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Application of computational technology in telehealth and telesurgery
No full textWith the invention of technology, numerous businesses have been reaping benefits by integrating technology into their products and processes. Likewise, decision tree is a computation-based technology that enables decision-makers to derive a conclusion by analyzing the predictions of the output information produced by the tree. As the application of digital and computational technology in healthcare emerges with a new sense of hope, many issues and challenges may threaten the growth of these health technologies. This report presents the scope, challenges, and limitations of telehealth and telesurgical fields of healthcare where applications of decision tree models have been postulated to offer a solution to the challenges as well as recommendations for the future
Future-proofing:AI and long-term strategic vision
No full textArtificial Intelligence is one area where the tourism industry is headed and assists in contributing to structural transformation and innovation as the business model increases in importance. High-performance organisations (HPOs) have the urge to meet the global challenge by utilising AI-based tools such as ChatGPT and Bard. In this chapter, a broader convergence of trends defines the extreme positionality of AI in the global ranking of tourism sector focus, which is extended towards management and customer relations and also towards operational efficiencies. AI can be used by the stakeholders under consideration in studying: HPO features which include predictive customer decisions, and improving customers’ experiences in delivering timely, accurate and satisfying means that organisations will be able to meet their target customers. The study explains HPO features such as better managers, better so that they will better deliver AI-enhanced assistance across all disciplines in a firm including finance, operations, marketing and more. Key applications include predictive analytics for market trends, AI-driven customer interactions via voice-activated devices such as Alexa and Google Home, and greater efficiency. Also, some of the challenges are examined such as data privacy concerns and ethical issues while looking at the tool’s promising ability to offer tailored services including real-time data. Understanding both the potential and the gaps of AI, tourism organisations will be able to apply the tools more strategically to secure their business and meet the fast-changing market landscape. AI is hence setting grounds as an important advancing factor in the mobility and maintenance of competitiveness alongside sustainability in the tourism sector
Youth and the materialities of the outdoors: exploring nature connectivity through free play in hidden green spaces
No full textNature connection is considered beneficial for young people’s health and wellbeing and for developing pro-environmental behaviour, yet they display some of the lowest rates of access to nature spaces and levels of nature connectedness. Nature connection is often presented as synonymous with learning and formalised environmental education programmes represent the usual model for nature engagement interventions in youth. Evidence indicates, however, that activities which are youth led, and independently accessed may have the most impact in terms of improving nature connectivity. This paper presents the findings of a qualitative research project with young people aged between 12 and 16 years, who choose to access hidden green spaces regularly and independently, yet often without permission, on off-road mountain bikes. Their use of is predicated on accessibility, affordance for embodied engagement, and the creative practice of self-built jumps and trails and see’s young people make claims to spaces on the suburban fringe and form embodied knowledge of, and engagement with material natures. Findings provide insights into the relational materialities of young people’s self-directed connections with nature through independent access, the choices and negotiations with others that occur when accessing these spaces, and the emergence of action competence in respondents’ environmental attitudes and behaviours.</p
Carbon equality could play a positive role in mitigating the climate crisis
Get PDFHumans needs to solve the urgent problem of analyzing the severe climate crisis and studying its profound impacts on the Earth. This paper introduces the concept of “carbon equality.” By detailing the concept, manifestations, and hazards of the climate crisis, as well as explaining the connotation and practical advantages of carbon equality, and combining this with real-life cases, it demonstrates the crucial role that carbon equality could play as a core solution in responding to the climate crisis. Based on the research results, this paper puts forward practical solutions to provide new ideas for global sustainable development
Interprofessional collaboration to support people experiencing self-neglect: a realist review of research studies and safeguarding adult reviews
Get PDFSummary: Self-neglect, where adult individuals—for varying reasons—do not care for aspects of their health, wellbeing or home environment, involves significant risks and potential for harm. The importance of effective interprofessional and inter-agency collaboration in supporting people experiencing self-neglect is widely recognized, yet research and practice reviews attest to continuing challenges in collaborative working. This realist review integrates two sources of evidence, the international research literature and Safeguarding Adult Reviews (SARs) of practice cases in England, to theorize what mechanisms need to operate for effective inter-agency collaboration to support people experiencing self-neglect, and how context affects this. Searches in 2023–24 identified 41 studies and 273 SARs to inform the review, assessed on relevance and rigor. Findings: The review identified four mutually reinforcing elements that underpin collaborative working: (1) Common framework provided by policies, procedures and interfaces; (2) Mutual understanding of each other's roles and the task; (3) Shared vision of the person and situation “in the round”; (4) Management and monitoring ensuring commitment, learning and resources. Each is discussed in light of the distinctive challenges of self-neglect, and a composite example constructed from the review sources is used to illustrate. Applications: This review theorizes the elements needed for successful inter-agency and interprofessional collaboration in supporting people experiencing self-neglect. Its framework supports service leaders and researchers to consider how the mechanisms identified interact with the inter-agency context in which they unfold, and recognize the conditions needed for interventions to be effective.</p
Sensitivity and lift-off robustness of magnetic resonance circuit topologies for enhanced WPT-based ECT systems
