Set Of Experts Research Articles

Community detection and co-author recommendation in co-author networks

With the increasing complexity of scientific research and the expanding scale of projects, scientific research cooperation is an important trend in large-scale research. The analysis of co-authorship networks is a big data problem due to the expanding scale of the literature. Without sufficient data mining, research cooperation will be limited to a similar group, namely, a “small group”, in the co-author networks. This “small group” limits the research results and openness. However, the researchers are not aware of the existence of other researchers due to insufficient big data support. Considering the importance of discovering communities and recommending potential collaborations from a large body of literature, we propose an enhanced clustering algorithm for detecting communities. It includes the selection of an initial central node and the redefinition of the distance and iteration of the central node. We also propose a method that is based on the hilltop algorithm, which is an algorithm that is used in search engines, for recommending co-authors via link analysis. The co-author candidate set is improved by screening and scoring. In screening, the expert set formation of the hilltop algorithm is added. The score is calculated from the durations and quantity of the collaborations. Via experiments, communities can be extracted, and co-authors can be recommended from the big data of the scientific research literature.

Nurses confronting the coronavirus: Challenges met and lessons learned to date

Registered nurses are an essential workforce group across the globe. They use their expertise and skill sets every day in clinical practice to protect, promote, and advocate on behalf of patients and families under their care. In this article we discuss the physical, emotional, and moral stresses that nurses are experiencing in their day-to-day practice settings created by the novel coronavirus. We consider the demands placed on nurses by unexpected patient surges within hospital environments and inadequate personal protective equipment and other critical resources, challenging nurses’ ability to meet their professional and ethical obligations. We also share our thoughts on supporting nurses and others now, and ideas for needed healing for both individuals and organizations as we move forward. Finally, we argue for the need for substantive reform of institutional processes and systems that can deliver quality care in the future when faced with another devastating humanitarian and public health crises.

Changing Perceptions, Changing Lives – Promoting Intercultural Competence and Ethical Creativity through Advertising

Few phenomena have incited as much passion as the unravelling of ‘creativity’ and few disciplines have brought about so many controversial expressions of it as advertising. In the bio-cultural framework of Intercultural Competence® the co-emergence of ‘ethical creativity’ is conceived to be pivotal for intercultural expertise. We suspect that interculturally competent individuals more habitually engage in ethical creativity, that is, the co-activation of a creative mindset and a benevolent moral mindset informed by a difference-oriented mindset towards the ‘familiar other’ as well as the ‘unfamiliar other’.In this framework, action is directly linked to perception, which, in turn, is influenced and shaped by the active creative mindset. To analyse ethical creativity as an intersecting process with the development of intercultural expertise, we designed and piloted a qualitative perceptuo-cognitive experiment including various advertising items to document the differences in perception of 34 leaders of small and medium enterprises and nongovernmental organisations (NGOs). The experiment consisted of 40 affective and culturalised visual items analysed with SR Research’s Data Viewer software. The eyetracking data were translated and clustered into gaze types and combined with the response patterns from the questionnaire for analysis. ‘Ethical creativity’ is regarded as a dynamic process emerging through the co-activation of benevolent, moral mindsets. A specific perceptual architecture emerges from the convergence of various sets of expertise. The process of becoming interculturally competent and being able to enact ethical creativity is linked to advertising campaigns. Such interactions (of perception with activation of mindsets) have the potential to profoundly shape the behaviours and understandings of consumers.

A new approach for heterogeneous linguistic failure mode and effect analysis with incomplete weight information

Failure mode and effects analysis (FMEA) is an important technique in safety and reliability analysis, which has been widely used to identify and eliminate known or potential failure. In the process of evaluating failure modes (FMs), experts usually adopt different types of linguistic information to reflect their judgments, and the weights of experts or criteria are often incompletely known. This study aims to develop a novel approach to solve heterogeneous linguistic FMEA problem, in which the ratings of FMs are described by different types of linguistic information, and the information about the importance of experts and criteria is incomplete. Firstly, we propose a linguistic distribution assessment Shapley Choquet ordered averaging (LDASCOA) operator, and discuss some properties of the operator, such as idempotency, monotonicity, boundary and commutativity. Secondly, we present a new idea to convert different types of linguistic information to linguistic distribution assessments (LDAs). Thirdly, to obtain collective linguistic distribution assessment decision matrix and necessary weights, we construct a model to determine the optimal fuzzy measures on expert set with respect to each criterion considering the interactions among elements in the expert set. Fourthly, a new approach to determine the priority of FMs is proposed by defining linguistic distribution assessment ideal variate (LDAIV) and linguistic distribution assessment nadir variate (LDANV), as well as calculating the relative correlation coefficient of each failure. Finally, an illustrative example is given to demonstrate the calculation process of the developed approach, and the advantages are verified by comparing the evaluation result of the developed approach with that of existing methods.

