Unstructured Approach Research Articles

An unstructured adaptive mesh refinement approach for computational fluid dynamics of reacting flows

A new Direct Numerical Simulation (DNS) code HAMISH with Adaptive Mesh Refinement (AMR) has been developed to simulate compressible reacting flow in a computationally economical manner. The focus is on problems where high gradients of temperature, density and species mass fraction remain localised, for example within the interior structure of flames. The resolution requirements of such local high-gradient regions often determine the global mesh spacing when uniform meshes are used. The numerical framework in HAMISH is based on an unstructured finite-volume approach together with a Runge-Kutta algorithm for time-stepping. The unstructured Cartesian mesh used in HAMISH allows for adaptive refinement and de-refinement of the local mesh depending on the demands of the flow physics and numerical accuracy. The code utilises an octree data structure and a Morton space-filling curve, allowing efficient cell division as well as straightforward parallel domain decomposition. The spatial discretisation scheme uses fourth-order polynomial reconstruction to evaluate the inter-cell fluxes. A third-order three-step explicit Runge-Kutta time-marching algorithm is used together with adaptive time-stepping with proportional-integral-type error control using an embedded Runge-Kutta scheme. The code is fully parallelised through domain decomposition over an arbitrary number of processors and exhibits a high level of parallel efficiency. In this paper the key capabilities of HAMISH are demonstrated based on a number of test cases. These test cases include (a) simulation of 1-D planar laminar premixed flames to demonstrate the capability of AMR in capturing the sharp gradients within the flame; (b) fully developed laminar channel flow, which shows that the code is capable of refining the mesh in the boundary layer next to the wall; (c) 2-D expanding flame under quiescent laminar condition, which demonstrates that the code is capable of dynamic local mesh refinement based on the position of the flame front; (d) 3-D non-reacting Taylor-Green vortex which demonstrates HAMISH can deal with vortical motion typical of turbulent flows; (e) 3-D premixed turbulent flame propagation under isotropic homogeneous decaying turbulence to demonstrate that the code can be employed for production level DNS of turbulent reacting flows.

What has been done and what has not – the government of Canada’s economic policy response to the coronavirus pandemic

PurposeThis paper aims to examine Canadian government measures to support country’s economic recovery and sustainable development. The goal is to examine whether all orders of government are working well to deliver the required help to Canadians.Design/methodology/approachThe theoretical foundations for this article are drawn from liberal and institutionalist approaches to comparative politics. Specifically, the proposed study draws on political tensions that occur because of actions of self-centered regional (provincial) governments who legitimize individual policies based on their self-centered economic and political objectives.FindingsNowadays, we can observe the primary role of the state in supporting and regulating the health governance systems, the economy and social life. Many informal groups have unstructured approach, which does not require them to follow existing strategies. The challenges caused by COVID-19 have led to the resurgence of collective, state-based approaches to the recovery. The key findings illuminate the importance of crisis communication activities which should be implemented properly. This implies that all disclosures must be timely and truthful.Practical implicationsThe study helps to better understand the events that disrupt parts of the Canadian economy during pandemic. It reviews the essential functions that are critical for reliable operation of infrastructure services to ensure safety and well-being of the population. During the COVID-19, federal–provincial–territorial collaboration runs into resistance because of competing interests, resource constraints, legacies from past conflicts and lack of coordination. In contrast to managers, who often focus on tangible short-term results, today’s leadership more often seeks intangible long-term results. This means that the central–local government relations tend to be more informal.Originality/valueIn the face of external shock, such as COVID-19, it did not take much time for Canadian provincial governments to realize that they cannot cope with a wide range of challenges alone. In these circumstances, the narratives of how governments work together during the challenging time to impact their desired outcomes are of crucial importance.

Early detection of skin cancer in Australia - current approaches and new opportunities.

