern Education and Library Board in Northern Ireland as a case study to trial its effectiveness. The paper outlines how the study was carried out before concluding with reflections by both teaching staff and architect on using the ASD Classroom Design Kit.

It is hoped that this paper will firstly highlight the need for better dialogue between expert and architect when considering ASD and the Built Environment and secondly, that it may encourage others to consider using models to convey their ideas and knowledge when designing, not just for ASD, but for other Special Educational Needs and disabilities.

A shared care model pilot for palliative home care in a rural area:Impact on symptoms, distress, and place of death

Context: Shared care models integrating family physician services with interdisciplinary palliative care specialist teams are critical to improve access to quality palliative home care and address multiple domains of end-of-life issues and needs. Objectives: To examine the impact of a shared care pilot program on the primary outcomes of symptom severity and emotional distress (patient and family separately) over time and, secondarily, the concordance between patient preferences and place of death. Methods: An inception cohort of patients (n = 95) with advanced, progressive disease, expected to die within six months, were recruited from three rural family physician group practices (21 physicians) and followed prospectively until death or pilot end. Serial measurement of symptoms, emotional distress (patient and family), and preferences for place of death was performed, with analysis of changes in distress outcomes assessed using t-tests and general linear models. Results: Symptoms trended toward improvement, with a significant reduction in anxiety from baseline to 14 days noted. Symptom and emotional distress were maintained below high severity (7-10), and a high rate of home death compared with population norms was observed. Conclusion: Future controlled studies are needed to examine outcomes for shared care models with comparison groups. Shared care models build on family physician capacity and as such are promising in the development of palliative home care programs to improve access to quality palliative home care and foster health system integration. © 2011 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Enhancing family physician capacity to deliver quality palliative home care:An end-of-life, shared-care model

PROBLEM BEING ADDRESSED: Family physicians face innumerable challenges to delivering quality palliative home care to meet the complex needs of end-of-life patients and their families. OBJECTIVE OF PROGRAM: To implement a model of shared care to enhance family physicians' ability to deliver quality palliative home care, particularly in a community-based setting. PROGRAM DESCRIPTION: Family physicians in 3 group practices (N = 21) in Ontario's Niagara West region collaborated with an interprofessional palliative care team (including a palliative care advanced practice nurse, a palliative medicine physician, a bereavement counselor, a psychosocial-spiritual advisor, and a case manager) in a shared-care partnership to provide comprehensive palliative home care. Key features of the program included systematic and timely identification of end-of-life patients, needs assessments, symptom and psychosocial support interventions, regular communication between team members, and coordinated care guided by outcome-based assessment in the home. In addition, educational initiatives were provided to enhance family physicians' knowledge and skills. CONCLUSION: Because of the program, participants reported improved communication, effective interprofessional collaboration, and the capacity to deliver palliative home care, 24 hours a day, 7 days a week, to end-of-life patients in the community.

The palliative care education needs of nursing home staff

Background: Palliative care is delivered in a number of settings, including nursing homes, where staff often have limited training in palliative care. Aim: We explored the level of palliative care knowledge among qualified staff delivering end-of-life care in nursing home settings, to inform the development of an appropriate education and training programme. Design: An audit of the educational needs assessment was performed using an anonymous postal questionnaire sent to 528 qualified nursing staff within 48 nursing homes. Findings: In total, 227 questionnaires were returned giving a response rate of 43%. Results indicated that less than half the sample had obtained formal training in the area of pain assessment and management and less than a quarter had obtained training in non-malignant conditions. Registered nurses in this study reported a lack of awareness of palliative care principles or national guidelines. Conclusion: Qualified nursing home staff agree that palliative care is a valuable model for care in their setting. There are clear opportunities for improvement in nursing home care, based on education and training in palliative care. Results also support the need for enhanced liaison between nursing homes and specialist palliative care services. © 2006 Elsevier Ltd. All rights reserved.

