Working across boundaries to improve health outcomes: a case study of a housing support and outreach service for homeless people living with HIV

This paper reports the findings of an evaluation of the ‘Housing Support, Outreach and Referral’ service developed to support people living with HIV who were homeless or at risk of homelessness. The service was set up as part of the Supporting People Health Pilot programme established to demonstrate the policy links between housing support services and health and social care services by encouraging the development of integrated services. The paper considers the role of housing support in improving people's health, and considers the challenges of working across housing, health and social care boundaries. The evaluation of the health pilot employed two main sources of data collection: quarterly project evaluation reports, which collected process data as well as reporting progress against aims and objectives, and semi-structured interviews with professionals from all key stakeholder groups and agencies, and with people who used services. Over the course of 15 months, 56 referrals were received of which 27 were accepted. Fifteen people received tenancy support of whom 12 were helped to access temporary accommodation. At the end of the 15 months, all of the tenancies had been maintained. In addition, 18 people registered with a general practitioner and 13 registered with an HIV clinic. Interviews with professionals emphasised the importance of the local joint working context, the involvement of the voluntary sector and the role of the support workers as factors that accounted for these outcomes. Those using services placed most emphasis on the flexibility of the support worker role. Importantly, interviews with professionals and those using services suggest that the role of support worker incorporates two dimensions – those of networker/navigator as well as advocate – and that both dimensions are important in determining the effectiveness of the service.

The challenges of joint working: lessons from the Supporting People Health Pilot evaluation

Purpose: This paper reports the findings of the evaluation of the Supporting People Health Pilots programme, which was established to demonstrate the policy links between housing support services and health and social care services by encouraging the development of integrated services. The paper highlights the challenges Method: The evaluation of the six health pilots rested on two main sources of data collection: Quarterly Project Evaluation Reports collected process data as well as reporting progress against aims and objectives. Semi-structured interviews—conducted across all key professional stakeholder groups and agencies and with people who used services—explored their experiences of these new services. Results: The ability of pilots to work across organisational boundaries to achieve their aims and objectives was associated not only with agencies sharing an understanding of the purpose of the joint venture, a history of joint working and clear and efficient governance arrangements but on two other characteristics: the extent and nature of statutory sector participation and, whether or not the service is defined by a history of voluntary sector involvement. In particular the pilots demonstrated how voluntary sector agencies appeared to be less constrained by organisational priorities and professional agenda and more able to respond flexibly to meet the complex needs of individuals. Conclusion and discussion: The pilots demonstrate that integrating services to support people with complex needs works best

A Pilot Evaluation of the Palliative Performance Scale in Long Term Care: Tips for Success

Aims: Palliative care in long-term care (LTC) homes is an area of growing concern. Little work has been done to explore innovative ways to identify and care for residents who become palliative. The purpose of this intervention study was to evaluate the implementation of the Palliative Performance Scale (PPS) in LTC. Specifically we explored staff perceptions about implementing the PPS and how it cued staff to initiate palliative care discussion with residents and family when a resident’s health declined.

Methods: This study utilized a qualitative descriptive design that included data from four separate sources: journals of three ‘champions’ who were responsible for leading the implementation of the PPS; staff evaluations of three educational training sessions; minutes from meetings; and 11 interviews from key staff who were involved in the implementation process. Data were analyzed using thematic content analysis.

Results: Staff generally felt positively about using the PPS in LTC and stated that it increased awareness of palliative care and helped identify those residents who were nearing the end of life. There were some barriers to implementing it, such as staff resistance and lack of time to complete it. The importance of having a designated ‘champion’ and effective interdisciplinary communication in addition to widespread training, were identified as successful strategies to facilitate the implementation process.

Conclusion: These study findings support the use of the PPS in LTC and offer some perspective about ways to implement it successfully. Future work is needed to evaluate the PPS in LTC using more rigorous designs.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

The determination of optimal processing conditions for PLA and PLA/CaCO3 in twin screw extrusion using DoE and multivariate analysis

