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  • Healthcare professionals' responses to complaints: a qualitative interview study with patients, carers and healthcare professionals using the Theoretical Domains Framework and COM-B model

    Antonopoulou, Vivi; Schenk, Paulina M.; McKinlay, Alison; Chadwick, Paul; Meyer, Carly; Gibson, Beckie; Sniehotta, Falko F.; Lorencatto, Fabiana; Vlaev, Ivo; Chater, Angel M.; et al. (Wiley, 2024-12-08)
    Patient complaints in healthcare settings can provide feedback for monitoring and improving healthcare services. Behavioural responses to complaints (e.g., talking or apologising to a patient) can influence the trajectory of a complaint for instance, whether a complaint is escalated or not. We aimed to explore healthcare professional (HCP) and service user (patient and carer) views on complaints' management and the perceived factors influencing responses to complaints within a healthcare setting by applying behavioural frameworks. A qualitative study was conducted using online or phone-based interviews with eleven HCPs and seven patients or carers. All participants (N = 18) had experience responding to or submitting a formal complaint in secondary and tertiary public healthcare settings in the United Kingdom. The interviews were structured using the Capability-Opportunity-Motivation-Behaviour (COM-B) Model. We analysed the transcripts using inductive thematic analysis. Then, themes were deductively mapped onto the COM-B Model and the more granular Theoretical Domains Framework (TDF). Ten themes were generated from the analysis representing the influences on HCPs' responses to complaints from HCP and patient/carer perspectives. This included (with TDF/COM-B in brackets): 'Knowledge of complaint procedure' (Knowledge/Capability), 'Training and level of skill in complaints handling' (Skills/Capability), 'Regulation of emotions associated with complaints' (Behavioural regulation/Capability), 'Confidence in handling complaints' (Beliefs about capabilities/Motivation), 'Beliefs about the value of complaints' (Beliefs about consequences/Motivation) and 'Organisational culture regarding complaints' (Social influences/Opportunity). Staff highlighted strong support systems and open discussions as part of positive organisational cultures regarding complaints (Social influences/Opportunity), and a lack of certainty around when to treat issues raised by patients as a formal complaint or informal feedback (Knowledge/Capability). Our study findings highlight the importance of strong support systems and organisational openness to patient feedback. These findings can be used to design targeted interventions to support more effective responses and enhance patient-centred approaches to complaints management in healthcare settings. Patient and public involvement (PPI) was integral in this research. The NIHR PRU in Behavioural and Social Sciences had a dedicated PPI strategy group consisting of six external representatives from the patient and public community (Newcastle University, 2024). These six PPI members actively participated in shaping the research by reviewing and providing feedback on all questionnaire items before the data collection. They were actively involved in supporting participant recruitment by advertising this study on their PPI platform, The VoiceR,1 and through their online social networks. During the analysis stages of the research, preliminary findings were discussed with the PPI group to support 'sense checking' and interpretation of the results.
  • Smart City lane detection for autonomous vehicle

    Dawam, Edward Swarlat; Feng, Xiaohua; University of Bedfordshire (IEEE, 2020-11-11)
    One of AI branch, Computer Vision-based recognition systems is necessary for security in Autonomous Vehicles (AVs). Traffic sign recognition systems are popularly used in AVs because it ensures driver safety and decrease vehicles accidents on roads. However, the inability of AVs to accurately detect road signs and pedestrian behaviour has led to road crashes and even death in recent times. Additionally, as cities become smarter, the traditional traffic signs dataset will change considerably, as theGoogle, 2020se vehicles and city infrastructure introduce modern facilities into their operation. In this paper, we introduce a computer vision based road surface marking recognition system to serve as an added layer of data source from which AVs will make decisions. We trained our detector using YOLOv3 running in the cloud to detect 25 classes of Road surface markings using over 25,000 images. The results of our experiment demonstrate a robust performance in terms of the accuracy and speed of detection. The results of which will consolidate the traffic sign recognition system, thereby ensuring more reliability and safety in AVs decision making. New algorithm using Deep Learning technology in Artificial intelligence (AI) application is implemented and tested successfully.
  • Exergy analysis of isochoric and isobaric Adiabatic Compressed Air Energy Storage

    Barbour, Edward R.; Oliveira Junior, Maury Martins; Cardenas, Bruno; Pottie, Daniel L.F.; ; Loughborough University; University of Birmingham; University of Nottingham; University of Bedfordshire (IET, 2024-12-06)
    Adiabatic Compressed Air Energy Storage (ACAES) is an energy storage technology that has the potential to play an important role in the transition to a predominantly renewables-driven net-zero energy system. However, it has not yet achieved the performance necessary to be widely deployed. In this paper, we undertake an exergy analysis of isobaric and isochoric ACAES systems, tracking lost work through the components and exploring the influences of different design choices. We model three different configurations: (1) 3 compression and 3 expansion stages; (2) 4 compression and 2 expansion stages; (3) 2 compression and 4 expansion stages. Our results illustrate that isobaric systems are likely to have higher round trip efficiency and significantly higher energy density, at the cost of achieving isobaric storage. Exergy analysis reveals that most of the losses arise in the compressors, compressor aftercoolers and expanders. Losses in aftercoolers are exaggerated when compressors operate with high pressure ratios, emphasizing that choice of TES is a key system variable. With pressurised water as the coolant and TES fluid, it seems likely that the best system will have more compression than expansion stages. Increasing the number of compression stages decreases the off-design penalty when the system is isochoric.
  • AI and forensics security with cloud, networks impact on education

    Feng, Xiaohua; University of Bedfordshire (2024-09-09)
    Large Language Models (LLMs) have demonstrated significant potential to revolutionize higher education, prompting a need for strategic guidance on leveraging their benefits while addressing associated challenges [1]. This paper reaches into the critical role of cloud computing in enabling the smooth integration and sustainable transformation of Higher Education Institutions (HEIs) through LLMs. By examining the mutually beneficial relationship between LLMs and cloud technologies, this paper highlights how the cloud empowers HEIs to utilize the full potential of LLMs, overcoming challenges related to scalability, accessibility, and cost-effectiveness. The paper presents a comprehensive framework for the strategic integration of LLMs and cloud computing within HEIs, addressing key considerations such as data privacy, security, interoperability, and ethical governance. Through a systematic review of case studies and best practices, the paper offers actionable insights and recommendations for HEIs to navigate the
  • SecureCloud: a cross-platform encrypted file sharing solution with forensic imaging capability

    Muthupandian, Arunpaul; Artemi, Mahmoud; Feng, Xiaohua; Conrad, Marc; University of Bedfordshire (Springer, 2024-12-06)
    In this age of AI dominating the digital panorama, the way we deal with, and procedure records has grown to be a sensitive circumstance. As individuals’ percentage sensitive non-public information and files over the net, a veil of uncertainty shrouds the adventure of those files, leaving us brooding about how inclined the device is to ability misused with the aid of malicious actors. This uncertainty extends to the protection of facts saved on our devices and how securely online provider companies manipulate our documents. Amid these issues, enterprise giants like Apple and Microsoft have taken proactive steps to deal with this issue. Notably, Apple, a brand recognised for its trustworthiness and successful products, has launched the latest marketing campaign squarely centred on improving privacy. Acknowledging the evolving panorama, they've committed to bolstering the security features of their gadgets. Yet, this begs the question of how different platforms are responding to privacy and security-demanding si

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