Application-based workload model for wireless sensor node computing platforms

Wireless sensor node platforms are very diversified and very constrained, particularly in power consumption. When choosing or sizing a platform for a given application, it is necessary to be able to evaluate in an early design stage the impact of those choices. Applied to the computing platform implemented on the sensor node, it requires a good understanding of the workload it must perform. Nevertheless, this workload is highly application-dependent. It depends on the data sampling frequency together with application-specific data processing and management. It is thus necessary to have a model that can represent the workload of applications with various needs and characteristics. In this paper, we propose a workload model for wireless sensor node computing platforms. This model is based on a synthetic application that models the different computational tasks that the computing platform will perform to process sensor data. It allows to model the workload of various different applications by tuning data sampling rate and processing. A case study is performed by modeling different applications and by showing how it can be used for workload characterization. © 2011 IEEE.

Towards Utilizing Model-Driven Engineering of Composite Applications for Business Performance Analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

A conceptual model and key variables for guiding supportive interventions for family caregivers of people receiving palliative care

According to the World Health Organization, the patient and family should be viewed as the "unit of care" when palliative care is required. Therefore family caregivers should receive optimal supportive care from health professionals. However, the impact of supporting a dying relative is frequently described as having negative physical and psychosocial sequalae. Furthermore, family caregivers consistently report unmet needs and there has been a dearth of rigorous supportive interventions published. In addition, comprehensive conceptual frameworks to navigate the family caregiver experience and guide intervention development are lacking. This article draws on Lazarus and Folkman's seminal work on the transactional stress and coping framework to present a conceptual model specific to family caregivers of patients receiving palliative care. A comprehensive account of key variables to aid understanding of the family caregiver experience and intervention design is provided.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Developing a best practice model for partnership practice between specialist palliative care and intellectual disability services: a mixed methods study

Background: The lack of access to good quality palliative care for people with intellectual disabilities is highlighted in the international literature. In response, more partnership practice in end-of-life care is proposed. 
Aim: This study aimed to develop a best practice model to guide and promote partnership practice between specialist palliative care and intellectual disability services. 
Design: A mixed methods research design involving two phases was used, underpinned by a conceptual model for partnership practice. 
Setting/participants: Phase 1 involved scoping end-of-life care to people with intellectual disability, based on self-completed questionnaires. In all, 47 of 66 (71.2%) services responded. In Phase 2, semi-structured interviews were undertaken with a purposive sample recruited of 30 health and social care professionals working in intellectual disability and palliative care services, who had provided palliative care to someone with intellectual disability. For both phases, data were collected from primary and secondary care in one region of the United Kingdom. 
Results: In Phase 1, examples of good practice were apparent. However, partnership practice was infrequent and unmet educational needs were identified. Four themes emerged from the interviews in Phase 2: challenges and issues in end-of-life care, sharing and learning, supporting and empowering and partnership in practice. 
Conclusion: Joint working and learning between intellectual disability and specialist palliative care were seen as key and fundamental. A framework for partnership practice between both services has been developed which could have international applicability and should be explored with other services in end-of-life care.

A Tree Augmented Classifier Based on Extreme Imprecise Dirichlet Model

In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet Model (EDM) (Cano et al., 2007) and deals conservatively with missing data in the training set, without assuming them to be missing-at-random. The EDM is an approximation of the global Imprecise Dirichlet Model (IDM), which considerably simplifies the computation of upper and lower probabilities; yet, having been only recently introduced, the quality of the provided approximation needs still to be verified. As first contribution, we extensively compare the output of the naive credal classifier (one of the few cases in which the global IDM can be exactly implemented) when learned with the EDM and the global IDM; the output of the classifier appears to be identical in the vast majority of cases, thus supporting the adoption of the EDM in real classification problems. Then, by experiments we show that TANC is more reliable than the precise TAN (learned with uniform prior), and also that it provides better performance compared to a previous (Zaffalon, 2003) TAN model based on imprecise probabilities. TANC treats missing data by considering all possible completions of the training set, but avoiding an exponential increase of the computational times; eventually, we present some preliminary results with missing data.