Search results for: forecast uncertainty

Authors: Mara Gabrielli, Jordi Pamies Rovira

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From a theoretical and interdisciplinary approach to visual ethnography and visual anthropology, this small scale, in-depth study explores the potential of photography as a participatory ethnographic method for a deep-understanding of the socio-educational integration of young refugees and asylum-seekers in the host society as regards their daily experiences, their needs, desires, expectations, and future goals. Qualitative data is collected by the author by observing 12 young participants in the age group 12-24 years per week for 12 months. The data consists of field notes, participatory observation, in-depth interviews with professionals, and the use of visual participatory ethnographic methods. Therefore, the young participants build their stories through the implementation of two participatory photographic methods - the 'photo-diary' and the 'photo-elicitation' - that permit them to analyse and narrate their social and educational experiences from their perspectives, thus collaborating in the construction of knowledge during the different stages of the research. Preliminary findings show the high resilience and social adaptability of young refugees and asylum-seekers to achieve their goals and overcome structural and socio-cultural barriers. However, the uncertainty of their administrative situation during the asylum submission and the lack of specific resources might impact negatively on their educational pathways and the transition to the labour market. Finally, this study also highlights the benefits of participatory photographic methods in ethnographic research, which impacts positively the well-being of these young people, helps them to develop critical thinking, and it also allows them to access information more respectfully when narrating painful experiences.

Keywords: photo-diary, photo-elicitation, resilience, strategies, visual methodologies, young refugees and asylum seekers

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Authors: Mohammad Zafar-ul Islam, Shaily Menon, Xingong Li, A. Townsend Peterson

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In addition to the mounting empirical data on direct implications of climate change for natural and human systems, evidence is increasing for other, indirect climate change phenomena such as sea-level rise. Rising sea levels and associated marine intrusion into terrestrial environments are predicted to be among the most serious eventual consequences of climate change. The many complex and interacting factors affecting sea levels create considerable uncertainty in sea-level rise projections: conservative estimates are on the order of 0.5-1.0 m globally, while other estimates are much higher, approaching 6 m. Marine intrusion associated with 1– 6 m sea-level rise will impact species and habitats in coastal ecosystems severely. Examining areas most vulnerable to such impacts may allow design of appropriate adaptation and mitigation strategies. We present an overview of potential effects of 1 and 6 m sea level rise for coastal conservation areas in the Indian Subcontinent. In particular, we examine the projected magnitude of areal losses in relevant biogeographic zones, ecoregions, protected areas (PAs), and Important Bird Areas (IBAs). In addition, we provide a more detailed and quantitative analysis of likely effects of marine intrusion on 22 coastal PAs and IBAs that provide critical habitat for birds in the form of breeding areas, migratory stopover sites, and overwintering habitats. Several coastal PAs and IBAs are predicted to experience higher than 50% losses to marine intrusion. We explore consequences of such inundation levels on species and habitat in these areas.

Keywords: sea-level change, coastal inundation, marine intrusion, biogeographic zones, ecoregions, protected areas, important bird areas, adaptation, mitigation

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Authors: Donald G. Danmeier, Gian Marco Pizzo, Matthew Brennan

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Although wetlands have been proposed as a green alternative to manage coastal flood hazards because of their capacity to adapt to sea level rise and provision of multiple ecological and social co-benefits, they are often overlooked due to challenges in quantifying the uncertainty and naturally, variability of these systems. This objective of this study was to quantify wave attenuation provided by a natural marsh surrounding a large oil refinery along the US Gulf Coast that has experienced steady erosion along the shoreward edge. The vegetation module of the SWAN was activated and coupled with a hydrodynamic model (DELFT3D) to capture two-way interactions between the changing water level and wavefield over the course of a storm event. Since the marsh response to relative sea level rise is difficult to predict, a range of future marsh morphologies is explored. Numerical results were examined to determine the amount of wave attenuation as a function of marsh extent and the relative contributions from white-capping, depth-limited wave breaking, bottom friction, and flexing of vegetation. In addition to the coupled DELFT3D-SWAN modeling of a storm event, an uncoupled SWAN-VEG model was applied to a simplified bathymetry to explore a larger experimental design space. The wave modeling revealed that the rate of wave attenuation reduces for higher surge but was still significant over a wide range of water levels and outboard wave heights. The results also provide insights to the minimum marsh extent required to fully realize the potential wave attenuation so the changing coastal hazards can be managed.

