15,612 research outputs found
Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control
This paper provides an overview of the current state-of-the-art in selective
harvesting robots (SHRs) and their potential for addressing the challenges of
global food production. SHRs have the potential to increase productivity,
reduce labour costs, and minimise food waste by selectively harvesting only
ripe fruits and vegetables. The paper discusses the main components of SHRs,
including perception, grasping, cutting, motion planning, and control. It also
highlights the challenges in developing SHR technologies, particularly in the
areas of robot design, motion planning and control. The paper also discusses
the potential benefits of integrating AI and soft robots and data-driven
methods to enhance the performance and robustness of SHR systems. Finally, the
paper identifies several open research questions in the field and highlights
the need for further research and development efforts to advance SHR
technologies to meet the challenges of global food production. Overall, this
paper provides a starting point for researchers and practitioners interested in
developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Bayesian networks for disease diagnosis: What are they, who has used them and how?
A Bayesian network (BN) is a probabilistic graph based on Bayes' theorem,
used to show dependencies or cause-and-effect relationships between variables.
They are widely applied in diagnostic processes since they allow the
incorporation of medical knowledge to the model while expressing uncertainty in
terms of probability. This systematic review presents the state of the art in
the applications of BNs in medicine in general and in the diagnosis and
prognosis of diseases in particular. Indexed articles from the last 40 years
were included. The studies generally used the typical measures of diagnostic
and prognostic accuracy: sensitivity, specificity, accuracy, precision, and the
area under the ROC curve. Overall, we found that disease diagnosis and
prognosis based on BNs can be successfully used to model complex medical
problems that require reasoning under conditions of uncertainty.Comment: 22 pages, 5 figures, 1 table, Student PhD first pape
Environmental surveillance for Salmonella Typhi as a tool to estimate the incidence of typhoid fever in low-income populations.
Background: The World Health Organisation recommends prioritised use of recently prequalified typhoid conjugate vaccines in countries with the highest incidence of typhoid fever. However, representative typhoid surveillance data are lacking in many low-income countries because of the costs and challenges of diagnostic clinical microbiology. Environmental surveillance (ES) of Salmonella Typhi in sewage and wastewater using molecular methods may offer a low-cost alternative, but its performance in comparison with clinical surveillance has not been assessed. Methods: We developed a harmonised protocol for typhoid ES and its implementation in communities in India and Malawi where it will be compared with findings from hospital-based surveillance for typhoid fever. The protocol includes methods for ES site selection based on geospatial analysis, grab and trap sample collection at sewage and wastewater sites, and laboratory methods for sample processing, concentration and quantitative polymerase chain reaction (PCR) to detect Salmonella Typhi. The optimal locations for ES sites based on digital elevation models and mapping of sewage and river networks are described for each community and their suitability confirmed through field investigation. We will compare the prevalence and abundance of Salmonella Typhi in ES samples collected each month over a 12-month period to the incidence of blood culture confirmed typhoid cases recorded at referral hospitals serving the study areas. Conclusions: If environmental detection of Salmonella Typhi correlates with the incidence of typhoid fever estimated through clinical surveillance, typhoid ES may be a powerful and low-cost tool to estimate the local burden of typhoid fever and support the introduction of typhoid conjugate vaccines. Typhoid ES could also allow the impact of vaccination to be assessed and rapidly identify circulation of drug resistant strains
Identifying and responding to people with mild learning disabilities in the probation service
It has long been recognised that, like many other individuals, people with learningdisabilities find their way into the criminal justice system. This fact is not disputed. Whathas been disputed, however, is the extent to which those with learning disabilities arerepresented within the various agencies of the criminal justice system and the ways inwhich the criminal justice system (and society) should address this. Recently, social andlegislative confusion over the best way to deal with offenders with learning disabilities andmental health problems has meant that the waters have become even more muddied.Despite current government uncertainty concerning the best way to support offenders withlearning disabilities, the probation service is likely to continue to play a key role in thesupervision of such offenders. The three studies contained herein aim to clarify the extentto which those with learning disabilities are represented in the probation service, toexamine the effectiveness of probation for them and to explore some of the ways in whichprobation could be adapted to fit their needs.Study 1 and study 2 showed that around 10% of offenders on probation in Kent appearedto have an IQ below 75, putting them in the bottom 5% of the general population. Study 3was designed to assess some of the support needs of those with learning disabilities in theprobation service, finding that many of the materials used by the probation service arelikely to be too complex for those with learning disabilities to use effectively. To addressthis, a model for service provision is tentatively suggested. This is based on the findings ofthe three studies and a pragmatic assessment of what the probation service is likely to becapable of achieving in the near future