Effects of public procurement of R&D on the innovation process: evidence from the UK small business research initiative

PurposeThe study aims to investigate how pre-commercial procurement (PCP) influences the activities, capabilities and behaviours of actors participating in the innovation process. Unlike much of PCP research underpinned by a market failure theoretical framework that evaluates the additionality of innovation inputs and outputs, this paper focusses on the role and capacity of PCP in addressing systemic failures impeding the process of innovation.Design/methodology/approachPCP effects on the innovation process were studied through a qualitative study of the UK small business research initiative (SBRI) programme. Data collection comprised 33 semi-structured interviews with key informants within 30 organisations and analysis of 80-plus secondary data sources. Interviewees included executives of technology-based small businesses, managers within public buying organisations and innovation policymakers and experts.FindingsThe UK SBRI improves connectivity and instigates research and development (R&D) related interactions and cooperation. Through securing government R&D contracts, small firms access relevant innovation ecosystems, build up their knowledge and capabilities and explore possible routes to market. Public organisations use the SBRI to connect to innovative small firms and access their sets of expertise and novel ideas. They also learn to appreciate the strategic role of procurement. Nonetheless, SBRI-funded small business face commercialisation and innovation adoption challenges because of institutional constraints pertaining to rules, regulations and public-sector norms of conduct.Research limitations/implicationsThe study contributes to existing PCP research by demonstrating innovation process-related effects of PCP policies. It also complements literature on small business-friendly public procurement measures by highlighting the ways through which PCP, rather than commercial procurement procedures, can support the development of small businesses other than just facilitating their access to government (R&D) contracts.Social implicationsThe study identifies several challenge areas that policymakers should address to improve the implementation of the UK SBRI programme.Originality/valueThe study demonstrates the effects of PCP on the activities, capabilities and behaviours of small businesses and public buying organisations involved in the innovation process.

Decision-Making Method Based on Fuzzy N-Soft Expert Sets

In this paper, we develop two novel hybrid models, namely N-soft expert set model and fuzzy N-soft expert set model. An N-soft expert set model is the combination of N-soft sets with soft expert sets, and a fuzzy N-soft expert model studies the fuzziness of N-soft expert sets. Further, we illustrate our hybrid models with daily life examples involving uncertainties in data. Moreover, we describe some fundamental operations, including intersection, union, complement, OR and AND. Further, we discuss three practical applications of proposed methods in decision making from which third application is a real case study (that is, selection of a place for a telecommunication tower). Algorithms of our proposed models prove their effectiveness and validity. Finally, we present a comparative analysis of our proposed models with some existing models.

Unravelling the panel contribution upon peer review evaluation of numerous, unstructured and highly interdisciplinary research proposals

Abstract In this study, we analyze the two-phase bottom-up procedure applied by the Future and Emerging Technologies Program (FET-Open) at the Research Executive Agency (REA) of the European Commission (EC), for the evaluation of highly interdisciplinary, multi-beneficiary research proposals which request funding. In the first phase, remote experts assess the proposals and draft comments addressing the pre-defined (by FET-Open) evaluation criteria. In the second phase, a new set of additional experts (of more general expertise and different from the remote ones), after cross reading the proposals and their remote evaluation reports, they convene in an on-site panel where they discuss the proposals. They complete the evaluation by reinforcing per proposal and per criterion one or another assessment, as assigned remotely during the first phase. We analyze the level of the inter-rater agreement among the remote experts and we identify its relative correlation with the funded proposals resulted after the end of the evaluation. Our study also provides comparative figures of the evolution of the proposals` scores during the two phases of the evaluation process. Finally, by carrying out an appropriate quantitative and qualitative analysis of all scores from the seven past cut-offs, we elaborate on the significant contribution of the panel (the second phase of the evaluation) in identifying and promoting the best proposals for funding.

Personality on the Hill: Expert Evaluations of U.S. Senators’ Psychological Traits

Long recognized for the diverse array of personalities it hosts, the U.S. Senate constitutes an institution in which individual psychological differences among its members carry significant potential consequences. Unfortunately, studying those individual differences is no easy task. This study introduces a new approach for doing so. Specifically, the study develops Big Five trait ratings for eighty-seven U.S. senators, with data drawn from assessments provided by a set of experts, U.S. Senate insiders. The paper explains the rationale for use of expert evaluations, offers evidence regarding the reliability and validity of the resulting measures, and explores possible relationships between personality and ten aspects of Senate behavior.

Ten recommendations for supporting open pathogen genomic analysis in public health.