Narrative review. Building on the discussions from the Melanoma Screening Summit held in Brisbane, Australia, in 2019, we reviewed evidence related to current approaches and new opportunities for early detection of melanoma and other skin cancers. Population-based melanoma screening is not currently recommended due to insufficient evidence that screening reduces melanoma mortality. Instead, in most countries including Australia, early detection of melanoma and keratinocyte carcinomas is undertaken opportunistically, by either the patient presenting for a routine skin check or with a lesion of concern, or by the doctor detecting a lesion incidentally. Several concerns about the current unstructured approach to skin cancer early detection have been identified, including variable quality of care, sociodemographic inequalities in medical access and health outcomes, excision of many benign lesions, overdiagnosis, gaps in workforce training, and health system inefficiencies. There has also been renewed interest in melanoma screening in Australia, driven by a changing landscape of skin cancer early detection. These changes include increasing health system costs for adjuvant therapies, advances in diagnostic technologies and artificial intelligence, the availability of validated risk-stratification tools, and consumer-driven digital technologies. The future of skin cancer early detection in Australia and internationally may incorporate features such as a more structured approach to skin cancer risk assessment using online risk calculators and invitations to screen, consumer-driven melanoma surveillance, and new technologies for diagnosis and monitoring of lesions. High-quality research evidence is being generated across multiple research programs, and is essential to underpin any changes to policy and practice in skin cancer early detection.

직접관찰법을 이용한 문학관광 관람자의 관람동선 및 관람행태 분석: 김유정문학촌을 대상으로

본 연구는 강원도 춘천시에 위치한 김유정문학촌을 대상으로 문학관광 관람자들의 관람동선과 관람행태를 분석하고자 한다. 김유정문학촌은 작가의 출생지와 거주지, 작품 배경 등으로 이루어져 있어 대한민국의 대표적인 문학관광지 중 하나라고 할 수 있다. 본 연구는 David Dean의 관람자 관람동선 모형과 Diamond Judy의 뮤즈에소그램에 근거하여 관람동선과 관람행태 분석을 진행하였으며, 직접관찰법을 사용하였다. 그 결과 주요 관광객들의 동선은 실내 전시공간에서는 제안동선(structured approach), 실외 전시공간에서는 임의동선(unstructured approach)이 주로 나타났다. 관람행태는 이동관람(ML), 정지(ST), 이동(M), 다른 사람과 대화(TK), 정지하여 관람하는 정지관람(SL), 전시내용 읽음(RE), 사진촬영(PH)의 빈도가 가장 높게 나타났다. 그러나 전시내용 읽음(RE)이 주된 관람행태 중 하나였으나, 이동관람(ML), 정지(ST), 이동(M), 다른 사람과 대화(TK), 정지하여 관람하는 정지관람(SL)보다 빈도가 낮게 나타났다. 이는 관람자들이 텍스트 기반의 문학작품을 읽는 것과 문학관광 목적지에서 작품을 경험하려는 것 사이에 차이가 있음을 의미한다. 또한 본 연구는 방문자들이 문학 관광지에서 보여주는 새로운 행동코드인

Biomaterials by design: Harnessing data for future development.

Biomaterials is an interdisciplinary field of research to achieve desired biological responses from new materials, regardless of material type. There have been many exciting innovations in this discipline, but commercialization suffers from a lengthy discovery to product pipeline, with many failures along the way. Success can be greatly accelerated by harnessing machine learning techniques to comb through large amounts of data. There are many potential benefits of moving from an unstructured empirical approach to a development strategy that is entrenched in data. Here, we discuss the recent work on the use of machine learning in the discovery and design of biomaterials, including new polymeric, metallic, ceramics, and nanomaterials, and how machine learning can interface with emerging use cases of 3D printing. We discuss the steps for closer integration of machine learning to make this exciting possibility a reality.

Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model using WAVEWATCH III version 6.07

Abstract. Wind-wave processes have generally been excluded from coupled Earth system models due to the high computational expense of spectral wave models, which resolve a frequency and direction spectrum of waves across space and time. Existing uniform-resolution wave modeling approaches used in Earth system models cannot appropriately represent wave climates from global to coastal ocean scales, largely because of tradeoffs between coastal resolution and computational costs. To resolve this challenge, we introduce a global unstructured mesh capability for the WAVEWATCH III (WW3) model that is suitable for coupling within the US Department of Energy's Energy Exascale Earth System Model (E3SM). The new unstructured WW3 global wave modeling approach can provide the accuracy of higher global resolutions in coastal areas at the relative cost of lower uniform global resolutions. This new capability enables simulation of waves at physically relevant scales as needed for coastal applications.

