Now showing items 1-20 of 10503

    • Which product description phrases affect sales forecasting? An explainable AI framework by integrating WaveNet neural network models with multiple regression

      Chen, S.; Ke, S.; Han, S.; Gupta, S.; Sivarajah, Uthayasankar (2023)
      The rapid rise of many e-commerce platforms for individual consumers has generated a large amount of text-based data, and thus researchers have begun to experiment with text mining techniques to extract information from the large amount of textual data to assist in sales forecasting. The existing literature focuses textual data on product reviews; however, consumer reviews are not something that companies can directly control, here we argue that textual product descriptions are also important determinants of consumer choice. We construct an artificial intelligence (AI) framework that combines text mining, WaveNet neural networks, multiple regression, and SHAP model to explain the impact of product descriptions on sales forecasting. Using data from nearly 200,000 sales records obtained from a cross-border e-commerce firm, an empirical study showed that the product description presented to customers can influence sales forecasting, and about 44% of the key phrases greatly affect sales forecasting results, the sales forecasting models that added key product description phrases had improved forecasting accuracy. This paper provides explainable results of sales forecasting, which can provide guidance for firms to design product descriptions with reference to the market demand reflected by these phrases, and adding these phrases to product descriptions can help win more customers.
    • Evaluating 'living well' with mild-to-moderate dementia: Co-production and validation of the IDEAL My Life Questionnaire

      Clare, L.; Pentecost, C.; Collins, R.; Martyr, A.; Litherland, R.; Morris, R.G.; Quinn, Catherine; Gamble, L.D.; Sabatini, S.; Victor, C. (2023)
      We aimed to co-produce and validate an accessible, evidence-based questionnaire measuring 'living well' with dementia that reflects the experience of people with mild-to-moderate dementia. Nine people with dementia formed a co-production group. An initial series of workshops generated the format of the questionnaire and a longlist of items. Preliminary testing with 53 IDEAL cohort participants yielded a shortlist of items. These were tested with 136 IDEAL cohort participants during a further round of data collection and assessed for reliability and validity. The co-production group contributed to decisions throughout and agreed the final version. An initial list of 230 items was reduced to 41 for initial testing, 12 for full testing, and 10 for the final version. The 10-item version had good internal consistency and test-retest reliability, and a single factor structure. Analyses showed significant large positive correlations with scores on measures of quality of life, well-being, and satisfaction with life, and expected patterns of association including a significant large negative association with depression scores and no association with cognitive test scores. The co-produced My Life Questionnaire is an accessible and valid measure of 'living well' with dementia suitable for use in a range of contexts.
    • Navigating the COVID-19 pandemic two years on: experiences of carers of people with dementia from the British IDEAL cohort

      Collins, R.; Dawson, E.; Pentecost, C.; Stapley, S.; Quinn, Catherine; Charlwood, C.; Allan, L.; Victor, C.; Clare, L. (2023)
      We explored carers experiences during the COVID-19 pandemic in England to identify long-term impacts and implications, and to suggest future support for caregivers. Data were collected during COVID-19 rapid response studies (IDEAL-CDI; INCLUDE) from carers participating in a British longitudinal cohort study (IDEAL). Semi-structured interview data were compared to their accounts from previous interviews conducted during the first 18 months of the pandemic. There was indication of some return to pre-pandemic lifestyles but without appropriate support carers risked reaching crisis point. Evidence points to a need for assessment and management of support needs to ensure well-being and sustainable dementia caregiving.
    • Caring beyond capacity’ during the COVID-19 pandemic: resilience and family carers of people with dementia from the IDEAL cohort

      Stapley, S.; Pentecost, C.; Collins, R.; Quinn, Catherine; Dawson, E.; Thom, J.M.; Clare, L. (2023)
      Family carers of people with dementia have reported increased caring demands during the COVID-19 pandemic. The aim of this qualitative study was to explore seven family carers’ accounts of dementia caregiving one year into the COVID-19 pandemic in England in relation to carer resilience. Themes described the complex challenges of caring during the pandemic, with interviewees burned out and ‘caring beyond capacity’ due to unmet needs within the caring role, therein highlighting the limitations of building individual resilience only. Timely practical support for carers is essential to protect their well-being and to ward against the potential consequences of carer burnout.
    • Provision of outdoor nature-based activity for older people with cognitive impairment: A scoping review from the ENLIVEN project