Increasingly, public-health agencies are using pathogen genomic sequence data to support surveillance and epidemiological investigations. As access to whole-genome sequencing has grown, greater amounts of molecular data have helped improve the ability to detect and track outbreaks of diseases such as COVID-19, investigate transmission chains and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of whole-genome sequencing also poses new challenges for public-health agencies that must adapt to support a new set of expertise, which means that the capacity to perform genomic data assembly and analysis has not expanded as widely as the adoption of sequencing itself. In this Perspective, we make recommendations for developing an accessible, unified informatic ecosystem to support pathogen genomic analysis in public-health agencies across income settings. We hope that the creation of this ecosystem will allow agencies to effectively and efficiently share data, workflows and analyses and thereby increase the reproducibility, accessibility and auditability of pathogen genomic analysis while also supporting agency autonomy.

Open Challenges of Blind People Using Smartphones

ABSTRACT Blind people face significant challenges when using smartphones. The focus on improving nonvisual mobile accessibility has been at the level of touchscreen access. Our research investigates the challenges faced by blind people in their everyday usage of mobile phones. In this article, we present a set of studies performed with the target population, novices and experts, using a variety of methods, targeted at identifying and verifying challenges; and coping mechanisms. Through a multiple methods approach we identify and validate challenges locally with a diverse set of user expertise and devices, and at scale through the analyses of the largest Android and iOS dedicate forums for blind people. We contribute with a prioritized corpus of smartphone challenges for blind people, and a discussion on a set of directions for future research, which tackle the open and often overlooked challenges.

Knowledge discovery from remote sensing images: A review

AbstractThe development of Earth observation (EO) technology has made the volume of remote sensing data archiving continually larger, but the knowledge hidden in massive remote sensing images has not been fully exploited. Through in‐depth research on the artificial intelligence (AI)‐based knowledge discovery approaches from remote sensing images, we divided them into four typical types according to their development stage, including rule‐based approaches, data‐driven approaches, reinforcement learning approaches, and ensemble methods. The basic principles, typical applications, advantages, and disadvantages have been detailed for commonly used algorithms within each category. Conclusions include the following: (a) Rule‐based, data‐driven and reinforcement learning algorithms form a trilogy from knowledge to data, and to capabilities. (b) Rule‐based data mining algorithms can provide prior knowledge for data‐driven approaches, the knowledge discovered by data‐driven models can be as an important complement to expert knowledge and rule sets, and reinforcement learning approaches can effectively make up for the lack of training samples or small training sample in data‐driven models. (c) The traditional data‐driven machine learning approaches and their ensemble methods are the current and may be the future mainstream methods for large regional and even global scale long time series remote sensing data mining and analysis, and improving their computing efficiency is the key research direction. (d) Deep learning, deep reinforcement learning, transfer learning, and an ensemble approach of the three may be the main means for small‐area scope, short time series, and key geoscience information extraction from remote sensing images within a long time of the future.This article is categorized under:Algorithmic Development > Spatial and Temporal Data MiningFundamental Concepts of Data and Knowledge > Big Data MiningTechnologies > Artificial Intelligence

Workplace Experience of International Students in Australia

For the past three years over 400,000 international students have enrolled annually to study in higher education contexts in Australia (Australian Government, 2019). The extensiveness of international student enrolments has been equalled to Australia’s third highest export industry after coal and iron ore (Grewal & Blakkarly, 2017). Given the significance of international students it is important that Australian universities find effective and culturally-appropriate ways to support this cohort. One such area needing support is work experience as many study programs that international students undertake include compulsory or elective courses involving assessed experiences in professional contexts. Degrees such as business, education, engineering, health including nursing and psychology all require students to successfully complete workplace experiences in order to graduate. It is critical that international students are supported before, during and after workplace components of study as the International Student Barometer indicated that international students desire quality career advice, work experience and subsequently employment as a result of their studies (Garrett, 2014).

Grant reviewer perceptions of the quality, effectiveness, and influence of panel discussion

BackgroundFunding agencies have long used panel discussion in the peer review of research grant proposals as a way to utilize a set of expertise and perspectives in making funding decisions. Little research has examined the quality of panel discussions and how effectively they are facilitated.MethodsHere, we present a mixed-method analysis of data from a survey of reviewers focused on their perceptions of the quality, effectiveness, and influence of panel discussion from their last peer review experience.ResultsReviewers indicated that panel discussions were viewed favorably in terms of participation, clarifying differing opinions, informing unassigned reviewers, and chair facilitation. However, some reviewers mentioned issues with panel discussions, including an uneven focus, limited participation from unassigned reviewers, and short discussion times. Most reviewers felt the discussions affected the review outcome, helped in choosing the best science, and were generally fair and balanced. However, those who felt the discussion did not affect the outcome were also more likely to evaluate panel communication negatively, and several reviewers mentioned potential sources of bias related to the discussion. While respondents strongly acknowledged the importance of the chair in ensuring appropriate facilitation of the discussion to influence scoring and to limit the influence of potential sources of bias from the discussion on scoring, nearly a third of respondents did not find the chair of their most recent panel to have performed these roles effectively.ConclusionsIt is likely that improving chair training in the management of discussion as well as creating review procedures that are informed by the science of leadership and team communication would improve review processes and proposal review reliability.

