Showing papers by "Coventry University published in 2019"

Twenty-three unsolved problems in hydrology (UPH)–a community perspective

Abstract: This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.

Review of application of analytic hierarchy process (AHP) in construction

Abstract: The analytic hierarchy process (AHP) has gained increasing attention in construction management (CM) domain as a technique to analyse complex situations and make sound decisions. However, AHP per s...

Systematically reviewing remote e-workers’ well-being at work: a multidimensional approach

Abstract: The practice of remote e-working, which involves work conducted at anyplace, anytime, using technology, is on the increase. The aim of this systematic literature review is to gain a deeper understa...

Seven HCI Grand Challenges

Abstract: This article aims to investigate the Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled w...

Exploring young adults’ e-waste recycling behaviour using an extended theory of planned behaviour model: A cross-cultural study

Abstract: The objective of this research is to explore young adults’ e-waste recycling behaviour cross-culturally using an extended Theory of planned Behaviour (TPB) model. The results of a survey involving respondents from the two culturally-distinct emerging markets showed that the key influencing factors that influenced e-waste recycling behaviour amongst young adults were: Attitude (moderated by a Sense of Duty), Perceived Control, Subjective Norm and Individual Responsibility whereas Convenience and Consequences Awareness constructs did not have significant influence. Cross-cultural differences were also evident as stronger relationships were witnessed for Perceived Control and Subjective Norm constructs for the Chinese young adults’ intention to recycle e-waste. The reverse was found to be true for Attitude (moderated by a Sense of Duty) and Individual Responsibility constructs where stronger relationships were observed in the Indian sample. This research makes a valuable theoretical contribution as it is positioned at the intersection of cross-cultural studies, sustainability and reverse supply chain management areas. This study has practical implication at two levels: the individual actor level and the supply chain level as consumers’ intentions to recycle, underpinned by responsibility towards environment, directly impact the performance of reverse supply chains.

Interactive machine learning: experimental evidence for the human in the algorithmic loop

Abstract: Recent advances in automatic machine learning (aML) allow solving problems without any human intervention. However, sometimes a human-in-the-loop can be beneficial in solving computationally hard problems. In this paper we provide new experimental insights on how we can improve computational intelligence by complementing it with human intelligence in an interactive machine learning approach (iML). For this purpose, we used the Ant Colony Optimization (ACO) framework, because this fosters multi-agent approaches with human agents in the loop. We propose unification between the human intelligence and interaction skills and the computational power of an artificial system. The ACO framework is used on a case study solving the Traveling Salesman Problem, because of its many practical implications, e.g. in the medical domain. We used ACO due to the fact that it is one of the best algorithms used in many applied intelligence problems. For the evaluation we used gamification, i.e. we implemented a snake-like game called Traveling Snakesman with the MAX–MIN Ant System (MMAS) in the background. We extended the MMAS–Algorithm in a way, that the human can directly interact and influence the ants. This is done by “traveling” with the snake across the graph. Each time the human travels over an ant, the current pheromone value of the edge is multiplied by 5. This manipulation has an impact on the ant’s behavior (the probability that this edge is taken by the ant increases). The results show that the humans performing one tour through the graphs have a significant impact on the shortest path found by the MMAS. Consequently, our experiment demonstrates that in our case human intelligence can positively influence machine intelligence. To the best of our knowledge this is the first study of this kind.

'People Like Me Don't Get Support': Autistic Adults' Experiences of Support and Treatment for Mental Health Difficulties, Self-Injury and Suicidality.

Abstract: Autistic people are at high risk of mental health problems, self-injury and suicidality. However, no studies have explored autistic peoples’ experiences of treatment and support for these difficult...