      Collins, R.; Owen, S.; Opdebeeck, C.; Ledingham, K.; Connell, J.; Quinn, Catherine; Page, S.; Clare, L. (2023-07)
      The health and well-being benefits of outdoor nature-based activity are increasingly recognised, but older people with cognitive impairment face significant barriers to access. The ENLIVEN project aims to promote access by gathering evidence and coproducing guidance for activity providers. As part of this project, we conducted a scoping review to characterise the types of outdoor nature-based activity for older people with dementia and other forms of cognitive impairment for which research evidence is available and the range of outcomes is examined. The protocol is available online. We systematically searched relevant databases from 1st January, 2009, to 20th October, 2022, and screened articles against the following criteria: participants were older people aged 65 and above with cognitive impairment arising from dementia or another health condition. The study described the formal provision of outdoor nature-based activity away from the person’s usual place of residence, and at least one outcome of participation in the activity was evaluated. Twenty-eight articles met inclusion criteria, all focused on people with dementia. In most cases, participants were attending day care or living in residential care, and sample sizes ranged from 4 to 136. Activities fell into three groups: green day care (fifteen articles), equine-assisted interventions (seven articles), and community nature-based activities (six articles). Outcome domains explored were connection with nature, activity engagement, impacts on clinical symptoms, functional ability, physical, psychological and social health,, and quality of life. Outdoor nature-based activity can be offered as an opportunity for meaningful occupation to enrich daily life, as a framework for day care provision, or as an intervention to address clinical needs. The evidence base for green day care is relatively established, but the potential for addressing specific clinical needs remains to be explored. The paucity of evidence regarding community provision, especially for those not attending formal care settings, suggests the need for effective knowledge exchange to stimulate initiatives in this area.
    • A fuzzy data-driven reliability analysis for risk assessment and decision making using Temporal Fault Trees

      Kabir, Sohag (Elsevier, 2023-09)
      Fuzzy data-driven reliability analysis has been used in different safety-critical domains for risk assessment and decision-making where precise failure data is non-existent. Expert judgements and fuzzy set theory have been combined with different variants of fault trees as part of fuzzy data-driven reliability analysis studies. In such fuzzy fault tree analyses, different people represented failure data using different membership functions for the fuzzy set, and different parameters were set differently in the expert opinion elicitation process. Due to the availability of a wide variety of options, it is possible to obtain different outcomes when choosing one option over another. This article performed an analysis in the context of fuzzy data-based temporal fault tree analysis to investigate the effect of choosing different membership functions on the estimated system reliability and criticality ranking of different failure events. Moreover, the effect of using different values for the relaxation factor, a parameter set during the expert elicitation process, was studied on the system reliability and criticality evaluation. The experiments on the fuel distribution system case study show system reliability did not vary when triangular and trapezoidal fuzzy numbers were used with the same upper and lower bounds. However, it was seen that the criticality rankings of a couple of events were changed due to choosing different membership functions and different values of relaxation factor
    • Reframing physically active learning as movement-centred pedagogy: a European priority action framework

      Chalkley, Anna; Mandelid, M.B.; Singh, A.; Resaland, G.K.; Daly-Smith, Andrew (2023-08)
      Physically active learning (PAL) has emerged as a promising way of eliciting health and education-based outcomes for pupils. Concurrently, research suggests large variability in how PAL is perceived, operationalized, and prioritized in practice across Europe. Therefore, this study aimed to co-develop a framework for action to support the adoption and implementation of PAL. Adopting a design thinking approach, 40 international stakeholders representing 13 countries engaged in an idea generation workshop during a two-day PAL international conference. Participants included professionals from research (n = 20), practice (n = 4) and policy (n = 1) or a combination (n = 15). Their experience with PAL ranged from none to 19 years (with an average of 3.9 years). Participants were allocated into one of six heterogeneous and multidisciplinary groups and led through interactive tasks to identify: the landscape for PAL across Europe, barriers to the adoption and implementation of PAL, and key objectives for research, policy and practice to improve the adoption and implementation of PAL. All discussions were audio recorded and prioritized objectives were transcribed verbatim and analysed using inductive qualitative content analysis. Five interlinked and mutually reinforcing themes were identified: (1) Integration of the health and education paradigms (2) Coherent national policy and decision making (3) Building confident and competent teachers (4) Adopting a whole school approach for PAL (5) Strengthening the evidence base for PAL. The priority action framework identifies five key areas for action to facilitate PAL adoption and implementation across Europe. Central to the success of border uptake of PAL is the integration of the health and education paradigms. To achieve this aim, reframing PAL as movement-centered pedagogy would provide a more holistic and inclusive perspective.
    • Perfection, hybridity or shutting up? A cross-country study of how language ideologies shape participation in international business

