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An adaptive and secure routes migration model for the sustainable cloud of things
No full textSoftware-defined networks (SDN) have gained a lot of attention in recent years as a technique to develop smart systems with a help of the Internet of Things (IoT). Its powerful and centralized architecture makes a balanced contribution to the management of sustainable applications through efficient processes. These networks also systematically keep track of mobile devices and decrease the extra overheads in the communication cost. Many solutions are proposed to cope with data transferring for the critical system, however, mobile devices, on the other hand, require long-distance communication links with minimal retransmissions. Furthermore, the mobile network is highly infected by security attacks and compromised the IoT architecture for both the intermediate layers and end-users. Therefore, this paper presents an adaptive routes migration model for sustainable applications with the collaboration of SDN architecture and limits the disconnectivity time in data transporting along with efficient management of network services. Moreover, its centralized controller fetches the updated information from low-level smart devices and supervised their monitoring efficiently. The proposed model also secures the cloud of things (CoTs) from network threats and protects private data. It provides three levels of security algorithms and supports adaptive computing systems. The proposed model was tested using simulations, and the findings showed that it outperformed other existing studies in terms of packet delivery ratio by 13%, packet loss rate by 15%, transmission error by 22%, computing cost by 17%, and latency by 18%
Managing the psychosocial impact of type 1 diabetes in young people
No full textAdolescent and young people with type 1 diabetes (T1D) experience higher rates of psychological distress, periods of burnout, and feelings of being unable to cope with the daily burden of living with diabetes, compared with those who are diagnosed as adult
Accountability and accomplished teaching: Researching the chartered teacher programme in Scotland.
No full textThe Scottish chartered teacher programme (2003–2011) is an important example of a national policy designed to support the development of ‘accomplished teaching’. This paper provides an account of the emergence of the programme before discussing how the impact of such a scheme might be assessed and thus rendered accountable. The difficulties of developing valid and reliable methodologies for ensuring accountability are explored, including an account of a pilot research project and an indication of what the international literature may reveal about such aspirations. The paper concludes with a summary of four major challenges facing researchers who wish to offer insights that are of use to policy-makers and practitioners
The importance of starting well: the influence of early career support on job satisfaction and career intentions in teaching
No full textAcross the UK and internationally high rates of attrition among recently qualified teachers has focused attention on strengthening early career support. Policy attention has shifted from recruitment to the issue of sustainability. While the importance of induction is widely recognised, few studies investigate the components of early career support that new teachers deem most effective and the contextual conditions that support professional growth. This article explores the complex relationship between perceptions of pre-service preparation, school context and induction experience on the continuing learning needs, job satisfaction and career intentions of teachers at the end of their first year post-qualification. The analysis draws on 382 survey responses from teachers undertaking statutory induction in primary and secondary schools in the North West of England and Scotland in 2019. The findings suggest that the quality of initial teacher education is the strongest predictor of continuing development needs at the end of induction. High quality preparation has the potential to sustain new teachers across diverse employment contexts and the many challenges of the early career phase
Game theory-based authentication framework to secure internet of vehicles with blockchain
No full textThe Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV’s openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities’ areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework’s credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the suggested framework achieves greater security and functionality characteristics and provides lower transaction and computation overhead than many of the available solutions so far. However, these solutions never considered the prime concerns of physical cloning and side-channel attacks. However, the framework in this paper is capable of handling them along with all the other security attacks the previous work can handle. Finally, the suggested framework has been subjected to a blockchain implementation to demonstrate its efficacy with duel gaming to achieve authentication in addition to its capability of using lower burdened blockchain at the physical layer, which current blockchain-based authentication models for IoVs do not support
