University of Stavanger (UiS)

Mobile edge computing (MEC) relieves the latency and energy consumption of mobile applications by offloading computation-intensive tasks to nearby edges. In wireless metropolitan area networks (WMANs), edges can better provide computing services via advanced communication technologies. For improving the Quality-of-Service (QoS), edges need to be collaborated rather than working alone. However, the existing solutions of multi-edge collaboration solely adopt a centralized or decentralized decision-making way of load balancing, making it hard to achieve the optimal result because the local and global conditions are not jointly considered. To solve this problem, we propose a novel Two-stage Decision-making method of load Balancing for multi-Edge Collaboration (TDB-EC). First, the centralized decision-making is executed with global information, where a deep neural networks (DNN) based prediction model is designed to evaluate the range of task scheduling between adjacent edges. Next, considering the global condition of load balancing, the decentralized decision-making is executed with local information, where a deep Q-networks (DQN) based Q-value prediction model of adjustment operations is developed to evaluate the load balancing plan among edges. Finally, the objective load balancing plan is obtained via feedback-control. Extensive simulation experiments demonstrate the adaptability of the TDB-EC to various scenarios of multi-edge load balancing, which approximates the optimal result and outperforms three classic methods.

The fresh vegetable supply chain (FVSC) is a vital food supply chain for human consumption patterns. There are several hindering issues in the FVSC. Specifically, issues related to logistics operations are directly affecting the socio-economic statuses of the value chain actors and the vegetable ecosystem. Therefore, this research study reviewed the current status of the logistics operations at one of the main economic centers of a developing economy. This economic center operates as a wholesale platform for the FVSC. In this study, Swimlane diagram was improved with the inspiration of Business Process Modeling to visualise the current status conceptual diagram of the FVSC. The key issues related to the activities and processes were identified after assessing the conceptual diagram, known as the “As Is state” model. In the latter part of the study, areas for improvement using technology were identified, and corrective measures were proposed to improve logistics operations in the “To Be State” model. According to the study, integrating the supply chain network with producers, value chain actors, and consumers via a digital platform for data sharing and management will improve supply chain traceability and efficiency. Furthermore, it will increase transparency, allowing the supply chain to be more quality conscious and resilient in order to mitigate operational risks associated with FVSC. This study will contribute to the literature by addressing the current gap between how to digitally transform a traditional FVSC into a data driven digital FVSC.

Vaccines can be seen as one of the greatest successes in modern medicine. Good examples are the vaccines against smallpox, polio, and measles. Unfortunately, vaccines can have side effects, but the risks are considered by the health authorities and experts to be small compared to their benefits. Nevertheless, there are many who are skeptical of vaccination, something which has been very clearly demonstrated in relation to the COVID‐19 disease. Risk is the key concept when evaluating a vaccine, in relation to both its ability to protect against the disease and its side effects. However, risk is a challenging concept to measure, which makes communication about vaccines’ performance and side effects difficult. The present article aims at providing new insights into vaccine risks—the understanding, perception, communication, and handling of them—by adopting what is here referred to as a contemporary risk science perspective. This perspective clarifies the relationships between the risk concept and terms like uncertainty, knowledge, and probability. The skepticism toward vaccines is multifaceted, and influenced by concerns that extend beyond the effectiveness and safety of the vaccines. However, by clarifying the relationships between key concepts of risk, particularly how uncertainty affects risk and its characterization, we can improve our understanding of this issue.

We report on how we integrated smell into the classic children's story ‘The Three Little Pigs’ to enhance a public children's museum exhibition. The study employed Wenger's (1998) social theory of learning as its conceptual framework. It aimed to enhance children's sensory experience in a local Norwegian museum through a collaboration between academia and the industry. We used five abstract smells that were included in five wooden boxes and strategically placed around an adventure trail inside the museum (science factory). In this article, we reflect on the exhibition choices and findings, and recommendations for future children's exhibitions combining odors and narrative.