      Barner-Rasmussen, W.; Gaibrois, C.; Wilmot, Natalie V. (2023)
      Employees’ participation in professional international business (IB) communication has important consequences for knowledge transfer and processing, a crucial function for multinational enterprises (MNEs). Research suggests that participation is shaped by language, but prior research has focused on firm-internal language dynamics, meaning that less is known about the influence of external context. We help redress this balance by drawing on the sociolinguistic concept of “language ideologies”. Language ideologies, or shared sets of beliefs about language(s) amongst social groups, are societal-level phenomena that employees bring with them to work. As such, they are part of the external social, political and historical context of IB activities. Our analysis of 82 interviews in three countries indicates that some language ideologies block participation and create friction, while others support participation. Implications for the conceptual understanding of language in IB and the management of internationally active firms are discussed.
    • Characterization and life cycle assessment of geopolymer mortars with masonry units and recycled concrete aggregates assorted from construction and demolition waste

      Kul, A.; Ozel, B.F.; Ozcelikci, E.; Gunal, M.F.; Ulugol, H.; Yildirim, Gurkan; Sahmaran, M. (2023-11)
      Developing a fast, cost-effective, eco-friendly solution to recycle large amounts of construction and demolition waste (CDW) generated from construction industry-related activities and natural disasters is crucial. The present investigation aims to offer a solution for repurposing CDW into building materials suitable for accelerated construction and housing in developing countries and disaster-prone areas. Feasibility of recycled concrete aggregate (RCA) inclusion in geopolymer mortars constituted entirely from CDW (masonry elements) was investigated via an environmental impact-oriented approach by addressing the composition related key parameters. Mechanical performance was evaluated through compressive strength tests, and scanning electron microscope (SEM) imaging with line mapping analyses were carried out to monitor the interfacial transition zone (ITZ) properties. To investigate the environmental impacts of the geopolymer mortars and highlight the advantages over Portland cement-based mortars, a cradle-to-gate life cycle assessment (LCA) was performed. Findings revealed that roof tile (RT)-based geopolymer mortars mainly exhibited better strength performance due to their finer particle size. Mixtures activated with 15 M NaOH solution and cured at 105 °C achieved an average compressive strength above 55 MPa. RCA size was the most influential parameter on compressive strength, and a smaller maximum RCA size significantly increased the compressive strength. Microstructural analyses showed that the ITZ around smaller RCAs was relatively thinner, resulting in better compressive strength results. LCA proved that CDW-based geopolymer mortars provide the same compressive strength with around 60% less CO2 emissions and similar energy consumption compared to Portland cement-based mortars.
    • The benefits and complexities of integrating mixed method findings using the Pillar Integration Process: A workplace health intervention case study

      Hall, Jennifer; Mansfield, L. (2023)
      The Pillar Integration Process was developed to facilitate integration of mixed method data, but there is limited historical application of this approach in complex intervention evaluation. To test the applicability of the technique, this paper presents two case studies examining the efficacy of a workplace intervention. The research included a pilot RCT and process evaluation. The case studies illustrate the benefits of applying the Pillar Integration Process to elicit a comprehensive understanding of intervention efficacy and to design better interventions. This paper contributes to the mixed methods research by advancing the technique through considering inherent philosophical assumptions, and evidencing the value of integrating methods within, as well as across, “qualitative” and “quantitative” categories.
    • A data collection programme for improving healthcare in UK human spaceflight ventures

      Cope, H.; Deane, C.S.; Szewczyk, N.J.; Etheridge, T.; Williams, P.M.; Willis, Craig R.G. (2023-06)
      Over the next decade the number of humans venturing beyond Earth is projected to rapidly increase in both quantity and diversity. Humans will regularly fly to the International Space Station until it is decommissioned by 2031, will return to the Moon by 2025 via the Artemis programme, and will fly to space via commercial ventures. Spaceflight presents a hazardous environment for human health. To understand spaceflight-associated health risks further and to increase safety via advanced healthcare approaches, including personalised medicine, more data must be collected. Importantly, this data must be derived from a diverse cohort of participants and a range of mission formats. We propose that the UK should start to consider all citizens venturing into space as potential participants from which health and biological data could be consensually collected. Importantly, we believe that this routine data collection programme should adopt a similar strategy to the UK National Health Service and the UK Biobank, by including "omics" data for scientific and healthcare purposes. We consider how such a world-leading programme, kick-started via a pilot study, might be realised through appropriate policy design, including which measures to collect, when to collect them, and unique ethical considerations pertaining to the spacefaring population.
    • Mitochondrial sulfide promotes life span and health span through distinct mechanisms in developing versus adult treated Caenorhabditis elegans