Keywords: green infrastructure, wave attenuation, wave modeling, wetland

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Authors: Sang-Ju Yu

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This paper examines the changing essences and effects of ‘affective atmosphere’ during the COVID-19 pandemic crisis, which have been facilitated and shaped the ‘affective governance’ in Taiwan. Due to long-term uncertainty and unpredictability, the COVID-19 pandemic not only caused unprecedented global crisis but triggered the public’s negative emotional responses. This paper unravels how the shortage of Personal Protective Equipment and the proliferating fake news heightened people’s fear and anxiety and how specific affective atmospheres can be provoked and manipulated to harness emotional appeals of citizens strategically in Taiwan. Through the in-depth interviews with diverse stakeholders involved, it unfolds the dynamics and strategies of affective governance, wherein public emotions and concerns are now given significant consideration in both policy measures and the affective expression of leadership, spatial arrangement, service delivery, and the interaction with citizens. Addressing psychosocial and emotional needs has become the core of crisis response mechanisms suited to dynamic affective atmospheres and pandemic situation. This paper also demonstrates that epidemic prevention and control is not merely the production of neutral or rational policy-making processes, as it is dominated by multiple emotions resulted from unexpected and salient events at different moments. It provides explicit insight into how different prevention scenarios operated effectively through political and affective mobilisation to strengthen emotional bonding and collective identity which energises collective action. Basically, successful affective governance calls for both negative and positive emotions, for both scientific and political decision-making, for both community and bureaucracy, and both quality and efficiency of private–public collaboration.

Keywords: affective atmospheres, affective governance, COVID-19 pandemic, private-public collaboration

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Authors: Sameer Jung Karki, Gokhan Saygili

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The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Sade Ogundipe

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The private healthcare sector in the United Kingdom has experienced unprecedented challenges during times of crisis, necessitating effective leadership adaptability. This qualitative study delves into the dynamic landscape of leadership within the sector, particularly during crises, employing the lenses of complexity theory and institutional theory to unravel the intricate mechanisms at play. Through in-depth interviews with 25 various levels of leaders in the UK private healthcare sector, this research explores how leaders in UK private healthcare organizations navigate complex and often chaotic environments, shedding light on their adaptive strategies and decision-making processes during crises. Complexity theory is used to analyze the complicated, volatile nature of healthcare crises, emphasizing the need for adaptive leadership in such contexts. Institutional theory, on the other hand, provides insights into how external and internal institutional pressures influence leadership behavior. Findings from this study highlight the multifaceted nature of leadership adaptability, emphasizing the significance of leaders' abilities to embrace uncertainty, engage in sensemaking, and leverage the institutional environment to enact meaningful changes. Furthermore, this research sheds light on the challenges and opportunities that leaders face when adapting to crises within the UK private healthcare sector. The study's insights contribute to the growing body of literature on leadership in healthcare, offering practical implications for leaders, policymakers, and stakeholders within the UK private healthcare sector. By employing the dual perspectives of complexity theory and institutional theory, this research provides a holistic understanding of leadership adaptability in the face of crises, offering valuable guidance for enhancing the resilience and effectiveness of healthcare leadership within this vital sector.