The Acceptance and Action Questionnaire-II (AAQ-II) as a measure of experiential avoidance: Concerns over discriminant validity

Abstract: Psychological inflexibility and experiential avoidance are key constructs in the Acceptance and Commitment Therapy (ACT) model of behavior change. Wolgast (2014) questioned the construct validity of the Acceptance and Action Questionnaire-II (AAQ-II), the most used self-report instrument to assess the efficacy of ACT interventions. Wolgast suggested that the AAQ-II measured psychological distress rather than psychological inflexibility and experiential avoidance. The current study further examined the construct validity of the AAQ-II by conducting an online cross-sectional survey (n = 524), including separate measures of experiential avoidance and psychological distress. Confirmatory factor analyses indicated that items from the AAQ-II correlated more highly with measures of depression, anxiety, and stress than the Brief Experiential Avoidance Questionnaire (BEAQ). Implications include that, as broad measures of experiential avoidance, the AAQ-II and BEAQ may not measure the same construct. In terms of psychological distress, the BEAQ has greater discriminant validity than the AAQ-II, and perhaps an alternative instrument of psychological inflexibility might be needed to assess core outcomes in ACT intervention research.

Iron and liver fibrosis: Mechanistic and clinical aspects.

Abstract: Liver fibrosis is characterised by excessive deposition of extracellular matrix that interrupts normal liver functionality. It is a pathological stage in several untreated chronic liver diseases such as the iron overload syndrome hereditary haemochromatosis, viral hepatitis, alcoholic liver disease, non-alcoholic fatty liver disease, non-alcoholic steatohepatitis and diabetes. Interestingly, regardless of the aetiology, iron-loading is frequently observed in chronic liver diseases. Excess iron can feed the Fenton reaction to generate unquenchable amounts of free radicals that cause grave cellular and tissue damage and thereby contribute to fibrosis. Moreover, excess iron can induce fibrosis-promoting signals in the parenchymal and non-parenchymal cells, which accelerate disease progression and exacerbate liver pathology. Fibrosis regression is achievable following treatment, but if untreated or unsuccessful, it can progress to the irreversible cirrhotic stage leading to organ failure and hepatocellular carcinoma, where resection or transplantation remain the only curative options. Therefore, understanding the role of iron in liver fibrosis is extremely essential as it can help in formulating iron-related diagnostic, prognostic and treatment strategies. These can be implemented in isolation or in combination with the current approaches to prepone detection, and halt or decelerate fibrosis progression before it reaches the irreparable stage. Thus, this review narrates the role of iron in liver fibrosis. It examines the underlying mechanisms by which excess iron can facilitate fibrotic responses. It describes the role of iron in various clinical pathologies and lastly, highlights the significance and potential of iron-related proteins in the diagnosis and therapeutics of liver fibrosis.

Obesity and Polycystic Ovary Syndrome: Implications for Pathogenesis and Novel Management Strategies.

Abstract: Polycystic ovary syndrome (PCOS) is a common female condition typified by reproductive, hyperandrogenic, and metabolic features. Polycystic ovary syndrome is a genetic condition, exacerbated by obesity. There is a close link between obesity and PCOS based on epidemiological data, and more recently corroborated through genetic studies. There are many mechanisms mediating the effects of weight-gain and obesity on the development of PCOS. The metabolic effects of insulin resistance and steroidogenic and reproductive effects of hyperinsulinaemia are important mechanisms. Adipokine production by subcutaneous and visceral fat appears to play a part in metabolic function. However, given the complexity of PCOS pathogenesis, it is important also to consider possible effects of PCOS on further weight-gain, or at least on hampering attempts at weight-loss and maintenance through lifestyle changes. Possible mediators of these effects include changes in energy expenditure, mental ill health, or physical inactivity. In this brief review, we discuss the main mechanisms that underlie the association between obesity and PCOS, from divergent perspectives of weight-gain contributing to development of PCOS and vice versa. We also consider novel management options for women with obesity and PCOS.