      Vintila, A.R.; Slade, L.; Cooke, M.; Willis, Craig R.G.; Torregrossa, R.; Rahman, M.; Anupom, T.; Vanapalli, S.A.; Gaffney, Christopher F.; Gharahdaghi, N.; et al. (2023-08)
      Living longer without simultaneously extending years spent in good health ("health span") is an increasing societal burden, demanding new therapeutic strategies. Hydrogen sulfide (H2S) can correct disease-related mitochondrial metabolic deficiencies, and supraphysiological H2S concentrations can pro health span. However, the efficacy and mechanisms of mitochondrion-targeted sulfide delivery molecules (mtH2S) administered across the adult life course are unknown. Using a Caenorhabditis elegans aging model, we compared untargeted H2S (NaGYY4137, 100 µM and 100 nM) and mtH2S (AP39, 100 nM) donor effects on life span, neuromuscular health span, and mitochondrial integrity. H2S donors were administered from birth or in young/middle-aged animals (day 0, 2, or 4 postadulthood). RNAi pharmacogenetic interventions and transcriptomics/network analysis explored molecular events governing mtH2S donor-mediated health span. Developmentally administered mtH2S (100 nM) improved life/health span vs. equivalent untargeted H2S doses. mtH2S preserved aging mitochondrial structure, content (citrate synthase activity) and neuromuscular strength. Knockdown of H2S metabolism enzymes and FoxO/daf-16 prevented the positive health span effects of mtH2S, whereas DCAF11/wdr-23 - Nrf2/skn-1 oxidative stress protection pathways were dispensable. Health span, but not life span, increased with all adult-onset mtH2S treatments. Adult mtH2S treatment also rejuvenated aging transcriptomes by minimizing expression declines of mitochondria and cytoskeletal components, and peroxisome metabolism hub components, under mechanistic control by the elt-6/elt-3 transcription factor circuit. H2S health span extension likely acts at the mitochondrial level, the mechanisms of which dissociate from life span across adult vs. developmental treatment timings. The small mtH2S doses required for health span extension, combined with efficacy in adult animals, suggest mtH2S is a potential healthy aging therapeutic.
    • Caenorhabditis elegans in microgravity: An omics perspective

      Scott, A.; Willis, Craig R.G.; Muratani, M.; Higashitani, A.; Etheridge, T.; Szewczyk, N.J.; Deane, C.S. (2023-07)
      The application of omics to study Caenorhabditis elegans (C. elegans) in the context of spaceflight is increasing, illuminating the wide-ranging biological impacts of spaceflight on physiology. In this review, we highlight the application of omics, including transcriptomics, genomics, proteomics, multi-omics, and integrated omics in the study of spaceflown C. elegans, and discuss the impact, use, and future direction of this branch of research. We highlight the variety of molecular alterations that occur in response to spaceflight, most notably changes in metabolic and neuromuscular gene regulation. These transcriptional features are reproducible and evident across many spaceflown species (e.g., mice and astronauts), supporting the use of C. elegans as a model organism to study spaceflight physiology with translational capital. Integrating tissue-specific, spatial, and multi-omics approaches, which quantitatively link molecular responses to phenotypic adaptations, will facilitate the identification of candidate regulatory molecules for therapeutic intervention and thus represents the next frontiers in C. elegans space omics research.
    • The systematic literature review process: a simple guide for public health and allied health students

      Kabir, R.; Hayhoe, R.; Bai, A.C.M.; Vinnakota, D.; Sivasubramanian, M.; Afework, S.; Chilaka, Marcus; Mohammadnezhad, Masoud; Aremu, O.; Sah, R.K.; et al. (2023)
      A literature review is a key part of all academic research that informs researchers of the existing body of knowledge. Reviews conducted systematically are becoming more appealing to the researcher about two reasons. Firstly, they are robust, strong, comprehensive and reproducible and can appropriately serve the background review of any primary research. Secondly, they are qualified to be a stand-alone piece of academic work that contributes to the scientific body of knowledge. Although researchers and students in higher education who wish to write their dissertations are informed about the need for generating a literature review for primary research, when it comes to conducting a full systematic review, they may have some confusion and doubt on the distinction between a traditional literature review and a systematic review. This paper aims to clarify what a systematic review entails and take the readers' attention through the practical steps in conducting a systematic review. So, more of a practical step-by-step guide, rather than theoretical discussion of content, has been included. This paper would benefit early-career researchers, undergraduate students and many post-graduate students who wish to write their papers or dissertations based on a systematic review.
    • Synthesis and biological evaluation of cyclobutane-based β3 integrin antagonists: A novel approach to targeting integrins for cancer therapy