Keywords: leadership, adaptability, decision-making, complexity, complexity theory, institutional theory, organizational complexity, complex adaptive system (CAS), crises, healthcare

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Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

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This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

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Authors: Mohd Najib Mansor, Nur Syamilah Md. Noor, Abdul Rahim Anuar, Shazida Jan Mohd Khan, Ahmad Zubir Ibrahim, Badariah Hj Din, Abu Sufian Abu Bakar, Kalsom Kayat, Wan Nurmahfuzah Jannah Wan Mansor

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This study aimed and focused on the behavior of youth entrepreneurs’ especially entrepreneurial self-efficacy and the performance in micro SMEs in Malaysia. Entrepreneurship development calls for support from various quarters, and mostly the need exists to initiate a youth entrepreneurship culture and drive amongst the youth in the society. Although backed up by the government and non-government organizations, micro-entrepreneurs are still facing challenges which greatly delay their progress, growth and consequently their input towards economic advancement. Micro-entrepreneurs are confronted with unique difficulties such as uncertainty, innovation, and evolution. Reviews on the development of entrepreneurial characteristics such as need for achievement, internal locus of control, risk-taking and innovation and have been recognized as highly associated with entrepreneurial behavior. The data in this study was obtained from the Department of Statistics, Malaysia. A random sampling of 830 respondents was distributed to 14 states that involve of micro-entrepreneurs. The study adopted a quantitative approach whereby a set of questionnaire was used to gather data. Multiple regression analysis was chosen as a method of analysis testing. The result of this study is expected to provide insight into the factor affecting entrepreneurial behavior and performance of youth entrepreneurs in micro SMEs. The finding showed that the Malaysian youth entrepreneurs do not have the entrepreneurial self-efficacy within themselves in order to accomplish greater success in their business venture. The establishment of entrepreneurial schools to allow our youth to be exposed to entrepreneurship from an early age and the development of special training focuses on the creation of business network so that the continuous entrepreneurial culture is crafted.

Keywords: youth entrepreneurs, micro entrepreneurs, entrepreneurial self-efficacy, entrepreneurial performance

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Authors: Masoud Ghahvechi Pour

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Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

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Authors: Peaceman Sopazi, Mabila Mathebula, John Smallwood

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Recent health and safety (H&S) concerns and their resultant impact on railway operations, namely, the severe acute respiratory syndrome (SARS) or collectively known as SARS-CoV-2 (Covid-19) pandemic and the Fourth Industrial Revolution (4IR), which have dominated public discourse, brought into question as to whether, or not, some aspects of how we have so far managed safety oversight as railway regulatory bodies and operators will remain relevant in a changing railway environment. Railway practitioners have generally found themselves between a proverbial rock and a hard place by being confronted by emerging challenges which have brought along great opportunities for sustainability. As witnesses and participants to the progressively introduced railway safety management, and transformation regimes, this paper attempts to share gathered field experience on adaptable regulatory oversight and safety awareness. The discourse is approached from a South African context but also with an informed perspective of what seems to work and what usually does not. The authors share their own multi and transdisciplinary experience coupled with insights they have gained as researchers of global trends in general safety management and specific aspects of railway safety management, for sustainability. In addition to sharing a largely experience-based methodology for survival, suggestions are offered for consideration as a way of keeping the railway safety management discourse alive as practitioners navigate a new path which is shrouded in a cloud of untold uncertainty. The authors further believe that the right timing for the implementation of the proposed suggestions in this paper will produce beneficial outcomes. Finally, the paper will identify areas that are still open for further investigation for and by researchers and practitioners alike.

Keywords: health & safety management, safety awareness, railway safety management, railway systems sustainability

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Authors: Meng Qing Feng, Otsile Morake

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Background: Successful implementation of the COVID-19 vaccination ensures the prevention of virus infection. Postponement and refusal of the vaccination will threaten public health, which is now common among the general public across the world. In addition, an acceptance of the COVID-19 vaccine appears as a decisive factor in controlling the COVID-19 pandemic. Purpose: This study's objective is to explore the factors influencing the public intention to be vaccinated (ITBV). Design/methodology/approach: The web-based survey included socio-demographics and questions related to the theory of planned behavior (TPB) and the health belief model (HBM). An online survey was administered using Google Form to collect data from participants of Botswana. The sample included 339 participants, half-half of the participants were female. Data analysis was run using the Statistical Package for the Social Sciences (SPSS). Findings: The study results highlight that perceived severity, perceived barriers, health motivation, and attitude have a positive and significant effect on ITBV, while perceived susceptibility, benefits, subjective norms, and perceived behavior control do not affect ITBV. Among all of the predictors, perceived barriers have the most significant influence on ITBV. Conclusion: Theoretically, this research stated that both HBM and TPB are effective in predicting and explaining the general public ITBV. Practically, this study offers insights to the government and health departments to arrange and launch health awareness programs and provide a better guide to vaccination so that doubts about vaccine confidence and the level of uncertainty can be decreased.