Consent and the Construction of the Volunteer: Institutional Settings of Experimental Research on Human Beings in Britain during the Cold War
This study challenges the primacy of consent in the history of human experimentation and argues that privileging the cultural frameworks adds nuance to our understanding of the construction of the volunteer in the period 1945 to 1970. Historians and bio-ethicists have argued that medical ethics codes have marked out the parameters of using people as subjects in medical scientific research and that the consent of the subjects was fundamental to their status as volunteers. However, the temporality of the creation of medical ethics codes means that they need to be understood within their historical context. That medical ethics codes arose from a specific historical context rather than a concerted and conscious determination to safeguard the well-being of subjects needs to be acknowledged. The British context of human experimentation is under-researched and there has been even less focus on the cultural frameworks within which experiments took place. This study demonstrates, through a close analysis of the Medical Research Council's Common Cold Research Unit (CCRU) and the government's military research facility, the Chemical Defence Experimental Establishment, Porton Down (Porton), that the `volunteer' in human experiments was a subjective entity whose identity was specific to the institution which recruited and made use of the subject. By examining representations of volunteers in the British press, the rhetoric of the government's collectivist agenda becomes evident and this fed into the institutional construction of the volunteer at the CCRU. In contrast, discussions between Porton scientists, staff members, and government officials demonstrate that the use of military personnel in secret chemical warfare experiments was far more complex. Conflicting interests of the military, the government and the scientific imperative affected how the military volunteer was perceived
Airportscape and its Effect on Airport Sense of Place and Destination Image Perception
Purpose – This study aims to validate a conceptual definition of airportscape and develop a multidimensional scale that integrates servicescape and service quality dimensions in order to comprehensively investigate airport service management. In addition, the study examines the structural relationships amongst airportscape, sense of place, airport image and destination image.
Design/methodology/approach – Covariance-based structural equation modelling has been employed. This study has collected the responses from 1,189 Thai respondents who had their experience in an international airport in the past 12 months.
Findings – Key findings reveal the set of three airportscape attributes which positively influenced the air traveller’s perceived sense of place. Four other dimensions were found to positively influence the airport image. The results also suggested the positive relationships amongst sense of place, airport image and destination image. Sense of place strongly predicted the destination image and airport image, and was found to be an important mediator of the relationship between airportscape dimension and perceived image variables
Originality/value – The study validates the airportscape scale and introduces “sense of place”, a concept that has not been objectively investigated in the airport context, and in relation to tourism. The findings provide insights to airport managers and tourism authorities by examining areas that highlight an airport’s sense of place and representation of the destination. The study also strengthens the theoretical link between airport and tourism knowledge, by showing that the airport’s sense of place can strongly influence airport image and destination image. The result ascertains that the airport can be a representative of a destination through the creation of a sense of place
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European Heart Rhythm Association (EHRA)/Heart Rhythm Society (HRS)/Asia Pacific Heart Rhythm Society (APHRS)/Latin American Heart Rhythm Society (LAHRS) Expert Consensus Statement on the state of genetic testing for cardiac diseases.
TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH
Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on people’s lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)
Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process
Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process
Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine).
In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model.
AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development.
Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models.
In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri
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