Biodegradable polymers, such as PLA (Polylactide), come from renewable resources like corn starch and if disposed of correctly, degrade and become harmless to the ecosystem making them attractive alternatives to petroleum based polymers. PLA in particular is used in a variety of applications including medical devices, food packaging and waste disposal packaging. However, the industry faces challenges in melt processing of PLA due to its poor thermal stability which is influenced by processing temperatures and shearing.
Identification and control of suitable processing conditions is extremely challenging, usually relying on trial and error, and often sensitive to batch to batch variations. Off-line assessment in a lab environment can result in high scrap rates, long lead times and lengthy and expensive process development. Scrap rates are typically in the region of 25-30% for medical grade PLA costing between €2000-€5000/kg.
Additives are used to enhance material properties such as mechanical properties and may also have a therapeutic role in the case of bioresorbable medical devices, for example the release of calcium from orthopaedic implants such as fixation screws promotes healing. Additives can also reduce the costs involved as less of the polymer resin is required.
This study investigates the scope for monitoring, modelling and optimising processing conditions for twin screw extrusion of PLA and PLA w/calcium carbonate to achieve desired material properties. A DAQ system has been constructed to gather data from a bespoke measurement die comprising melt temperature; pressure drop along the length of the die; and UV-Vis spectral data which is shown to correlate to filler dispersion. Trials were carried out under a range of processing conditions using a Design of Experiments approach and samples were tested for mechanical properties, degradation rate and the release rate of calcium. Relationships between recorded process data and material characterisation results are explored.

Challenges and Opportunities in Edge Computing

Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables. This model places ever increasing demands on communication and computational infrastructure with inevitable adverse effect on Quality-of-Service and Experience. The concept of Edge Computing is predicated on moving some of this computational load towards the edge of the network to harness computational capabilities that are currently untapped in edge nodes, such as base stations, routers and switches. This position paper considers the challenges and opportunities that arise out of this new direction in the computing landscape.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Special condition wind power forecasting based on Gaussian process and similar historical data

Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.

Review of the Viability Audit process: analysis of post-primary school data

This paper provides an analysis of the post-primary school data provided in the viability audit report published in February 2012 and complements a paper already prepared with an analysis of primary school data. The Viability Audit has been led by the Education and Library Boards, working in close conjunction with CCMS. The Area Planning process was led by the Department of Education, working with the Education and Library Boards and CCMS.

Review of the Viability Audit process: analysis of primary school data

This paper provides an analysis of the primary school data provided in the viability audit report published in February 2012. The Viability Audit has been led by the Education and Library Boards, working in close conjunction with CCMS. The Area Planning process was led by the Department of Education, working with the Education and Library Boards and CCMS. Draft area planning reports, and revised reports following consultation, have been published for post primary schools; draft area planning reports for primary schools have been published and are not out for consultation. It should be noted that the draft area plan reports for primary schools used updated data available to the ELBs so some of the patterns will differ slightly from those reported in the analysis below.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Influence of process parameters on fluidised hot-melt granulation and tablet pressing of pharmaceutical powders

This study investigates the influence of process parameters on the fluidised hot melt granulation of lactose and PEG 6000, and the subsequent tablet pressing of the granules. Granulation experiments were performed to assess the effect of granulation time and binder content of the feed on the resulting granule properties such as mass mean granule size, size distribution, granule fracture stress, and granule porosity. These data were correlated using the granule growth regime model. It was found that the dominant granule growth mechanisms in this melt granulation system were nucleation followed by steady growth (PEG 10–20% w/w). However, with binder contents greater than 20% w/w, the granulation mechanism moved to the “over-wet massing” regime in which discrete granule formation could not be obtained. The granules produced in the melt fluidised bed process were subsequently pressed into tablets using an industrial tablet press. The physical properties of the tablets: fracture stress, disintegration time and friability were assessed using industry standards. These analyses indicated that particle size and binder content of the initial granules influenced the mechanical properties of the tablets. It was noted that a decrease in initial granule size resulted in an increase in the fracture stress of the tablets formed.

Client's assessment of architects' performance in building delivery process: Evidence from Nigeria

The overall intent of this research is to provide architects with information that can be used to improve their performance so as to optimally satisfy the client's requirements and achieve high-quality overall project performance in Nigerian construction industry. Architect performance criteria were identified based on literature within the domain of architect responsibilities. The assessment of architects’ performance was carried out through a questionnaire survey of clients of recently completed building projects in Nigeria. Analysis of data includes comparison of criteria using importance–performance index analysis. Factor analysis was carried out on criteria where architects are falling below average, to group and explore the latent structure of the criteria in the data. The results showed that the architect needs to focus on management skills and ability, buildability, design quality, project communication, project integration and client focus. These results would encourage architects to perform better within their full responsibilities in the building delivery process and deliver high-quality projects within Nigerian construction industry.