Keywords: COVID-19, Omicron, intention to be COVID-19 vaccine, health behavior model, theory of planned behavior, Botswana

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Authors: Van-Thanh Ho, Jaiyoung Ryu

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In soft robotics, the optimization of fluid dynamics through pneumatic methods plays a pivotal role in enhancing operational efficiency and reducing energy loss. This is particularly crucial when replacing conventional techniques such as cable-driven electromechanical systems. The pneumatic model employed in this study represents a sophisticated framework designed to efficiently channel pressure from a high-pressure reservoir to various muscle locations on the robot's body. This intricate network involves a branching system of tubes. The study introduces a comprehensive pneumatic model, encompassing the components of a reservoir, tubes, and Pneumatically Actuated Muscles (PAM). The development of this model is rooted in the principles of shock tube theory. Notably, the study leverages experimental data to enhance the understanding of the interplay between the PAM structure and the surrounding fluid. This improved interactive approach involves the use of morphing motion, guided by a contraction function. The study's findings demonstrate a high degree of accuracy in predicting pressure distribution within the PAM. The model's predictive capabilities ensure that the error in comparison to experimental data remains below a threshold of 10%. Additionally, the research employs a machine learning model, specifically a surrogate model based on the Kriging method, to assess and quantify uncertainty factors related to the initial reservoir pressure and tube diameter. This comprehensive approach enhances our understanding of pneumatic soft robotics and its potential for improved operational efficiency.

Keywords: pneumatic artificial muscles, pressure drop, morhing motion, branched network, surrogate model

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Authors: Suneel Kumar, Nanda Kumar J. Sreelal Sreedhar, Suchibrata Sen, V. Muralidharan,

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Fan technology is very critical and crucial for any aero engine technology. The fan disc forms a critical part of the fan module. It is an airworthiness requirement to have a metrological qualified quality disc. The current study uses a tactile probing and scanning on an articulated measuring machine (AMM), a bridge type coordinate measuring machine (CMM) and Metrology software for intermediate and final dimensional and geometrical verification during the prototype development of the disc manufactured through forging and machining process. The circumferential dovetails manufactured through the milling process are evaluated based on the evaluated and analysed metrological process. To perform metrological optimization a change of philosophy is needed making quality measurements available as fast as possible to improve process knowledge and accelerate the process but with accuracy, precise and traceable measurements. The offline CMM programming for inspection and optimisation of the CMM inspection plan are crucial portions of the study and discussed. The dimensional measurement plan as per the ASME B 89.7.2 standard to reach an optimised CMM measurement plan and strategy are an important requirement. The probing strategy, stylus configuration, and approximation strategy effects on the measurements of circumferential dovetail measurements of the developmental prototype disc are discussed. The results were discussed in the form of enhancement of the R &R (repeatability and reproducibility) values with uncertainty levels within the desired limits. The findings from the measurement strategy adopted for disc dovetail evaluation and inspection time optimisation are discussed with the help of various analyses and graphical outputs obtained from the verification process.