Deep Learning based Privacy Information Identification approach for Unstructured Text

Data sharing sometimes brings the privacy disclosure risk. Anonymization methods such as k-anonymity, l-diversity prevent privacy disclosure, but such methods are suitable for structured text. There are a lot of unstructured texts in people’s lives (such as social network texts, clinical texts), and identifying and structuring the private information(PI) of unstructured texts is a problem. Based on this, we propose a deep learning-based unstructured text PI identification approach, which can extract PI in unstructured text, associate the PI with the corresponding subject, and organize it into structured data, to support follow-up anonymization. This approach is divided into two tasks: PI identification and PI association. we respectively propose a sequence labeling model based on the RoBERTa-BiLSTM-CRF hybrid neural network and a PI association method based on the RoBERTa-HCR hybrid neural network to identify PI and organize it into structured data. The experimental results show that, compared with the benchmark model, RoBEERTa-BiLSTM-CRF has better performance; compared with the current Chinese coreference resolution model, the average F1-score value of RoBERTa-HCR is increased by 6%.

What Are We Missing?: Evaluating an Intimate Partner Violence Screening Program in a Pediatric Emergency Department.

Our study sought to explore and assess pediatric emergency department (ED) health care providers' knowledge, attitudes, and behaviors surrounding an existing intimate partner violence (IPV) screening program 4 years after initial implementation. We used anonymous electronic surveys and telephone interviews to obtain provider perspectives using a mixed-methods analysis. We used χ2 tests to analyze the quantitative survey results, and an unstructured qualitative approach to analyze the telephone interviews. We analyzed 141 survey responses, which correlated to a response rate of about 35% of all the providers reached, and 20 telephone interviews. Our results demonstrate that pediatric ED providers have some knowledge of our existing caregiver IPV screening program in the pediatric ED and universally endorse routine caregiver IPV screening, which both are suggestive of postimplementation cultural shifts. However, reported provider behaviors still indicate selective/targeted screening. For example, many providers reported screening males and nontraditional caregivers less often compared with female caregivers. Reported barriers potentially explaining such screening habits mirror those in existing literature: patient acuity, time, multiple caregivers being present, and more. Our study indicates that more research must be done to assess root causes of provider barriers to IPV screening in pediatric ED settings because trainings and a long-standing program do not seem to be changing screening practices. Addressing these issues may lead to truly sustainable and effective IPV screening programs in pediatric ED settings.

Estimating Social Preferences Using Stated Satisfaction: Novel Support for Inequity Aversion

In this paper, we use stated satisfaction to estimate social preferences: subjects report their satisfaction with payment-profiles that hold their own payment constant while varying another subject's payment. This approach yields significant support for the inequity aversion model of Fehr and Schmidt (1999). This model is among the most renowned in behavioral economics, positing a generalized aversion to inequality that is stronger when one's own payoff is lower–rather than higher–than others'; i.e., is stronger than guilt. While aggregate-level estimates based on revealed preferences in laboratory games have supported the model, the assumption that guilt is stronger than envy is often violated at the individual level. This paradox may be due to limitations of the revealed-preference approach. An advantage of avoiding games is that eliciting stated satisfaction is relatively easy to implement and is less prone to being confounded with motives like reciprocity; also the absence of tradeoffs between own and others' payoffs is cognitively less demanding for subjects. Our unstructured approach does not limit the expression of social preferences to inequity aversion, yet our methodology yields significant support for it. At the individual level, 86% of subjects exhibit at least as strong envy as guilt, and 76% (65%) of subjects weakly (strongly) adhere to the model. Our individual-level estimates are robust to changing the value of one's own constant payment and to changing the range of the other subject's payments. Methodologically, eliciting satisfaction can be an easy-to-implement complement to choice-based preference-measures in contexts other than social preferences that are of interest to economists.

