Expert Process Research Articles

Two Years of Experience and Methodology of Korean COVID-19 Living Clinical Practice Guideline Development.

In Korea, during the early phase of the coronavirus disease 2019 (COVID-19) pandemic, we responded to the uncertainty of treatments under various conditions, consistently playing catch up with the speed of evidence updates. Therefore, there was high demand for national-level evidence-based clinical practice guidelines for clinicians in a timely manner. We developed evidence-based and updated living recommendations for clinicians through a transparent development process and multidisciplinary expert collaboration. The National Evidence-based Healthcare Collaborating Agency (NECA) and the Korean Academy of Medical Sciences (KAMS) collaborated to develop trustworthy Korean living guidelines. The NECA-supported methodological sections and 8 professional medical societies of the KAMS worked with clinical experts, and 31 clinicians were involved annually. We developed a total of 35 clinical questions, including medications, respiratory/critical care, pediatric care, emergency care, diagnostic tests, and radiological examinations. An evidence-based search for treatments began in March 2021 and monthly updates were performed. It was expanded to other areas, and the search interval was organized by a steering committee owing to priority changes. Evidence synthesis and recommendation review was performed by researchers, and living recommendations were updated within 3-4 months. We provided timely recommendations on living schemes and disseminated them to the public, policymakers and various stakeholders using webpages and social media. Although the output was successful, there were some limitations. The rigor of development issues, urgent timelines for public dissemination, education for new developers, and spread of several new COVID-19 variants have worked as barriers. Therefore, we must prepare systematic processes and funding for future pandemics.

Fuzzy linguistic forecasting of the results of the implementation of regional socio-economic projects

The article is devoted to the problem of improving the intellectual digital support for managing the implementation of regional socio-economic projects, which are an effective mechanism for the development of regions. Given the high level of uncertainty in the description of the subject area, it is proposed to use expert technologies to assess the degree of achievement of the intermediate and target indicators of the project. L. Zadeh's linguistic modeling apparatus was used as the basis for intellectual tools for representing and processing expert judgments. A linguistic indicative-temporal-territorial model of the project has been built in the form of a set of linguistic variables and a system of fuzzy production rules linking these variables. At the same time, temporal and territorial linguistic variables reflect the time and place of measurement of project indicators, the incomplete correspondence of which determines the degree of reliability of the measured values of indicators. The use of the constructed system of indicative-temporal-territorial fuzzy production rules makes it possible to link the intermediate values of the indicators with the target values of the project indicators and thereby predict the possible outcomes of its implementation. For this, a fuzzy logic inference procedure based on the use of the Mamdani algorithm has been developed. Preliminary results of using a research prototype of an intelligent expert system for analyzing the intermediate results of the project stages and predicting its results may indicate the effectiveness of the proposed approach.

Cómo obtener mosaicos u orlas de personas en el Directorio EXIT [How to get tiles or mosaics of people in the EXIT Directory

Se detalla como obtener mosaicos de personas en el Directorio de Expertos en el Tratamiento de la Información (Directorio EXIT). La selección puede hacerse a partir de los miembros de un país, provincia, ciudad, institución y materia o especialidad. Es una opción muy interesante para recordar nombres de personas cuyo aspecto físico se conoce.

Development of Nursing Process Expert System for Android-based Nursing Student Learning

Development of Nursing Process Expert System for Android-based Nursing Student Learning

Efficient machine learning model to predict fineness, in a vertical raw meal of Morocco cement plant

Soft sensor enables computing parameters that can be physically impossible to measure. This work aims to develop a soft sensor for raw meal fineness in a vertical roller mill of a cement plant. In previous research, some key indicators of the process were ignored. It is well known that vertical raw meal is feeded with heterogenous material that impacts raw meal fineness, and therefore, can deteriorates prediction accuracy of the soft sensor. To deal with this constraint, one-year history of industrial data was exploited and processed by a robust multivariate outlier identification method, followed by process expert outlier verification. Then a particular attention was given to process and material quality parameters using a statistical method to test parameters significance on fineness based on data variance calculation. Eight process and four quality parameters were retained to develop robust nonlinear model using artificial neural network: Bayesian regularization and Levenberg Marquart, then compared with Support vector regression with different acquisition function and kernels to tune and select optimum model hyperparameters. The best model performance was obtained with the Bayesian regularization algorithm.