Fault Detection and Isolation in Industrial Processes Using Deep Learning Approaches

Abstract: Automated fault detection is an important part of a quality control system. It has the potential to increase the overall quality of monitored products and processes. The fault detection of automotive instrument cluster systems in computer-based manufacturing assembly lines is currently limited to simple boundary checking. The analysis of more complex nonlinear signals is performed manually by trained operators, whose knowledge is used to supervise quality checking and manual detection of faults. We present a novel approach for automated Fault Detection and Isolation (FDI) based on deep learning. The approach was tested on data generated by computer-based manufacturing systems equipped with local and remote sensing devices. The results show that the approach models the different spatial/temporal patterns found in the data. The approach can successfully diagnose and locate multiple classes of faults under real-time working conditions. The proposed method is shown to outperform other established FDI methods.

Sustainable supply chain modeling and analysis: Past debate, present problems and future challenges

Abstract: For the last two decades, the topic of sustainable supply chains has evoked considerable interest from academics and practitioners. Within this context, Resources, Conservation and Recycling (RCR) and its two predecessors (Resources and Conservation, and Conservation and Recycling) have provided a platform for the exchange of technological, economic, institutional and policy aspects to help societies transition toward sustainability. The current article analyses the published research works in the RCR literature within the context of sustainable supply chain modeling by employing a content analysis literature review technique. Using the body of available literature in RCR, the articles on sustainable supply chain are analyzed in terms of the following: (1) publication per year, (2) top-cited papers across time, (3) most productive and influential authors, institutions and countries (4) supply chain related topical themes, (5) research methodologies applied, (6) illustration types and (7) industries addressed. The analysis revealed that the call for incorporating sustainability (i.e., economic, social, and environmental pillars) into supply chain operations has increased in recent years in RCR publications. Finally, the comprehensive findings and interpretations are presented, as well as the primary current trends, future challenges, directions and opportunities.

Standards and core components for cardiovascular disease prevention and rehabilitation

Abstract: In 2017, the British Association for Cardiovascular Prevention and Rehabilitation published its official document detailing standards and core components for cardiovascular prevention and rehabilitation. Building on the success of previous editions of this document (published in 2007 and 2012), the 2017 update aims to further emphasise to commissioners, clinicians, politicians and the public the importance of robust, quality indicators of cardiac rehabilitation (CR) service delivery. Otherwise, its overall aim remains consistent with the previous publications—to provide a precedent on which all effective cardiovascular prevention and rehabilitation programmes are based and a framework for use in assessment of variation in service delivery quality. In this 2017 edition, the previously described seven standards and core components have both been revised to six, with a greater focus on measurable clinical outcomes, audit and certification. The principles within the updated document underpin the six-stage pathway of care for CR, and reflect the extensive evidence base now available within the field. To help improve current services, close collaboration between commissioners and CR providers is advocated, with use of the CR costing tool in financial planning of programmes. The document specifies how quality assurance can be facilitated through local audit, and advocates routine upload of individual-level data to the annual British Heart Foundation National Audit of Cardiac Rehabilitation, and application for national certification ensuring attainment of a minimum quality standard. Although developed for the UK, these standards and core components may be applicable to other countries.

Capturing the Benefits of Industry 4.0: A Business Network Perspective

Abstract: This study uses a business network perspective to investigate the industry 4.0 context with the internet of things (IoT) as its enabling technology and product-use data as its core network resource. A three-stage qualitative methodology (interviews, focus group, Delphi-based inquiry) was used to examine the case of an emergent IoT-based business network in the UK road transport industry to examine: (i) how aspects of product use data influence the benefit opportunities the data provide to the different network actors; (ii) how capturing of the benefit opportunities in a network context is impacted by key barriers; and (iii) how network capabilities can overcome these barriers to capture benefits from product-use data. The study, thereby, contributes to an understanding of the industry 4.0 context from a resource dependency theory perspective and provides concrete recommendations for management operating in this context.