Structured and Unstructured Robust Control for an Induction Motor

The indirect field-oriented control approaches for induction motors have recently gained more attention due to its use in trend areas, such as electromobility, electric vehicles, electric ships, and unmanned vehicles. This work studies the performance of two advanced control synthesized by the H8 norm as an alternative to the classical Proportional-Integral and Derivative controller. It will be assessed in terms of the performance against disturbance variations in the reference speed in the nominal conditions. The tuning of the parameters of these controllers must be defined of the stability and performance of the system and to increase their operation range frequency. An algorithm is proposed to reach a better shape of weighting func-tions. A numerical simulation will be shown where the advances in structured advanced controller synthesis with unstructured H8 controller is still the good election for the induction motor control. Unstructured controller approach shows still good robustness in performance and stability compared with the structured controller. Constraints imposed in structured controller is the main disadvantage to improve its robustness properties. However, compared with a conventional PID approach, the structured controller has shown quite good performance and can become in one of the most attractive approaches for practitioners.

The Integrated Prevention Model for Marijuana Smuggling in Land Border Region of Indonesia-Papua Nugini (Case: Muara Tami District, Jayapura City, Papua Province)

AbstractThis paper describes the need for an effective preventive model in preventing the smuggling of marijuana in the Indonesia- Papua New Guinea land border area in Muara Tami District, Jayapura Papua. The model applied so far is an outward looking model where this model implements an integrated cross-border inspection, supervision and security. The unstructured interview approach and the Delphi method were used in this study so that accurate data was obtained that in practice, the current model used still did not look professional and integrated, namely between cross-border service officers, Police and defense, Ondoaffi. (traditional leaders), religious leaders and border communities in the Indonesia-Papua New Guinea region. In addition, the integration between Ministries / Institutions related to programs and budgets in order to prevent marijuana smuggling in the Indonesia-Papua New Guinea border area in Muara Tami District, Jayapura City, Papua Province is also still weak. The reason of people who choose to smuggle marijuana is because they do not feel guilty and think that it is a profitable job with a strong social network, the behavior that neutralizes themselves that carrying marijuana is not a crime. In addition, the existence of problems such as geographic, demographic and disturbance from armed crime groups (OPM) that have not received serious action are also factors related to the above problems. Based on this background, this dissertation provides a strategic step, contained several policy recommendations that can strengthen this model so that it is expected to be maximized and more efficient than the previous model.Keywords: The Indonesian-Papua New Guinea Border Area, Rational considerations of profit and loss, Organized Crime, Social Networks, Neutralization and Delphi Methods, Marijuana Smuggling Crime Prevention Models

Strategies to improve communication in telementoring in acute care coordination: a scoping review.

Telementoring facilitates the coordination of advanced medical care in rural, remote or austere environments. Because the interpersonal element of telementoring has been relatively underexplored, we conducted a scoping review to identify strategies to improve communication in telementoring. Two independent reviewers searched all English-language articles in MEDLINE and Scopus from 1964 to 2017, as well as reference lists of relevant articles to identify articles addressing telementored interactions between health care providers. Search results were gathered in June 2017 and updated in January 2018. Identified articles were categorized by theme. We identified 144 articles, of which 56 met our inclusion criteria. Forty-one articles focused on improving dispatcher-directed cardiopulmonary resuscitation (CPR). Major themes included the importance of language in identifying out-of-hospital cardiac arrest and how to provide instructions to enable administration of effective CPR. A standardized approach with scripted questions was associated with improved detection of out-of-hospital cardiac arrest, and a concise script was associated with improved CPR quality compared to no mentoring, unscripted mentoring or more complex instructions. Six articles focused on physician-physician consultation. Use of a handover tool that highlighted critical information outperformed an unstructured approach regarding transmission of vital information. Nine articles examined telementoring in trauma resuscitation. A common theme was the need to establish an understanding between mentor and provider regarding the limitations of the provider and his or her environment. The available data suggest that standardization coupled with short, concise validated scripts could improve efficacy, safety and engagement. Improvements will require multidisciplinary input, practice and deliberate efforts to address barriers.