Hyperparameter selection for Discrete Mumford–Shah

This work focuses on a parameter-free joint piecewise smooth image denoising and contour detection. Formulated as the minimization of a discrete Mumford-Shah functional and estimated via a theoretically grounded alternating minimization scheme, the bottleneck of such a variational approach lies in the need to fine-tune their hyperparameters, while not having access to ground truth data. To that aim, a Stein-like strategy providing optimal hyperparameters is designed, based on the minimization of an unbiased estimate of the quadratic risk. Efficient and automated minimization of the estimate of the risk crucially relies on an unbiased estimate of the gradient of the risk with respect to hyperparameters. Its practical implementation is performed using a forward differentiation of the alternating scheme minimizing the Mumford-Shah functional, requiring exact differentiation of the proximity operators involved. Intensive numerical experiments are performed on synthetic images with different geometry and noise levels, assessing the accuracy and the robustness of the proposed procedure. The resulting parameter-free piecewise-smooth estimation and contour detection procedure, not requiring prior image processing expertise nor annotated data, can then be applied to real-world images.

Design and evaluation of ecological interface for Feedwater Deaerating Tank and Gas Stripper System based on cognitive work analysis

Abstract The investigation of nuclear power plants (NPPs) accidents in the past shows that most of the accidents mainly occur in unexpected events. In this study, in order to verify whether Ecological Interface Design (EID) improves the situational awareness of operators in NPPs, this paper first analyzes the system by using the first three stages of cognitive work analysis, and then applies EID to the operating interface of NPPs to develop an ecological interface. In order to make the test results more complete, an improved interface has also been developed. A process expert and six operators were invited to participate in our experiments to measure situational awareness. The results show that the situational awareness of ecological interfaces in unexpected events is significantly higher than that of traditional and advanced interfaces. The significance of this study is that EID, as a practical technology, can be widely used in operator control rooms to improve the ability of operators to solve unexpected events.

Empowering Women's Coconut Farmer Groups To Build Family Economic Resilience Based On Local Potential In Tidore Islands City

Coconut farmers' homes may have a poor economy or income since their goods rely solely on one primary commodity: copra and coconut grains. It can potentially upset economic circumstances since, as the price of copra and coconut falls, so does household income. As a result, help for coconut farmers, notably women farmer organizations, is required to boost the economic worth of their coconuts. For example, the economic value of coconut may be improved by producing various coconut-based goods so that farmers are not only reliant on copra prices. According to the survey findings and the identification of problems with the partners of the women's group Tani Igo Jaya, based in Jaya Village, Tidore Islands City, all members have encountered economic difficulties due to the drop-in copra prices. It was exacerbated by the fact that it occurred concurrently with the COVID-19 epidemic. As a result, most coconut growers refuse to process their coconuts into copra, and some coconuts go to waste. The issue is that partners lack expertise and abilities in processing or diversifying processed coconuts, although all components of the coconut fruit may be utilized to generate economic value. The solution that will be applied to partners is the transfer of science, technology, and skills for partners in processing their coconut harvests, as well as the provision of solid business management so that partners are not only reliant on copra. Furthermore, the identification of waste concerns from processed coconut fruit will be minimized since partners can employ coconut water, coconut pulp, and coconut fiber, which are presently considered waste but have promising economic value. This community service project is intended to create a new entrepreneurial group by exploiting possible sources of local raw materials available to partners, and it will directly benefit the economic resilience of coconut growers' homes. This community empowerment activity was successful in increasing partners' knowledge and skills in processing coconut fruit into nine products: coconut confectionery, shredded coconut (serundeng), coconut chips, sweet soy sauce, coconut jam, coconut milk, coconut oil, virgin coconut oil (VCO), and pots, as well as planting media made from coconut coir.

Research on the Key Success Factors for the Transformation of the Traditional Fishery to Recreational Fishery in Taiwan’s Outlying Islands