We propose a novel elastic AVO inversion process to estimate the fluid saturation and effective pressure or variations in these properties from time-lapse seismic datasets. These changes occur in oil and gas reservoirs caused by fluid injection or hydrocarbon production that leads to changes in the elastic wave properties, reflectivity, and seismic response. The proposed method is based on a seismic forward model that consists of a linearized AVO equation and a rock physics model. The AVO equation links the elastic wave properties to seismic reflection amplitudes, whereas the rock physics model maps the saturation and pressure into seismic properties. The inversion approach relies on the gradient-descent technique to estimate the unknown variables by searching for the minimum of the least-square misfit between observed and modeled data. The first-order gradient equations of the least-square data misfit function with respect to effective pressure and water saturation are derived by using the adjoint-state method and the chain rule. The optimization method used to minimize the misfit function and obtain the best optimal solution is a limited-memory quasi-Newton algorithm. This inversion process allows us to incorporate prior constraints by using the logistic function to map the model variables to a bounded range. To achieve a stable solution to ill-posed inversion problems, optimal regularization weights are applied. The application of the developed workflow on 1D synthetic and real well log data from the Edvard Grieg oil field simulating various saturation-pressure conditions during production demonstrates the validity of the approach with different noise levels. The inversion is then applied to a 2D synthetic dataset modeled from the reservoir model of the Smeaheia field, a potential site for a large-scale offshore CO2 storage field located in the North Sea. Our results illustrate that the proposed inversion method efficiently and accurately estimates reservoir saturation and pressure variations.

Background Prevalence of dementia illness, causing certain morbidity and mortality globally, places burden on global public health. This study primary goal was to assess future risks of dying from severe dementia, given specific return period, within selected group of regions or nations. Methods Traditional statistical approaches do not have benefits of effectively handling large regional dimensionality, along with nonlinear cross-correlations between various regional observations. In order to produce reliable long-term projections of excessive dementia death rate risks, this study advocates novel bio-system reliability technique, that being particularly suited for multi-regional environmental, biological, and health systems. Data Raw clinical data has been used as an input to the suggested population-based, bio-statistical technique using data from medical surveys and several centers. Results Novel spatiotemporal health system reliability methodology has been developed and applied to dementia death rates raw clinical data. Suggested methodology shown to be capable of dealing efficiently with spatiotemporal clinical observations of multi-regional nature. Accurate disease risks multi-regional spatiotemporal prediction being done, relevant confidence intervals have been presented as well. Conclusions Based on available clinical survey dataset, the proposed approach may be applied in a variety of clinical public health applications. Confidence bands, given for predicted dementia-associated death rate levels with return periods of interest, have been reasonably narrow, indicating practical values of advocated prognostics.

The aim of this research paper is to identify advantages and barriers to implementation and usage of robotic-assisted surgery (RAS), specifically the Da Vinci robot, at a larger regional hospital in Norway and from a multiple stakeholder perspective. The identified advantages and barriers are connected to the socio-technical system framework SEIPS, thereby establishing a broader contextual system perspective on RAS implementation and usage. Our findings both align and extend upon existing human factors and ergonomics (HFE) knowledge on RAS in the operating room. In terms of specific future directions, we believe that a pressing concern for both management and current HFE research involving RAS implementation and usage relates to exploring and accounting for the close connections between the organization itself and the external stakeholders that exert a considerable influence on the internal work system and processes and the ability to achieve cost-efficiency and safety levels. We further conclude that the SEIPS framework can be a powerful tool in drawing or eliciting the larger contextual picture of RAS implementation and usage, and we encourage further HFE research to explore its application in different contexts to improve the current knowledge base.