Lessons we never wanted to learn: pandemic as pedagogy

PurposeThe purpose of this paper is a reflective account in which one person who has been around long enough to see a good bit considers how COVID-19 might change the general contours of the world.Design/methodology/approachThis paper follows a broadly based and relatively unstructured approach, based on personal understandings and whatever rigor might have been gained by a life spent thinking about research design and the limits of methodology.FindingsThe opposite of what many others believe will happen is argued for. Things will change more than we wish. Most will change for the worse.Research limitations/implicationsAccounting research will have a role to play, but to have impact, this study will require that researchers adopt a much more critical perspective about capitalism and its consequences than before.Practical implicationsEveryone must do the best they can. Everyone must learn to accept the new and not rage to restore that which existed in before times.Social implicationsHarsher climate of interpersonal relations will be realized.Originality/valueThis paper is more about change than about accounting. A 30,000-foot level analysis that does not try to provide many examples. An effort to rise above the specifics that vary across the world.

On the design of potential turbine positions for physics-informed optimization of wind farm layout

Wind farm layout optimization is a critical step in the design of a wind energy project. In the literature, the potential turbine positions employed in the layout optimization are often obtained by discretizing the field using a Cartesian mesh. In this work, physical understanding is proposed to incorporate in the design of potential turbine positions. Specifically, the known knowledge, that a staggered arrangement is more efficient for extracting energy from wind than an aligned arrangement, is employed and implemented using the staggered mesh approach, the unstructured mesh approach and the sunflower mesh approach. Different mesh approaches are tested using two cases, i.e. case I, unidirectional uniform wind, and case II, uniform wind with variable wind direction. The optimal layout obtained from the staggered mesh approach performs the best for case I. For case II, the farm performance from different layouts is similar. The performance of the layouts under off-design conditions is also tested for case I. For all considered cases, the optimal layout obtained from the sunflower approach shows an overall good performance.

Exploring the views of forest industry companies on the long-term forestry development in Russia: A case study in Republic of Karelia

Forest industry companies are the chief exploiters of forest resources, and their day-to-day decisions and actions may have major implications for the sustainable development of forests, and for those who depend on them. Russian companies have a special place in this regard as they operate in the most forested country in the world and the local forest resources have considerable global effects. In this study, the concerns and views of an expert group from Russian wood harvesting companies in regard to forests and forestry development in the long term are scrutinized through a case study in Republic of Karelia, one of the main forest regions in Russia. The study employed a two-stage survey carried out by interviewing representatives from the companies in order to identify critical issues that they think will influence long-term forestry development. The survey combined an unstructured interview approach for the first stage and cumulative voting (CV) for the second. The identified data were summarized into a PESTE (Political, Economic, Social, Technological and Environmental) framework to obtain a general overview of the macro environments in the study area. The results show that the companies' views were mainly influenced by the technological, political and economic issues faced by the Russian forestry sector last decades, while social and environmental dimensions were considered of minor significance. The companies did not refer to the concept of sustainable development. Forestry was largely associated with the management of own business demands.

Comparing Structured and Unstructured Facilitation Approaches in Consultation Workshops: A Field Experiment

Facilitators must make important decisions when preparing for consultation workshops. One critical choice pertains to how much structure should be incorporated in a workshop and imposed on group discussions. Highly structured consultations may ensure efficiency and help produce specific outputs. However, too much structure may limit group discussion, creativity, or be ill received by participants. To examine the impacts of structure in a workshop consultation, we conducted a field experiment that compares structured and unstructured facilitation approaches in a workshop on participatory environmental monitoring. We randomized participants (n = 34) into two parallel sessions where they completed the same tasks of idea generation and prioritization but with contrasting facilitation approaches. We collected pre and post surveys to compare satisfaction between groups across a range of variables. We find that structured facilitation with small group discussions provide a modest yet consistent improvement over the unstructured facilitation approach. We also find that women and men had very different perceptions about the level of women’s participation in the session. Experimental research designs are feasible for learning about facilitation methods and testing best practices in public participation and consultations.

Unstructured Gridding for MODFLOW from Prior Groundwater Flow Models: A New Paradigm

This work introduces a new unstructured gridding approach relying on feedback from a previous groundwater flow model. All cells in a relatively coarse model using a rectilinear grid are recursively subdivided following a cell wise specific discharge-based indicator to generate quadtree, octree or Voronoï grids. This technique leverages the full potential of the latest MODFLOW engines. The suitability of this approach is demonstrated on challenging single and multilayered heterogeneous formations. The proposed method is straightforward to implement in existing software packages. It supports iterative updating of groundwater flow models from the legacy rectilinear to unstructured grids.