Outlying islands are affected by the environment and economy, and fishery resources are the first to experience these impacts. Therefore, it is necessary to actively and effectively transform traditional fisheries in outlying islands. This is the case in Penghu County (Penghu Islands), located on the outlying islands of Taiwan. The transformation to recreational fishery can increase the additional income of traditional fisheries during the fishing moratorium through the development of recreational fishery boats by fishermen. Recreational fishery means the fishery using fishing vessels for recreational purposes or for passengers to harvest aquatic organisms on the reef or to engage in sightseeing on the islets. Therefore, this study will explore the key factors for the successful route planning of fishermen who switch to recreational fishery boats to assist the fishermen in successfully transitioning and enabling recreational fishery to flourish. In the research, using the method of the Analytic Hierarchy Process (AHP) expert questionnaire, it was found that the key factors affecting the route planning of recreational fishery boats are “boat conditions”, “berthing conditions”, “operating environment”, and “sightseeing potential”. After the expert questionnaire, a weight comparison of each level was performed, and it was found that “operating environment” was the most important factor, followed by “tourism potential”. However, the key factors of the “natural environment” and “cultural environment” are more important under the influence of the “operating environment”. Under the influence of “tourism potential”, “attractiveness” is a key factor, as is the “accessibility” factor. In this study, the four main fishing ports in Penghu County were also used for empirical discussion. The study results showed that Magong Fishing Port was the first choice for transformation, followed by Chikan Fishing Port. The results of this study can be used as a reference for fishermen and officials in developing a subsidy scheme for fishing boat operation, and they can be used as a reference for transforming traditional fisheries in outlying islands into recreational fishing to develop recreational fishery boats and leisure tourism industries. This research can help fishermen to attach importance to the development of recreational fishing activities and promote the stable growth of the fishery industry environment.

Epidemic Question Answering: question generation and entailment for Answer Nugget discovery.

The rapidly growing body of communications during the COVID-19 pandemic posed a challenge to information seekers, who struggled to find answers to their specific and changing information needs. We designed a Question Answering (QA) system capable of answering ad-hoc questions about the COVID-19 disease, its causal virus SARS-CoV-2, and the recommended response to the pandemic. The QA system incorporates, in addition to relevance models, automatic generation of questions from relevant sentences. We relied on entailment between questions for (1) pinpointing answers and (2) selecting novel answers early in the list of its results. The QA system produced state-of-the-art results when processing questions asked by experts (eg, researchers, scientists, or clinicians) and competitive results when processing questions asked by consumers of health information. Although state-of-the-art models for question generation and question entailment were used, more than half of the answers were missed, due to the limitations of the relevance models employed. Although question entailment enabled by automatic question generation is the cornerstone of our QA system's architecture, question entailment did not prove to always be reliable or sufficient in ranking the answers. Question entailment should be enhanced with additional inferential capabilities. The QA system presented in this article produced state-of-the-art results processing expert questions and competitive results processing consumer questions. Improvements should be considered by using better relevance models and enhanced inference methods. Moreover, experts and consumers have different answer expectations, which should be accounted for in future QA development.

A policy cycle of electoral reform: comparing directly elected chief executives in Israel and Turkey

In studying electoral reforms, the democratic context is often a neglected variable. Israel and Turkey, at different times with different levels of democracy, have implemented a similar reform, the direct election of the chief executive. While there were similar justifications at the time of the introduction, the reforms then took on different dynamics. In Israel the reform was reversed, while in Turkey it became the centrepiece of further autocratisation. Adapting a framework of policy-analysis, the article explores similarities and differences in both cases. It argues that the democratic environment turns out as an important factor to explain the different trajectories of seemingly similar policy reforms in both cases. While the reverse reform in the Israeli case is linked to advantages in processing expert and civil society information, the trajectory in the Turkish case is based on the different power structure in the course of presidentialisation. Applying a comparative policy analysis to these cases of electoral reform, the article concludes that the democratic environment, that is, the degree of freely available information, helps explaining the different trajectories in both cases.

In Memoriam: Anil K. Bidani, MD.

In Memoriam: Anil K. Bidani, MD.

Blockchain Technology Application Maturity Assessment Model for Digital Government Public Service Projects

With the deepening application of blockchain technology, exaggerating its empowering effects has become common. In recent years, the rational assessment of the maturity of blockchain technology applications in digital projects in different fields has been the focus of attention and identified as the key to improving the implementation effect of various digital projects. Although some studies have obtained substantial research results on technology maturity and its derivative applications, which can be used to predict the overall trend of a technology or guide the implementation of the technology on the ground, few studies have evaluated the maturity of blockchain technology in combination with different application scenarios. Our study combines application scenarios and the technical characteristics of blockchain technology and proposes an evaluation system for blockchain technology application maturity consisting of five primary indicators, that is, key application requirements, data security, process complexity, application ecological completeness, and technical performance requirements, and their corresponding secondary indicators. In addition, we take digital government public service projects as application scenarios and use the analytic hierarchy process (AHP) entropy method and expert scoring method to determine the weights corresponding to each index in the assessment system and construct a blockchain technology application maturity assessment model. Moreover, we apply the model to ten typical digital government public service projects to conduct a comprehensive assessment and analysis. By comparing the indicator scores of the different projects, we analyze the project characteristics influencing blockchain technology application maturity and provide suggestions for applying “blockchain + digital government public services”.