Keywords: coordinate measuring machine, CMM, aero engine, articulated measuring machine, fan disc

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Habib Abida, Noura Dahri

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Flash floods are among the most serious natural hazards that have disastrous environmental and human impacts. They are associated with exceptional rain events, characterized by short durations, very high intensities, rapid flows and small spatial extent. Flash floods happen very suddenly and are difficult to forecast. They generally cause damage to agricultural crops and property, infrastructures, and may even result in the loss of human lives. The city of Gabes (South-eastern Tunisia) has been exposed to numerous damaging floods because of its mild topography, clay soil, high urbanization rate and erratic rainfall distribution. The risks associated with this situation are expected to increase further in the future because of climate change, deemed responsible for the increase of the frequency and the severity of this natural hazard. Recently, exceptional events hit Gabes City causing death and major property losses. A major flooding event hit the region on June 2nd, 2014, causing human deaths and major material losses. It resulted in the stagnation of storm water in the numerous low zones of the study area, endangering thereby human health and causing disastrous environmental impacts. The characterization of flood risk in Gabes Watershed (South-eastern Tunisia) is considered an important step for flood management. Analytical Hierarchy Process (AHP) method coupled with Monte Carlo simulation and geographic information system were applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin. Moreover, a survey was conducted from different areas of the city in order to understand and explore the different causes of this disaster, its extent and its consequences.

Keywords: analytical hierarchy process, flash floods, Gabes, remote sensing, Tunisia

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Sarah Snyder

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Historians use the term ‘post-Holocaust’ to indicate the period from 1945 onward; however, for survivors of the Holocaust and their families, the Holocaust did not end in 1945. In fact, for some, it was just the beginning of their struggles. There are those who could not return to their homes, find loved ones, or fight off night terrors. Additionally, they continue to suffer from mental illness or physical disease stemming from the Holocaust. In order for historians to have a clearer understanding of the trauma survivors have endured, it is must to approach time differently. Trauma does not operate on a timeline and thereby, our understanding of ‘before,’ ‘during’ and ‘after’ are flawed. In order to convey this flaw, this study will examine memoirs of second and third-generation survivors and of child survivors. Within the second and third generation group, there are two types of generational memoirs that are scrutinized for this case study. The first being when a child or grandchild records the stories of their parent(s) or grandparent(s) without any of the second or third generation’s stories implicitly written. ‘Implicitly’ is used in the context that it is impossible for any writer to not impose at least some stylistic portion of themselves into writing, but the intent was to focus on the parent or grandparent. The other type of memoir is when they write their parent(s) or grandparent(s) story intertwined with their own story. Additionally, the child survivor has a unique role in memory and trauma studies. Much like later generations who write about the Holocaust but have not experienced the trauma firsthand, the child survivor must write about what they lived through and experienced but cannot remember without the assistance of research or other survivors. This study shows that survivors continue to demonstrate trauma-related paranoia. They fear experiencing another Holocaust. In their minds, they replay the horrors that they had experienced. A pilgrimage to a 20th century Europe, unlike one of the 1940s, causes uncertainty, confusion, and additional paranoia. It is through these findings that it becomes evident that historians must learn to study trauma without placing strict timelines that prevent understanding of how trauma impacts those who have experienced complex trauma.

Keywords: holocaust, generational, memoirs, trauma

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Ässia Boukhatmi, Roger Nyffenegger

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The expansion of solar energy as a means to address the climate crisis is undisputed, but the increasing number of new photovoltaic (PV) modules being put on the market is simultaneously leading to increased challenges in terms of managing the growing waste stream. Many of the discarded modules are still fully functional but are often damaged by improper handling after disassembly or not properly tested to be considered for a second life. In addition, the collection rate for dismantled PV modules in several European countries is only a fraction of previous projections, partly due to the increased number of illegal exports. The underlying problem for those market imperfections is an insufficient data exchange between the different actors along the PV value chain, as well as the limited traceability of PV panels during their lifetime. As part of the Horizon 2020 project CIRCUSOL, an asset database prototype was developed to tackle the described problems. In an iterative process applying the design science research methodology, different business models, as well as the technical implementation of the database, were established and evaluated. To explore the requirements of different stakeholders for the development of the database, surveys and in-depth interviews were conducted with various representatives of the solar industry. The proposed database prototype maps the entire value chain of PV modules, beginning with the digital product passport, which provides information about materials and components contained in every module. Product-related information can then be expanded with performance data of existing installations. This information forms the basis for the application of data analysis methods to forecast the appropriate end-of-life strategy, as well as the circular economy potential of PV modules, already before they arrive at the recycling facility. The database prototype could already be enriched with data from different data sources along the value chain. From a business model perspective, the database offers opportunities both in the area of reuse as well as with regard to the certification of sustainable modules. Here, participating actors have the opportunity to differentiate their business and exploit new revenue streams. Future research can apply this approach to further industry and product sectors, validate the database prototype in a practical context, and can serve as a basis for standardization efforts to strengthen the circular economy.