An Effective Method of Weld Defect Detection and Classification Based on Machine Vision

Abstract: In order to effectively identify and classify weld defects of thin-walled metal canisters, a weld defect detection and classification algorithm based on machine vision is proposed in this paper. With the weld defects categorized, a modified background subtraction method based on Gaussian mixture models, is proposed to extract the feature areas of the weld defects. Then, we design an algorithm for weld detection and classification according to the extracted features. Next, by using the weld images sampled by the constructed weld defect detection system on a real-world production line, the parameters of the weld defect classifiers are determined empirically. Experimental results show that the proposed methods can identify and classify the weld defects with more than 95% accuracy rate. Moreover, the weld detection results obtained in the actual production line show that the detection and classification accuracy can reach more than 99%, which means that the system enhanced with the proposed method can meet the requirements for the best real-time and continuous weld defect detection systems available nowadays.

An experimental study of residual stress and direction-dependence of fatigue crack growth behaviour in as-built and stress-relieved selective-laser-melted Ti6Al4V

Abstract: Selective-laser-melting (SLM) is a powder-bed fusion additive-manufacturing process that has the potential to deliver three-dimensional complex parts with mechanical properties comparable or superior to parts produced via traditional manufacturing using cast and wrought alloys. Concerns for metallic parts built via SLM are the process-induced residual stresses, and anisotropic mechanical properties. This paper investigates the effect of residual stresses on the fatigue crack growth rate of SLM Ti6Al4V in as-built and stress-relieved conditions. Neutron diffraction and the contour method are employed to measure residual stresses in compact-tension samples. Neutron diffraction results are in good agreement with the contour method. It was found that tensile stresses are present at the notch root and the free edge areas, and compressive stress is seen in the middle of the sample. The tensile stresses in the as-built condition resulted in a higher fatigue crack growth rate. After stress relieving by heat treatment, the tensile residual stress diminished by around 90%, resulting in decreased crack growth rate. The build direction was seen to affect the crack growth rate, although the trend was different between the as-built and stress-relieved conditions.

An Effective Hybrid Genetic Algorithm and Variable Neighborhood Search for Integrated Process Planning and Scheduling in a Packaging Machine Workshop

Abstract: Process planning and scheduling are modeled sequentially in the traditional manufacturing system. However, because of their complementarity, the increasing need to integrate them has emerged to enhance the manufacturing productivity significantly. Therefore, the integrated process planning and scheduling (IPPS) is becoming a hotspot in providing a blueprint for efficient manufacturing system. This paper proposes a novel algorithm hybridizing the genetic algorithm with strong global searching ability and variable neighborhood search with strong local searching ability for the IPPS problem. To improve the searching ability, a novel procedure, encoding method, and local search method have been designed. Effective operators have been adopted. Three experiments with totally 37 well-known benchmark problems are employed to evaluate the performance of the proposed method. Based on the results, the proposed algorithm outperforms the state-of-the-art methods and finds the new solutions (the best solutions found so far) for some problems. The proposed method has also been applied on a real-world case from a nonstandard equipment production workshop for the packaging machine of a machine tool company in China. The solution demonstrates that it can solve real-world cases very well.

The Evolution of Blockchain: A Bibliometric Study

Abstract: Blockchain as emerging technology is revolutionizing several industries, and its abundant privileges have opened up a bunch of research directions in various industries; thereby, it has acquired many interests from the research community. The rapid evolution of blockchain research papers in recent years has resulted in a need to conduct research studies that investigate a detailed analysis of the current body of knowledge in this field. To address this need, a few review papers have been published to report the latest accomplishments and challenges of blockchain technology from different perspectives. Nonetheless, there has not been any bibliometric analysis of the state of the art in blockchain where Web of Science (WoS) has been taken into consideration as a literature database. Hence, a thorough analysis of the current body of knowledge in blockchain research through a bibliometric study would be needed. In this paper, we performed a bibliometric analysis of all Blockchain’s conference papers, articles, and review papers that have been indexed byWoS from 2013 to 2018. We have analyzed those collected papers against five research questions. The results revealed some valuable insights, including yearly publications and citations trends, hottest research areas, top-ten influential papers, favorite publication venues, and most supportive funding bodies. The findings of this paper offer several implications that can be used as a guideline by both fresh and experienced researchers to establish a baseline before initiating a blockchain research project in the future.