Abstract Objective To identify, review and synthesise qualitative literature on healthcare professionals’ adaptations to changes and challenges resulting from the COVID-19 pandemic. Design Systematic review with meta-synthesis. Data sources Academic Search Elite, CINAHL, MEDLINE, PubMed, Science Direct and Scopus. Eligibility criteria Qualitative or mixed-methods studies published between 2019 and 2021 investigating healthcare professionals’ adaptations to changes and challenges resulting from the COVID-19 pandemic. Data extraction and synthesis Data were extracted using a predesigned data extraction form that included details about publication (eg, authors, setting, participants, adaptations and outcomes). Data were analysed using thematic analysis. Results Forty-seven studies were included. A range of adaptations crucial to maintaining healthcare delivery during the COVID-19 pandemic were found, including taking on new roles, conducting self and peer education and reorganising workspaces. Triggers for adaptations included unclear workflows, lack of guidelines, increased workload and transition to digital solutions. As challenges arose, many health professionals reported increased collaboration across wards, healthcare teams, hierarchies and healthcare services. Conclusion Healthcare professionals demonstrated significant adaptive capacity when faced with challenges imposed by the COVID-19 pandemic. Several adaptations were identified as beneficial for future organisational healthcare service changes, while others exposed weaknesses in healthcare system designs and capacity, leading to dysfunctional adaptations. Healthcare professionals’ experiences working during the COVID-19 pandemic present a unique opportunity to learn how healthcare systems rapidly respond to changes, and how resilient healthcare services can be built globally.

The gas–liquid two-phase flow patterns of subsea jumpers are identified in this work using a multi-sensor information fusion technique, simultaneously collecting vibration signals and electrical capacitance tomography of stratified flow, slug flow, annular flow, and bubbly flow. The samples are then processed to obtain the data set. Additionally, the samples are trained and learned using the convolutional neural network (CNN) and feature fusion model, which are built based on experimental data. Finally, the four kinds of flow pattern samples are identified. The overall identification accuracy of the model is 95.3% for four patterns of gas–liquid two-phase flow in the jumper. Through the research of flow profile identification, the disadvantages of single sensor testing angle and incomplete information are dramatically improved, which has a great significance on the subsea jumper’s operation safety.

This book reviews the formative years of the United Nations (UN) under its first Secretary-General Trygve Lie.This welcome appraisal shows how the foundations for an expanded secretary-general role were laid during this period, and that Lie’s contribution was greater than has later been acknowledged. The interplay of crisis decision-making, institutional constraints and the individuals involved thus built the foundations for the UN organization we know today.Addressing important wider questions of IGO creation, governance and autonomy, this is an incisive account of how the UN moved from paper to practice under Lie.

A new research area is developing, risk literacy. The term “risk literacy” basically refers to one's ability to understand and evaluate risk, in order to support and make appropriate decisions. In this article, we discuss how risk literacy relates to risk analysis/science with its topics of risk fundamentals (concepts), risk understanding, risk assessments, risk characterizations, risk perception, risk communication, and risk handling (covering risk management, risk governance, and policies on risk). We question how issues and research topics addressed in risk literacy relate to risk analysis/science knowledge, particularly on risk understanding. The main conclusion of the article is that risk literacy addresses an important topic—from both a theoretical and a practical societal relevancy perspective—and brings the potential for many additional developments and further insights if the topic is better integrated with risk science knowledge more broadly.