Keywords: business model, circular economy, database, design science research, solar industry

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Authors: Housein Deli, Loui Al-Shrouf, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Renan De Caldas Honorato, Ana Augusta Ferreira De Freitas

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Homosexuality is still criminalized in a large number of countries. In some of them, being gay or lesbian can even be punished by death. Added to this context, the experiences of social discrimination faced by the LGBT population, including homophobia, machismo and misogyny, cause numerous restrictions throughout their lives. The possibility of confronting these challenges in moments that should be pleasant, such as on a trip or on vacation, is unpleasant, to say the least. In the current scenario of intensifying the use of Social network sites (SNSs) to search for information, including in the tourist area, this work aims to analyze the sharing of tourist experiences with situations of confrontation and perceptions of homophobia, machismo and misogyny, and restrictions suffered in tourist destinations. The fieldwork is a community of LGBT backpackers based on Facebook. Netnography was the core method adopted. A qualitative approach was conducted and 463 publications posted from January to December 2020 were assessed through the computer-mediated discourse analysis (CMDA). The results suggest that these publications exist to identify the potential exposure to these offensive behaviors while traveling. Individuals affirm that the laws, positive or not, in relation to the LGBT public are not the only factors for a place to be defined as safe or not for gay travelers. The social situation of a country and its laws are quite different and this is the main target of these publications. The perception of others about the chosen destination is more important than knowing your rights and the legal status of each country and it also lessens uncertainty, even when they are never totally confident when choosing a travel destination. In certain circumstances, sexual orientation also needs to be protected from the judgment of hosts and residents. The systemic treatment of homophobic behavior and the construction of a more inclusive society are urgent.

Keywords: homophobia, hospitality, machismo, misogyny

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Authors: Chatelier Charlene, Oyegoke Adekunle, Ajayi Saheed, Jeffries Andrew

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This study seeks to understand Schedule Risk Assessments as a priori for better performance whilst exploring the strategies employed to deliver complex projects like the New Polar research ship. This high-profile vessel was offered to Natural Environment Research Council and British Antarctic Survey (BAS) by Cammell Laird Shipbuilders. The Research Ship was designed to support science in extreme environments, with the expectancy to provide a wide range of specialist scientific facilities, instruments, and laboratories to conduct research over multiple disciplines. Aim: The focus is to understand the allocation and management of schedule risk on such a Major Project. Hypothesising that "effective management of schedule risk management" could be the most critical factor in determining whether the intended benefits mentioned are delivered within time and cost constraints. Objective 1: Firstly, the study seeks to understand the allocation and management of schedule risk in Major Projects. Objective 2: Secondly, it explores "effective management of schedule risk management" as the most critical factor determining the delivery of intended benefits. Methodology: This study takes a retrospective review of schedule risk management and how it influences project performance using a case study approach for the RRS (Royal Research Ship) Sir David Attenborough. Research Contribution: The outcomes of this study will contribute to a better understanding of project performance whilst building on its under-researched relationship to schedule risk management for complex projects. The outcomes of this paper will guide further research on project performance and enable the understanding of how risk-based estimates over time impact the overall risk management of the project.