Models of adaptive integration of weighted interval data in tasks of predictive expert assessment

The problem of improving the methodological and algorithmic support of the complexing process by developing models of adaptive redundant complexing of weighted interval data has been solved. The object of this study is the process of complexing interval data obtained from several independent sources; the subject is the algebraic methods of excessive complexing of weighted interval data. The relevance of the task is due to the severity of the problem of consolidating homogeneous data in order to obtain more accurate and relevant information about the object or process under study. Models have been developed that, unlike the existing ones, make it possible a posteriori to take into account the accuracy of experts at the preliminary stage of expert evaluation. A single analytical form of the model for processing weighted interval and point estimates with the possibility of structural and parametric tuning is proposed. It allows one to increase the degree of automation of processing expert assessments under conditions of interval uncertainty. Recommendations for the practical application of the proposed models have been formulated. Options for parametric configuration of preference functions were indicated depending on the characteristics of weighted interval estimates. The commonality of the limiting cases of the proposed models with previously known ones is proved. The example shows the shift of the integrated assessment to the side of more accurate assessments at the previous stage of source assessment. The adaptability of the proposed models is illustrated. At the same time, a slight, on average, about 10 %, expansion of the complexed interval relative to the primary ones was registered. The built models and algorithms can be used in automated expert systems, as well as in cascade models of information processing and compression.

The impact of participatory policy formulation on regulatory legitimacy: the case of Great Britain’s Office of Gas and Electricity Markets (Ofgem)

Energy markets policy in Great Britain has been largely delegated from elected representatives to a market regulator: the Office of Gas and Electricity Markets (Ofgem). Regulatory legitimacy requires due process and appropriate expertise to expose the regulator to democratic influence. As the legitimacy of regulatory participation processes start to be discussed more intensively in the European context, this timely article examines the relationship between the use of policy formulation tools and the resulting legitimacy gained by an independent market regulator. It employs a detailed case study analysing how participatory policy formulation tools – deliberative focus groups with members of the public, and stakeholder consultations – were used in energy markets policy formulation in Ofgem between 2007 and 2016. Through assessing the actors, venues, capacities and effects associated with selection and use of the tools, it finds there were inequalities of influence between different policy actors which posed a significant challenge to legitimacy.

Resilience organizing: a multilevel communication framework

Abstract This study advances communication-centered resilience theory by examining adaptive capacity of nonprofit networks impacted by Hurricane Harvey in 2017. Data show how formal structures set up conditions for adaptive/informal organizing. This highlights a quandary for disaster planning: improvising emerges from organizations having plans in place. Iterative processes between formal and informal structures expanded capacity, building a foundation for work processes to scaffold from individual to organizational to interorganizational networks. Yet some employees were personally vulnerable, revealing a multilevel dilemma: organizations were resilient even if employees were not. This study also theorizes time as an endogenous mechanism. As workers perceived less urgency, process experts broadened communication across levels, integrating more complex work processes. Resilience differed between organizations that lacked process experts, revealing their critical role across levels. Findings point to a policy-making dilemma: successful resilience processes undermine pressure on policy-makers to mitigate threats that necessitate improving resilience processes to begin with.

Validation of a modified questionnaire to assess Ukrainian Family Physicians’ readiness to implement the evidence-based screening recommendations into their clinical practice, using a mixed method study