Background Most senior citizens want to live independently at home as long as possible. The World Health Organization recommends an age-friendly community approach by transforming the service ecosystem for senior citizens and basing it on the question “What matters to you?”. However, there is limited research-based knowledge to determine the characteristics of the preferred service ecosystem from the perspectives of multiple stakeholders. Therefore, the aim of the study was to gain a deeper understanding of multiple stakeholder perspectives on the preferred service ecosystem for senior citizens living at home. Methods Four stakeholder groups (n = 57) from a Norwegian municipality participated in an interview study in 2019 and 2020: senior citizens, carers, healthcare professionals, and managers. Data were analysed according to qualitative content analysis. Results Overall, there was considerable correspondence between the four stakeholder groups’ perspectives on the preferred service ecosystem for senior citizens. Six themes were developed: (1) “self-reliance – living independently at home as long as possible”; (2) “remaining active and social within the community”; (3) “support for living at home as long as possible”; (4) “accessible information and services”; (5) “continuity of services”; and (6) “compassionate and competent healthcare professionals”. Conclusions In order to adapt and meet changing needs, the preferred service ecosystem should support senior citizens’ autonomy through interpersonal relationships and involvement. Healthcare managers and decision makers should consider a broader range of practical and social support services. Municipalities should plan for and develop age-friendly infrastructures, while healthcare professionals should rely on their compassion and competence to meet senior citizens’ needs.

This longitudinal study applied latent change score (LCS) modeling to examine individual changes in students’ (N = 1205) academic engagement (behavioral and emotional), social competencies (relationship skills and social awareness), and classroom relationships (emotional support from teachers and collaborative peer relations). Average changes during the first year of lower secondary school were investigated, and an LCS model specifying that individual changes in social competencies are related to individual changes in academic engagement partially via individual changes in classroom relationships was tested. The results indicated an average decline for all variables, particularly emotional engagement. Changes in social competencies were associated with changes in classroom relationships and indirectly with changes in academic engagement via changes in emotional support from teachers. A direct association was found between changes in social awareness and behavioral engagement. The findings reflect that the promotion of social competencies in lower secondary school may foster positive classroom relationships and academic engagement, mainly via perceived social awareness for behavioral engagement or via emotional support from teachers for both dimensions of academic engagement.

Background Operating room nurses have specialised technical and non-technical skills and are essential members of the surgical team. The profession’s dependency of tacit knowledge has made their non-technical skills difficult to access for researchers, thus, creating limitations in the identification of the non-technical skills of operating room nurses. Non-technical skills are categorised in the crew resource management framework, and previously, non-technical skills of operating room nurses have been identified within the scope of the framework. The purpose of this study is to explore operating room nurses’ descriptions of their practices in search for non-technical skills not included in the crew resource management framework. Methods This study has a qualitative design. An expert panel of experienced operating room nurses (N = 96) in Norway provided qualitative descriptions of their practice in a Delphi survey. The data were analysed in an inductive thematic analysis. This study was conducted and reported in line with Standards for Reporting Qualitative Research (SRQR). Results The inductive thematic analysis developed two themes, ‘Ethical competence’ and ‘Professional accountability’, that encompass operating room nurses’ novel descriptions of their non-technical skills. The participants take pride in having the patients’ best interest as their main objective even if this may threaten their position in the team. Conclusions This study has identified novel non-technical skills that are not described in the crew resource management framework. These findings will contribute to the development of a new behavioural marker system for the non-technical skills of operating room nurses. This system will facilitate verbalisation of tacit knowledge and contribute to an increased knowledge about the operating room nursing profession.

Technological reading and writing tools can help students with dyslexia improve their writing, but students do not use reading and writing functions as much as expected. However, research addressing relevant technological functions is scarce. This study explored the needs of writers with dyslexia and how technological writing tools developed for three Nordic languages meet these needs. Snowball sampling was used to identify different technological features, spellchecker, word prediction, auto‐correction, text‐to‐speech and speech‐to‐text functions available in nine widely used programmes were investigated. The results indicated that students with moderate spelling difficulties can now achieve accurate spellings using the most sophisticated spelling aids; however, most of these features require time and attention, and this can disturb writing fluency and hamper text production. The implication of this study is that the underlying conflict between spelling accuracy and writing fluency must be actively managed, which necessitates competence in the use of technological tools for both students and teachers in school. Also, further development of tools for scaffolding transcription must consider the dilemma of achieving both writing fluency and spelling accuracy. Further, the accuracy of the aid for students with severe spelling difficulties remains unclear and must be investigated.