Keywords: complexity, major projects, performance management, schedule risk management, uncertainty

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

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Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

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Authors: Ana L. Martins, Luis Orfão

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Healthcare systems have been subject to various research efforts aiming at process improvement under a lean approach. Another perspective, agility, has also been used, though in a lower scale, in order to analyse the ability of different hospital services to adapt to demand uncertainties. Both perspectives have a common denominator, the improvement of effectiveness and efficiency of the services in a healthcare setting context. Mixing the two approached allows, on one hand, to streamline the processes, and on the other hand the required flexibility to deal with demand uncertainty in terms of both volume and variety. The present research aims to analyse the impacts of the combination of both perspectives in the effectiveness and efficiency of an hospital service. The adopted methodology is based on a case study approach applied to the process of the ambulatory surgery service of Hospital de Lamego. Data was collected from direct observations, formal interviews and informal conversations. The analyzed process was selected according to three criteria: relevance of the process to the hospital, presence of human resources, and presence of waste. The customer of the process was identified as well as his perception of value. The process was mapped using flow chart, on a process modeling perspective, as well as through the use of Value Stream Mapping (VSM) and Process Activity Mapping. The Spaghetti Diagram was also used to assess flow intensity. The use of the lean tools enabled the identification of three main types of waste: movement, resource inefficiencies and process inefficiencies. From the use of the lean tools improvement suggestions were produced. The results point out that leagility cannot be applied to the process, but the application of lean and agility in specific areas of the process would bring benefits in both efficiency and effectiveness, and contribute to value creation if improvements are introduced in hospital’s human resources and facilities management.

Keywords: case study, healthcare systems, leagility, lean management

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Authors: Soleen Karim, Meira Yasin, Rezhin Qader

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Children’s books present a colorful life for kids around the world, their current environment or what they could potentially have- a home, two loving parents, a playground, and a safe school within a short walk or bus ride. These images are only pages in a donated book for children displaced by war. The environment they live in is significantly different. Displaced children are faced with a temporary life style filled with fear and uncertainty. Children of war associate various structural institutions with a trauma and cannot enter the space, even if it is for their own future development, such as a school. This paper is a collaborative effort with students of the Kennesaw State University architecture department, architectural designers and a mental health professional to address and link the design challenges and the psychological trauma for children of war. The research process consists of a) interviews with former refugees, b) interviews with current refugee children, c) personal understanding of space through one’s own childhood, d) literature review of tested design methods to address various traumas. Conclusion: In addressing the built environment for children of war, it is necessary to address mental health and well being through the creation of space that is sensitive to the needs of children. This is achieved by understanding critical design cues to evoke normalcy and safe space through program organization, color, and symbiosis of synthetic and natural environments. By involving the children suffering from trauma in the design process, aspects of the design are directly enhanced to serve the occupant. Neglecting to involve the participants creates a nonlinear design outcome and does not serve the needs of the occupant to afford them equal opportunity learning and growth experience as other children around the world.

Keywords: activist architecture, childhood education, childhood psychology, adverse childhood experiences

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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Authors: Seyedmohsen Mortazavi

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The purpose of this research is to investigate the personality types of internal auditors on the quality of financial reporting in companies admitted to the Tehran Stock Exchange. Personality type is one of the issues that emphasizes the field of auditors' behavior, and this field has attracted the attention of shareholders and stock companies today, because the auditors' personality can affect the type of financial reporting and its quality. The research is applied in terms of purpose and descriptive and correlational in terms of method, and a researcher-made questionnaire was used to check the research hypotheses. The statistical population of the research is all the auditors, accountants and financial managers of the companies admitted to the Tehran Stock Exchange, and due to their large number and the uncertainty of their exact number, 384 people have been considered as a statistical sample using Morgan's table. The researcher-made questionnaire was approved by experts in the field, and then its validity and reliability were obtained using software. For the validity of the questionnaire, confirmatory factor analysis was first examined, and then using divergent and convergent validity; Fornell-Larker and cross-sectional load test of the validity of the questionnaire were confirmed; Then, the reliability of the questionnaire was examined using Cronbach's alpha and composite reliability, and the results of these two tests showed the appropriate reliability of the questionnaire. After checking the validity and reliability of the research hypotheses, PLS software was used to check the hypotheses. The results of the research showed that the personalities of internal auditors can affect the quality of financial reporting; The personalities investigated in this research include neuroticism, extroversion, flexibility, agreeableness and conscientiousness, all of these personality types can affect the quality of financial reporting.

Keywords: flexibility, quality of financial reporting, agreeableness, conscientiousness

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