Dr Mark Wallis

This paper discusses the needs of medical researchers working in the area of patient-centred medicine, in particular their use of survey data in measuring patient opinions, needs, perceived quality of care received, and priorities of health service interventions. Until quite recently, collection of survey data has been either paper-based, or achieved using computer software that largely duplicated paper-based processes with limited additional functionality. The authors investigate the use of web-based technology to support collection of such data from patients, including experiences and observations on enhanced/additional functionality made possible by its adoption. A novel software design termed QuON is presented, together with examples of its capabilities and uses in current research projects. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

Nowadays Model-Driven Engineering (MDE) is gaining more popularity due to high-level development leading to a faster generation of executable code, which reduces manual intervention. Verification is crucial at different levels of model-based development. Model-based development, along with formal verification process, assures the developed model satisfies software requirements described in formal specifications. Owing the inadequate knowledge of formal methods (complex mathematical theory), software developers are not adopting formal methods during software development. There are several approaches in the literature available to transform MDE models into formal models directly for formal verification, and these approaches require an additional input of formal specifications to verification tools for formal verification. But these methods have not addressed the problem of formal specifications at the model level. In this paper, we design a modelling framework using modelling techniques, which allows specifying formal properties at the model level, automatically extracting formal specifications and formal models from developed application models, which are used for formal verification. The proposed method allows full automation and reduces the time for formal verification process during the development life-cycle. Furthermore, the method reduces the complexity of learning formal specification notations (specifications specified at the model level are automatically converted into formal specifications), which are required to input verification tools for formal verification.

The Fourth Industrial Revolution (Industry 4.0), with the help of cyber-physical systems (CPS), the Internet of Things (IoT), and Artificial Intelligence (AI), is transforming the way industrial setups are designed. Recent literature has provided insight about large firms gaining benefits from Industry 4.0, but many of these benefits do not translate to SMEs. The agent-oriented smart factory (AOSF) framework provides a solution to help bridge the gap between Industry 4.0 frameworks and SME-oriented setups by providing a general and high-level supply chain (SC) framework and an associated agent-oriented storage and retrieval (AOSR)-based warehouse management strategy. This paper presents the extended heuristics of the AOSR algorithm and details how it improves the performance efficiency in an SME-oriented warehouse. A detailed discussion on the thorough validation via scenario-based experimentation and test cases explain how AOSR yielded 60¿148% improved performance metrics in certain key areas of a warehouse.

Nowadays, automation can be assisted by using programmable logic controllers (PLCs). PLCs are typically programmed with IEC 61131-3 languages to automate and implement the applications. PLC program classification plays an important role in the identification of similar functionality, which can be considered as software clones. In this paper, we present work to identify clones in IEC 61131-3 languages, using an approach based on four different perspectives: (a) clone prediction: Filtering based on heuristics; (b) structural analysis: Detect syntactic code clones; (c) semantic analysis: Analysis of output variable dependency and input variable impact usage to detect semantic clones; (d) variable interval analysis: Analysis of each program variable intervals to examine and detect clones. Our approach is a combination of structural, semantic and data interval based analysis. As a result, our approach is feasible and yields good results in detecting clones on our test data.

Background Stroke events often result in long-term negative health outcomes. People who experience a first stroke event are 30%-40% more likely to experience a second stroke event within 5 years. An online secondary prevention programme for stroke survivors may help stroke survivors improve their health risk behaviours and lower their risk of a second stroke. Objectives This paper describes the development and early iteration testing of the usability and acceptability of an online secondary prevention programme for stroke survivors (Prevent 2nd Stroke, P2S). P2S aims to address six modifiable health risk behaviours of stroke: blood pressure, physical activity, nutrition, depression and anxiety, smoking, and alcohol consumption. Methods P2S was developed as an eight-module online secondary prevention programme for stroke survivors. Modelled on the DoTTI (Design and development, Testing early iterations, Testing for effectiveness, Integration and implementation) framework for the development of online programmes, the following stages were followed during programme development: (1) content development and design; and (2) testing early iteration. The programme was pilot-tested with 15 stroke survivors who assessed P2S on usability and acceptability. Results In stage 1, experts provided input for the content development of P2S. In stage 2, 15 stroke survivors were recruited for usability testing of P2S. They reported high ratings of usability and acceptability of P2S. P2S was generally regarded as easy to use' and relevant to stroke survivors'. Participants also largely agreed that it was appropriate to offer lifestyle advice to stroke survivors through the internet. Conclusions The study found that an online secondary prevention programme was acceptable and easily usable by stroke survivors. The next step is to conduct a randomised controlled trial to assess the effectiveness of the programme regarding behaviour change and determine the cost-effectiveness of the intervention.

Background Tobacco smoking can have negative health outcomes on recovery from surgery. Although it is recommended best practice to provide patients with advice to quit and follow-up support, provision of postdischarge support is rare. Developing an online smoking cessation program may help address this gap. Objectives This paper describes the development and pretesting of an online smoking cessation program (smoke-free recovery, SFR) tailored to the orthopaedic trauma population for use while in hospital and post-discharge. Methods Drawing on the DoTTI framework for developing an online program, the following steps were followed for program development: (1) design and development; (2) testing early iteration; (3) testing for effectiveness and (4) integration and implementation. This article describes the first two stages of SFR program development. Results SFR is a 10-module online smoking cessation program tailored for patients with orthopaedic trauma. Of the participants who completed testing early iterations, none reported any difficulties orientating themselves to the program or understanding program content. The main themes were that it was 'helpful', provision of 'help to quit' was low and SFR increased thoughts of 'staying quit post discharge'. Conclusions This study found that a theory and evidence-based approach as the basis for an online smoking cessation program for patients with orthopaedic trauma was acceptable to users. A randomised controlled trial will be conducted to examine whether the online smoking cessation program is effective in increasing smoking cessation and how it can be integrated and implemented into hospital practice (stages three and four of the DoTTI framework).