Length of stay in Acute Medical Admissions: Analysis from the Society for Acute Medicine Benchmarking Audit
No full textIntroduction: Medical admissions to hospital represent a diverse range of patients, from those managed on ambulatory pathways through Same Day Emergency Care (SDEC) services, to those requiring prolonged inpatient admission. An understanding of current patterns of admission through acute medicine services and patient factors associated with longer hospital admission is needed to guide service planning and improvement.Methods: Data from the Society for Acute Medicine Benchmarking Audit (SAMBA) 2021 were analysed. Patients admitted to acute medicine services during a 24-hour period on 17th June 2021 were included, with data recording patient demographics, frailty score, acuity and follow-up of outcomes after seven days.Results: 8101 unplanned medical admissions were included, from 156 hospitals. 31.6% were discharged without overnight admission; the median hospital performance was 30.1% (IQR 19.3-39.3%). 22.1% of patients remained in hospital for more than 7 days. Those remaining in hospital for more than 48 hours and for more than seven days were more likely to be aged over 70, to be frail, or to have a NEWS2 of 3 or more on arrival to hospital.Conclusion: The proportion of acute medical attendances receiving overnight admission varies between hospitals. Length of stay is impacted by patient factors and illness acuity. Strategies to reduce inpatient service pressures must ensure effective care for older patients and those with frailty
LEAP Online - Get behind the wheel
No full textPoster presentation for TIRI Conference 2022.Underpinned by the Learning Excellence Achievement Pathway framework (“LEAP”) framework, LEAP Online was launched in September 2017 as part of a renewed approach to learning development and information literacy at the University of Bolton.LEAP Online is a digital resource for promoting student learning development and information and digital literacy at the University.LEAP Online works in collaboration with other interventions across the University to improve student experience. For instance, ‘LEAP Ahead’
The use of chatbots as supportive agents for people seeking help with substance use disorder: a systematic review
No full textThe use of chatbots in healthcare is an area of study receiving increased academic interest. As the knowledge base grows, the granularity in the level of research is being refined. There is now more targeted work in specific areas of healthcare, for example, chatbots for anxiety and depression, cancer care, and pregnancy support. The aim of this paper is to systematically review and summarize the research conducted on the use of chatbots in the field of addiction, specifically the use of chatbots as supportive agents for those who suffer from a substance use disorder (SUD). A systematic search of scholarly databases using the broad search criteria of ("drug" OR "alcohol" OR "substance") AND ("addiction" OR "dependence" OR "misuse" OR "disorder" OR "abuse" OR harm*) AND ("chatbot" OR "bot" OR "conversational agent") with an additional clause applied of "publication date" ≥ January 01, 2016 AND "publication date" ≤ March 27, 2022, identified papers for screening. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to evaluate eligibility for inclusion in the study, and the Mixed Methods Appraisal Tool was employed to assess the quality of the papers. The search and screening process identified six papers for full review, two quantitative studies, three qualitative, and one mixed methods. The two quantitative papers considered an adaptation to an existing mental health chatbot to increase its scope to provide support for SUD. The mixed methods study looked at the efficacy of employing a bespoke chatbot as an intervention for harmful alcohol use. Of the qualitative studies, one used thematic analysis to gauge inputs from potential users, and service professionals, on the use of chatbots in the field of addiction, based on existing knowledge, and envisaged solutions. The remaining two were useability studies, one of which focussed on how prominent chatbots, such as Amazon Alexa, Apple Siri, and Google Assistant can support people with an SUD and the other on the possibility of delivering a chatbot for opioid-addicted patients that is driven by existing big data. The corpus of research in this field is limited, and given the quality of the papers reviewed, it is suggested more research is needed to report on the usefulness of chatbots in this area with greater confidence. Two of the papers reported a reduction in substance use in those who participated in the study. While this is a favourable finding in support of using chatbots in this field, a strong message of caution must be conveyed insofar as expert input is needed to safely leverage existing data, such as big data from social media, or that which is accessed by prevalent market leading chatbots. Without this, serious failings like those highlighted within this review mean chatbots can do more harm than good to their intended audience. [Abstract copyright: © 2022 S. Karger AG, Basel.