      Sutherland, Mark H.; Gordon, Andrew; Al-Shammari, F.O.F.O.; Throup, Adam E.; La Corte, A.C.; Philippou, H.; Shnyder, Steven D.; Patterson, Laurence H.; Sheldrake, Helen M. (2023-08)
      The Arg-Gly-Asp (RGD)-binding family of integrin receptors, and notably the β3 subfamily, are key to multiple physiological processes involved in tissue development, cancer proliferation, and metastatic dissemination. While there is compelling preclinical evidence that both αvβ3 and αIIbβ3 are important anticancer targets, most integrin antagonists developed to target the β3 integrins are highly selective for αvβ3 or αIIbβ3. We report the design, synthesis, and biological evaluation of a new structural class of ligand-mimetic β3 integrin antagonist. These new antagonists combine a high activity against αvβ3 with a moderate affinity for αIIbβ3, providing the first evidence for a new approach to integrin targeting in cancer.
    • Transformative role of big data through enabling capability recognition in construction

      Atuahene, Bernard T.; Kanjanabootra, S.; Gajendran, T. (Taylor and Francis (Routledge), 2023)
      Big data application is a significant transformative driver of change in the retail, health, engineering, and advanced manufacturing sectors. Big data studies in construction are still somewhat limited, although there is increasing interest in what big data application could achieve. Through interviews with construction professionals, this paper identifies the capabilities needed in construction firms to enable the accrual of the potentially transformative benefits of big data application in construction. Based on previous studies, big data application capabilities, needed to transform construction processes, focussed on data, people, technology, and organisation. However, the findings of this research suggest a critical modification to that focus to include knowledge and the organisational environment along with people, data, and technology. The research findings show that construction firms use big data with a combination strategy to enable transformation by (a) driving an in-house data management policy to rolling-out the big data capabilities; (b) fostering collaborative capabilities with external firms for resource development, and (c) outsourcing big data services to address the capabilities deficits impacting digital transformation.
    • Early diagnosis and personalised treatment focusing on synthetic data modelling: Novel visual learning approach in healthcare

      Mahmoud, Ahsanullah Y.; Neagu, Daniel; Scrimieri, Daniele; Abdullatif, Amr R.A. (2023-09)
      The early diagnosis and personalised treatment of diseases are facilitated by machine learning. The quality of data has an impact on diagnosis because medical data are usually sparse, imbalanced, and contain irrelevant attributes, resulting in suboptimal diagnosis. To address the impacts of data challenges, improve resource allocation, and achieve better health outcomes, a novel visual learning approach is proposed. This study contributes to the visual learning approach by determining whether less or more synthetic data are required to improve the quality of a dataset, such as the number of observations and features, according to the intended personalised treatment and early diagnosis. In addition, numerous visualisation experiments are conducted, including using statistical characteristics, cumulative sums, histograms, correlation matrix, root mean square error, and principal component analysis in order to visualise both original and synthetic data to address the data challenges. Real medical datasets for cancer, heart disease, diabetes, cryotherapy and immunotherapy are selected as case studies. As a benchmark and point of classification comparison in terms of such as accuracy, sensitivity, and specificity, several models are implemented such as k-Nearest Neighbours and Random Forest. To simulate algorithm implementation and data, Generative Adversarial Network is used to create and manipulate synthetic data, whilst, Random Forest is implemented to classify the data. An amendable and adaptable system is constructed by combining Generative Adversarial Network and Random Forest models. The system model presents working steps, overview and flowchart. Experiments reveal that the majority of data-enhancement scenarios allow for the application of visual learning in the first stage of data analysis as a novel approach. To achieve meaningful adaptable synergy between appropriate quality data and optimal classification performance while maintaining statistical characteristics, visual learning provides researchers and practitioners with practical human-in-the-loop machine learning visualisation tools. Prior to implementing algorithms, the visual learning approach can be used to actualise early, and personalised diagnosis. For the immunotherapy data, the Random Forest performed best with precision, recall, f-measure, accuracy, sensitivity, and specificity of 81%, 82%, 81%, 88%, 95%, and 60%, as opposed to 91%, 96%, 93%, 93%, 96%, and 73% for synthetic data, respectively. Future studies might examine the optimal strategies to balance the quantity and quality of medical data.
    • An overview of safety and security analysis frameworks for the Internet of Things