Get PDFElectromagnetic sensors’ response is affected by lift-off variations, which are caused by nonmagnetic coating thickness, surface roughness, or sensor vibrations. These variations affect eddy current testing (ECT) sensitivity, defect quantification, and reconstruction of material properties. This article compares different magnetic resonance circuit (MRC) topologies as signal conditioning for improving the ECT system’s response to various lift-offs. The MRC is designed to operate at maximum energy, with the potential of several resonances, which lead to enhanced response for optimal and multiple feature extraction, improving signal-to-noise ratio (SNR) and increasing sensitivity to cracks. The proposed paper designs and investigates the effect of different MRC topologies connected to ECT systems to inspect a steel block with surface cracks. The performance comparison of the proposed systems provides the advantages and limitations of different MRC approaches for multiple resonance potentials, higher SNR, and response sensitivity at different lift-off distances. The advanced MRC, featuring series and shunt topologies in each transmit and receive coil, is the most immune to noise, with an SNR of 49.9 dB at a 3.4 mm lift-off using its first peak frequency feature. Its response is less crack-sensitive, with a sensitivity of up to 1.5% at 0.6 mm lift-off
Taming the radical: domesticating Forum Theatre in leadership development
Get PDFArts-based approaches to leadership development are becoming increasingly popular because of their potential to highlight the symbolic, aesthetic and sensual dimensions of organizing, thus opening up new possibilities for insights and action. However, our study shows that such interventions can also surface complex dynamics and can be co-opted in ways that diminish their more empowering potential. Our focus is on one such leadership development initiative within a UK based education institution focussing on Forum Theatre, a specific form of dramaturgy typically used to challenge structures of power and oppression. We draw on semi-structured interviews with senior level participants and facilitators to ask whether the programme was effective as a means of learning and empowering the participants. Our findings suggest that the co-option of Forum Theatre to serve organizational interests raises significant concerns when it requires a domestication of its more radical potential
Factors that influence the commissioning and implementation of integrated care for adults at risk of cardiovascular disease and mild-to-moderate mental health concerns in the UK:a systematic review protocol
Get PDFBACKGROUND: Cardiovascular disease (CVD) risk factors and mild-to-moderate mental health concerns (anxiety, depression) often co-occur and can worsen individual health outcomes, increase healthcare burden, and related costs relative to non-co/multi-morbidity. Existing evidence from both staff and service users suggests that integrating care for this population can be beneficial but challenging. Therefore, it is important that the key influences on integrated care are mapped to behavioural science frameworks so that intervention strategies in the system are actionable. This review aims to synthesise findings on which individual, organisational, social, and system-level factors influence integrated care for people experiencing co-occurring CVD risk factors and mild-to-moderate mental health concerns from the perspective of a range of health and social care professionals.METHODS: This systematic review will search MEDLINE, Embase, Emcare, PsycInfo, CINAHL, and grey literature in PsyArXiv and HMIC. Included studies will be qualitative primary research published in the English language reporting on the factors that influence the commissioning and implementation of integrated care for adults at risk of CVD and experiencing mild-to-moderate mental health concerns. This will be from the perspective of healthcare professionals, managers, commissioners, and policymakers. A thematic synthesis will identify relevant actions, actors, context, targets, and timeframes using the AACTT framework, and influences on actors' behaviour will be mapped to the Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF).DISCUSSION: Data from this review will provide insight for a larger NHIR-funded programme of work that aims to optimise Integrated Care Services (OptICS) that will develop a whole-systems map to identify appropriate targets and intervention strategies to optimise integrated care. This review will offer a novel contribution to knowledge by synthesising qualitative evidence from a range of stakeholders on the influences on commissioning and implementation of integrated care for adults with physical and mental health comorbidities, mapped to complementary implementation frameworks.SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42024554221.</p
Detection for user impersonation attacks in mobile social networks based on high-order Markov chains
Get PDFIn security defense of MSN (MSN), attackers often impersonate themselves as other users, making it difficult to detect network user attacks based on user behavior. Multi-order Markov chains can consider the front-to-back correlation of user behavior, thereby more accurately identifying disguised users. Therefore, this paper proposes a user impersonation attack detection method based on multi-order Markov chains. First, the relevance coefficient method is used to determine the order of the multi-order Markov chain, and by defining appropriate multi-order Markov chain states to capture key features in user behavior, a multi-order Markov chain is established. Then, through the multi-order Markov chain combined with Shell commands, the normal behavior profile of legitimate users is established, and based on this, the probability of occurrence of the state sequence is calculated to complete the detection of userimpersonation attacks. The experimental results show that the similarity between the results of the proposed method and the actual situation in detecting impersonation attacks is more than 97%, indicating that this method can detect MSN user impersonation attacks with high accuracy
Robust sensor fault detection in wireless sensor networks using a hybrid conditional generative adversarial networks and convolutional autoencoder
Get PDFIn the rapidly growing realm of the Internet of Things (IoT), reliance on sensor-generated data has become crucial for the operation of multiple services and systems. As essential components of these systems, wireless sensor networks (WSNs) are installed in a wide range of diverse and often harsh environments. However, these networks are highly prone to a range of faults, including software bugs, communication failures, and hardware malfunctions. Such issues can lead data to data being transmitted incorrectly, endangering the security, reliability, and economic stability of the systems they support. Addressing the challenge of sensor fault detection, we propose a novel hybrid technique to enhance the classification of sensor fault data in WSNs. Our method leverages a publicly available dataset of temperature sensor readings to generate synthetic data by using a conditional generative adversarial networks. These synthetic samples closely resemble common temperature sensor data despite the introduction of artificial sensor faults in WSNs, including hardover, drift, spike, erratic, and stuck faults. In order to capture the temporal dependencies in time-series data, we transform the sensor readings into Gramian Angular Field images (GAF), retaining the temporal structure. These GAF images are then processed using a convolutional autoencoder to extract rich feature representations, followed by a three-layer artificial neural network for the multi-class classification of sensor faults. Our proposed method not only addresses the challenges of data scarcity and imbalance but also enhances accuracy in sensor fault detection. The proposed method demonstrates high accuracy, F1-score, recall, and sensitivity, achieving 95.93%, 95.84%, 95.88%, and 95.88% respectively
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