BackgroundUkrainian Family Doctors' knowledge and readiness for the implementation of new guidelines recommendations into practice has to be evaluated and taken into consideration, meanwhile they often use the old protocols of annual checkups. This study aimed to perform a linguistic and cultural validation of Ukrainian adopted questionnaire designed on the German prototype “Readiness of general practitioners to recommend and implement evidence-based screening recommendations questionnaire”.MethodsThis was a mixed method study. The English version of the original German prototype questionnaire was translated into Ukrainian with forward–backward method. Additionally Ukrainian version was modified by including an extra questions about evidence based screening of cardiovascular risks, infectious diseases, type 2 diabetes mellitus, depression, and some old-fashioned annual checkups which are still commonly used in routine family doctors’ practice. During the face validation process, 10 practicing general practitioners assessed all the items in the questionnaire as adequately structured, grammatically correct, and understandable. During qualitative part of content validation process 11 experts found and corrected some grammatical errors, indicated that items of the questionnaire were comprehensible and related to Ukrainian culture. During the quantitative part of content validation process experts accessed 5 of 6 items as essential, relevant, and clear. Internal consistency of the items, assessed by using Cronbach’s alpha method was acceptable. To access how stable can be results provided by the questionnaire, test–retest reliability was performed, where 19 general practitioners filled in the same questionnaire twice over a period of two weeks.ResultsIn our study CVR > 0.79 and CVI > 0.59 were acceptable. The internal consistency was evaluated by using Cronbach’s alpha method and had to be above 0.7. According to the test–retest reliability results of weighted kappa and Cohen's kappa coefficients, test–retest agreement of the questionnaire was moderate for 29%, substantial for 38%, and almost perfect for 5% of the items (p ≤ 0.05). Kappa coefficients were not computed for 10% of items as there was no variability in the assessments.ConclusionsThe Ukrainian version of the questionnaire can be used for the assessment Ukrainian Family Doctor’s readiness to implement the evidence-based screening recommendations into their clinical practice.

A Classification Method for National Culture Propagation Using Deep Learning

This paper combines the artificial intelligence (AI) and deep leaning technologies to classify the spread of national culture. First, we use the Python language to build a crawler technology in order to obtain the sample data of national culture from authoritative websites. Then, we use the natural language processing (NLP) expertise to analyze and preprocess the text of national diversity. In this way, we realize vectorization and the feature word extraction of the text related to national cultural resources based on the doc2vec technology. The vectorized texts of national cultural resources are clustered based on the K-means clustering technique. Moreover, the elbow rule process is implemented to determine the optimal number of clustering clusters. Finally, the text association relationship of the national cultural resources is obtained. Moreover, this paper adopts the unsupervised training method, which can reveal the semantic information contained in the text of national cultural resources. This can also help us during the identification process of the category connection amongst the texts of national cultural resources and provide us with methodological support for the gathering, storing, and other smart services of enormous national cultural resources. The outcomes demonstrate that the correctness rate of the suggested algorithm is greater than the accuracy of the linear regression and can reach up to 80%.

Revisiting transplant immunology through the lens of single-cell technologies.

Solid organ transplantation (SOT) is the standard of care for end-stage organ disease. The most frequent complication of SOT involves allograft rejection, which may occur via T cell– and/or antibody-mediated mechanisms. Diagnosis of rejection in the clinical setting requires an invasive biopsy as there are currently no reliable biomarkers to detect rejection episodes. Likewise, it is virtually impossible to identify patients who exhibit operational tolerance and may be candidates for reduced or complete withdrawal of immunosuppression. Emerging single-cell technologies, including cytometry by time-of-flight (CyTOF), imaging mass cytometry, and single-cell RNA sequencing, represent a new opportunity for deep characterization of pathogenic immune populations involved in both allograft rejection and tolerance in clinical samples. These techniques enable examination of both individual cellular phenotypes and cell-to-cell interactions, ultimately providing new insights into the complex pathophysiology of allograft rejection. However, working with these large, highly dimensional datasets requires expertise in advanced data processing and analysis using computational biology techniques. Machine learning algorithms represent an optimal strategy to analyze and create predictive models using these complex datasets and will likely be essential for future clinical application of patient level results based on single-cell data. Herein, we review the existing literature on single-cell techniques in the context of SOT.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00281-022-00958-0.

HOTS-Based Worksheet in English Learning Activity for Eight Grade Students of Junior High School

Teachers should be able to develop learning activities that offer meaningful learning to students and improve students' English skills. Higher Order Thinking Skills, or HOTS, are the current solution to support the development of student's abilities. This study has the purpose to develop a students' worksheet in a form of a supplementary book by promoting HOTS for eighth-grade students to implement curriculum 2013. The book is for the eighth grade in the second semester of junior high school students. This research implements D&D (Design and Development research) methods with four steps which are Analysis, Design, Development, and Evaluation. The researcher employed random sampling and participants in this study were eighth-grade Junior High School students. In collecting the data, the researcher conducted learning process observation, teacher interview, document analysis, and expert judgment. The result of the study found that the HOTS-Based Worksheet can use as a guide for leading and educating students when reading books. The use of this book makes learning more fun, interesting, and visually appealing for students. This worksheet can also help students improve their English language skills and critical thinking skills. The expert evaluation findings show that this product falls into the category of "very good" media. It is hoped that the product will be giving advantages for both students and teachers to improve the quality of English teaching and learning process.