      Abdulhamid, Alhassan; Kabir, Sohag; Ghafir, Ibrahim; Lei, Ci (2023-07)
      The rapid progress of the Internet of Things (IoT) has continued to offer humanity numerous benefits, including many security and safety-critical applications. However, unlocking the full potential of IoT applications, especially in high-consequence domains, requires the assurance that IoT devices will not constitute risk hazards to the users or the environment. To design safe, secure, and reliable IoT systems, numerous frameworks have been proposed to analyse the safety and security, among other properties. This paper reviews some of the prominent classical and model-based system engineering (MBSE) approaches for IoT systems’ safety and security analysis. The review established that most analysis frameworks are based on classical manual approaches, which independently evaluate the two properties. The manual frameworks tend to inherit the natural limitations of informal system modelling, such as human error, a cumbersome processes, time consumption, and a lack of support for reusability. Model-based approaches have been incorporated into the safety and security analysis process to simplify the analysis process and improve the system design’s efficiency and manageability. Conversely, the existing MBSE safety and security analysis approaches in the IoT environment are still in their infancy. The limited number of proposed MBSE approaches have only considered limited and simple scenarios, which are yet to adequately evaluate the complex interactions between the two properties in the IoT domain. The findings of this survey are that the existing methods have not adequately addressed the analysis of safety/security interdependencies, detailed cyber security quantification analysis, and the unified treatment of safety and security properties. The existing classical and MBSE frameworks’ limitations obviously create gaps for a meaningful assessment of IoT dependability. To address some of the gaps, we proposed a possible research direction for developing a novel MBSE approach for the IoT domain’s safety and security coanalysis framework.
    • Optimal planning and operation of distribution systems using network reconfiguration and flexibility services

      Marquez, Jorge A.; Al-Ja'Afreh, Mohammad A.; Mokryani, Geev; Kabir, Sohag; Campean, I. Felician; Dao, Cuong D.; Riaz, Sana (Elsevier, 2023-12)
      This paper proposes a novel approach for the reliability cost-based optimization of Distribution Systems (DS), considering tie line-based network reconfiguration method with integration of Distributed Energy Resources (DER). An optimal Energy not Supplied (ENS) index is proposed, where the capacity is handled by curtailment devices in the network such as sectionalizers and the energy supplied by DERs which considers Flexibility Services (FS) within a market environment. The decision variables include the investment and operation of tie-lines and buying regulation services from DER such as Distributed Generation (DG) and Battery Energy Storage Systems (BESS). The results validate the cost-effectiveness of the proposed method through implementation of these technologies to improve the reliability of the DS, within a comprehensive set of case-study scenarios for a 16-bus UK generic distribution system (UKGDS). The case study results indicate that significant savings can be achieved through the proposed method, ranging between 36%–71% depending on the level of automation in tie-line operations in combination with the settlement price for the power-balance of FS. This illustrates that the proposed DS reliability cost-based optimization method could have a significant impact for real world DG and BESS applications.
    • A knowledge-driven model to assess inherent safety in process infrastructure

      Gholamizadeh, K.; Zarei, E.; Kabir, Sohag; Mamudu, A.; Aala, Y.; Mohammadfam, I. (2023-06)
      Process safety has drawn increasing attention in recent years and has been investigated from different perspectives, such as quantitative risk analysis, consequence modeling, and regulations. However, rare attempts have been made to focus on inherent safety design assessment, despite being the most cost-effective safety tactic and its vital role in sustainable development and safe operation of process infrastructure. Accordingly, the present research proposed a knowledge-driven model to assess inherent safety in process infrastructure under uncertainty. We first developed a holistic taxonomy of contributing factors into inherent safety design considering chemical, reaction, process, equipment, human factors, and organizational concerns associated with process plants. Then, we used subject matter experts, content validity ratio (CVR), and content validity index (CVI) to validate the taxonomy and data collection tools. We then employed a fuzzy inference system and the Extent Analysis (EA) method for knowledge acquisition under uncertainty. We tested the proposed model on a steam methane-reforming plant that produces hydrogen as renewable energy. The findings revealed the most contributing factors and indicators to improve the inherent safety design in the studied plant and effectively support the decision-making process to assign proper safety countermeasures.