A conceptual model framework for XAI requirement elicitation of application domain system

The use of data analytics and Machine Learning (ML) branches of AI for predictive and analytic knowledge retrieval has surged significantly in various industries (e.g., health, finance, business, and manufacturing). However, the acceptance of AI has been hindered by opaque models that lack transparency. Explainability in AI (XAI) has gained significant prominence owing to its focus on introducing avenues of accountability in AI. XAI acknowledges the importance of human factors and strives to incorporate them into the design process, recognising that the cognitive effort involved in understanding explanations is a key aspect. Mental Models play a crucial role in the XAI evaluative premise, but their current utility is limited. By intentionally designing explanations that align with users’ mental models, their experiences can be significantly enhanced, leading to improved understanding, satisfaction, trust, and performance. This study proposes using Mental Models to elicit explainability requirements and to develop an Ontology-Driven Conceptual Model to facilitate the learning process for a better understanding of explanations.</p

Examining the effect of external force applied to the pelvic region on postpartum women's static stability [Abstract]

Examining the effect of external force applied to the pelvic region on postpartum women's static stability [Abstract]</p

Examining the effect of external force applied to the pelvic region on postpartum women's static stability [Abstract]

Examining the effect of external force applied to the pelvic region on postpartum women's static stability [Abstract]</p

Investigating the physical activity habits and apparel choices of perinatal women

Background: This study investigates the physical activity and apparel choices of perinatal women. The perinatal period involves significant anatomical, physiological, and biomechanical changes as the body prepares to carry and deliver a child, and the recovery process which follows. Despite the recognised benefits of physical activity returning to physical activity postpartum can be difficult. Methods: 106 postpartum women completed an online questionnaire, exploring women’s physical activity habits before, during, and after pregnancy, along with their use of activewear/compression aids during this time. Statistical analyses, including chi-squared tests, investigated the relationship between initiation of physical activity postpartum (by and after 12 weeks) and: delivery method (vaginal, c-section, assisted), perineal trauma, activewear purchase, and pre-pregnancy activity level. Thematic analysis was applied to identify themes from participant’s answers.Results: A vaginal delivery correlated with a higher likelihood of resuming physical activity within 12 weeks postpartum. Moreover, a high level of activity pre-pregnancy was associated with a high level of physical activity postpartum. The study identified key reasons for the cessation of physical activity during pregnancy including, discomfort, tiredness, and misinformation. Barriers hindering the return to physical activity postpartum included discomfort, misinformation, and time constraints. Few participants used compression aids in the postpartum period, with the majority leveraging them to alleviate pain (71%). Conclusions: This study highlights a crucial gap in utilisation of compression garmentsduring the postpartum period. Understanding these factors is pivotal in enhancing support for postpartum women in their pursuit of resuming physical activity.</p

Electric bicycles, next generation low carbon transport systems: A survey

Electrical assisted bicycles (e-Bikes) represent an emerging sustainable mode of transport for future smart cities. Several designs issues impact policy in several countries such as the UK, Europe and the USA. As e-bike usage continues to grow, so too will the need for further research, in order to provide the necessary data to inform industrialists what cycling features matters for a wider, diverse and sustainable adoption of this mode of transport. This investigation discusses results from a survey on end-user preferences for future e-Bikes that will be developed in the coming years. User preferences related to safety and convenience were defined using market reviews and responses gathered from 638 potential users mainly from Europe and North America. Data were analysed to rank the importance of desired functionality to improve the uptake of cycling within urban environments. In general, the results indicate that safety and convenience features were equally valued across the whole sample size. ‘Gradient Climb Assist’ and ‘Break Lights & Indicators’ were respectively the most preferred convenience and safety feature. This survey showed how respondents expressed a desire for a more intelligent, secure and adaptive e-Bikes

Personalised controller strategies for next generation intelligent adaptive electric bicycles

Air pollution and increasing traffic congestion means the current way of navigating through a city needs to be rethought. One of the possible solutions is to move away from internal combustion engines and embrace electric and hybrid vehicles. Electric Bicycles can offer an alternative to traditional modes of transport and support an environmentally friendly way to navigate an urban environment, with the benefit of encouraging physical exercise. There are still several issues that constrain a large-scale acceptance of Electric Bicycles, including the need for personalised controller strategies and the energy efficiencies. Current strategies do not include any analysis of rider’s capabilities, physiological factors or pedalling techniques. The research outlined in this paper involved 30 participants that volunteered to take part in an Incremental Sub-Maximal Ramp Test with the aim of understanding and quantifying pedalling characteristics and demonstrating that a better motor controller strategy tailored toward individual requirements is possible. Gender and Cycling Experience were the most prominent factors that differentiate the capabilities of the population. Three novel controller techniques (i.e. Fixed Percentage, Torque Filling and Real-Time Power mapping) are analysed and presented as innovative methods for next generation personalised controller strategies for Electric Bicycles

The potential of industry 4.0 cyber physical system to improve quality assurance: An automotive case study for wash monitoring of returnable transit items

The aim of the research outlined in this paper is to demonstrate the implementation of a Cyber-Physical System (CPS) within the Automotive Industry for the monitoring and control of Returnable Transit Items (RTIs) toward improved quality assurance and process compliance. The socio-technical issues encountered during the realworld implementation are discussed to inform future design Automotive RTI’s are utilised in the transportation of both components and subsequently assembled products at the beginning and end of life stages. The implemented system utilises passive Ultra-High Frequency (UHF) Radio Frequency IDentification (RFID) tags for the identification of metal RTIs via associated plastic separators, whilst a distributed network of RFID portals was integrated within the RTI working environment to capture and characterise their movements. The requirements, design process and resulting architecture are presented alongside the results and lessons learnt from an implementation within the automotive industry. Through the integration of business processes, analytics and tacit domain knowledge, a real-time model of the state of RTIs was developed to support decision making by a range of stakeholders. This research contributes to the knowledge of CPSs requirements identification, design, deployment and the challenges faced within real world asset monitoring and traceability within the automotive industry. Areas for future research to support the next generation of RTI traceability, monitoring and control systems are presented