Canadian Cardiovascular Society Clinical Practice Update on the Assessment and Management of Syncope

Syncope is a symptom that occurs in multiple settings and has a variety of underlying causes, ranging from benign to life threatening. Determining the underlying diagnosis and prognosis can be challenging and often results in an unstructured approach to evaluation, which is ineffective and costly. In this first ever document, the Canadian Cardiovascular Society (CCS) provides a clinical practice update on the assessment and management of syncope. It highlights similarities and differences between the 2017 American College of Cardiology/American Heart Association/Heart Rhythm Society and the 2018 European Society of Cardiology guidelines, draws on new data following a thorough review of medical literature, and takes the best available evidence and clinical experience to provide clinical practice tips. Where appropriate, a focus on a Canadian perspective is emphasized in order to illuminate larger international issues. This document represents the consensus of a Canadian panel comprised of multidisciplinary experts on this topic with a mandate to formulate disease-specific advice. The primary writing panel wrote the document, followed by peer review from the secondary writing panel. The CCS Guidelines Committee reviewed and approved the statement. The practice tips represent the consensus opinion of the primary writing panel authors, endorsed by the CCS. The CCS clinical practice update on the assessment and management of syncope focuses on epidemiology, the initial evaluation including risk stratification and disposition from the emergency department, initial diagnostic work-up, management of vasovagal syncope and orthostatic hypotension, and syncope and driving.

SEMI-STRUCTURED DESIGN AND PROBLEM-BASED EXPERIENTIAL LEARNING IN A FIRST-YEAR BIOMEDICAL ENGINEERING LABORATORY COURSE

A first-year biomedical engineering laboratory course was created using a problem-based approach, introducing students to the interplay of engineering design and biology in biomedical engineering. Open-ended problems were central to each laboratory module, and were designed to enhance students’ development of high-order learning skills. Although the value of problem-based learning in engineering laboratory courses has been recognized, its implementation in the first-year engineering program presents unique challenges for students who are unfamiliar with the unstructured approach and who are in their early stages of developing discipline-specific knowledge. Immediate feedback scaffolding strategies, including interactive pre-laboratory assessments and team-based quizzes, were implemented in the second iteration of the course to support students’ achievement of learning outcomes, and to improve their perception of their learning experience in a problem-based laboratory. According to preliminary survey results, students attributed the value of problem-based laboratory activities to the acquisition of technical skills, engineering design skills, as well as the development of self-directed ability, and a growth mindset. Results from the second iteration of the course also revealed that students perceived the interactive pre-laboratory assessments and team-based quizzes to be highly valuable. Taken together, our study thus far has underlined the importance of immediate feedback as an effective scaffolding strategy for supporting semi-structured experiential learning in a first-year engineering laboratory course.

An unstructured big data approach for country logistics performance assessment in global supply chains

PurposeThe purpose of this study is to explore the potential for the development of a country logistics performance assessment approach based upon textual big data analytics.Design/methodology/approachThe study employs design science principles. Data were collected using the Global Perspectives text corpus that describes the logistics systems of 20 countries from 2006–2014. The extracted texts were processed and analysed using text analytic techniques, and domain experts were employed for training and developing the approach.FindingsThe developed approach is able to generate results in the form of logistics performance assessments. It contributes towards the development of more informed weights of the different country logistics performance categories. That said, a larger text corpus and iterative classifier training is required to produce a more robust approach for benchmarking and ranking.Practical implicationsWhen successfully developed and implemented, the developed approach can be used by managers and government bodies, such as the World Bank and its stakeholders, to complement the Logistics Performance Index (LPI).Originality/valueA new and unconventional approach for logistics system performance assessment is explored. A new potential for textual big data analytic applications in supply chain management is demonstrated. A contribution to performance management in operations and supply chain management is made by demonstrating how domain-specific text corpora can be transformed into an important source of performance information.