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

In this paper, we study Reinforcement Learning from Demonstrations (RLfD) that improves the exploration efficiency of Reinforcement Learning (RL) by providing expert demonstrations. Most of existing RLfD methods require demonstrations to be perfect and sufficient, which yet is unrealistic to meet in practice. To work on imperfect demonstrations, we first define an imperfect expert setting for RLfD in a formal way, and then point out that previous methods suffer from two issues in terms of optimality and convergence, respectively. Upon the theoretical findings we have derived, we tackle these two issues by regarding the expert guidance as a soft constraint on regulating the policy exploration of the agent, which eventually leads to a constrained optimization problem. We further demonstrate that such problem is able to be addressed efficiently by performing a local linear search on its dual form. Considerable empirical evaluations on a comprehensive collection of benchmarks indicate our method attains consistent improvement over other RLfD counterparts.

The Medical Library Association Data Services Competency: a framework for data science and open science skills development.

Increasingly, users of health and biomedical libraries need assistance with challenges they face in working with their own and others’ data. Librarians have a unique opportunity to provide valuable support and assistance in data science and open science but may need to add to their expertise and skill set to have the most impact. This article describes the rationale for and development of the Medical Library Association Data Services Competency, which outlines a set of five key skills for data services and provides a course of study for gaining these skills.

Cost control mechanism as procurement selection decision matrix for Malaysian infrastructure projects

Malaysia was enumerated as the realm that retains a high quality of infrastructure facilities among the other ASEAN countries, and the number of infrastructure projects is progressively developed to offers a virtuous cordiality to the citizen. Inevitably, the infrastructure projects are barely devoted to the complex project selection decision phase where the procurement represents the suave configuration of the projects. However due to the difficulty in analyzing an assorted variety of procurement system afford by inexperienced decision maker the procurement route often unkempt the cost related dynamic. Regularly, the decision based on narrow consideration of cost and project quality overestimated in within a short period of construction. Even worst, there is partially public discourse on the cost control elements towards the disputable project procurement selection, which reflects the lesson learnt on the previous infrastructure project has mismanaged to provide a municipal cost precaution. Prior to that, the research objective is to identify the relationship in between the cost control mechanism and project procurement selection decision in infrastructure projects. The adoption of quantitative method and analysis applies in this research among the infrastructure expert settings. The output from the methods disclose that the cost control acquires a strong correlation in the project procurement selection decision equation with project risk, capital resources, alliance requirement based, changes of policy, fluctuation of inflation rates, labor cost, material cost, robust feasibility studies as a driver to an efficacious project procurement assortment verdict.

Application of Decision Making Problem in Bipolar Fuzzy Soft Expert Set

Application of Decision Making Problem in Bipolar Fuzzy Soft Expert Set

Dialogic Pathways to Manage Uncertainty for Productive Engagement in Scientific Argumentation

Scientific knowledge is advanced because scientists manage uncertainty. Although managing uncertainty is an essential practice of science, transferring it from expert settings to K–12 classrooms is problematic because, understandably, students are not familiar with the intentions of scientists. Few studies have explored learning science as an enterprise of uncertainty management. This longitudinal case study, grounded in ethnographic microanalysis of interaction, examines dialogic pathways for the dynamics of authority and accountability between students and teachers as a mechanism to understand how uncertainty gets raised and managed through resources related to the epistemic understanding of argument. The data sources include 15 videotaped fifth-grade, whole class discussions over a 20-week period. Students obtained peer feedback through discussions focused on group presentations of arguments regarding the scientific concepts of the ecosystem, the human body, and the day and night cycle. As time passed and as opportunities for students to engage in managing uncertainty increased, the dialogic pathways moved away from teacher-scaffolded to serpentine and to student-led. Results indicate that elementary school students are able to engage in uncertainty management, yet they need support from the teacher to know how to use resources effectively. Student development of scientific practices and knowledge may depend on teachers knowing when to authorize and hold students accountable as they work to resolve their uncertainty, learning how to interpret data as evidence, and using resources productively. A schematic model is conceptualized regarding the tensions between authority and accountability that shape the three dialogic pathways to manage uncertainty.

TEACHER CHARACTERISTICS: WHAT DO EFL PRE-SERVICE TEACHERS EXPECT?

Desirable characteristics of TEFL (Teacher of English as a Foreign Language) have recently presented a major concern for researchers, particularly in the realm of teacher education. However, no matter how large the number of research projects conducted in the field is, very few ever investigated the perspective of pre-service teachers. This mixed-method research was then conducted to identify characteristics of a good TEFL, as perceived by pre-service teachers. Participants were 117 students at Faculty of English Language Teacher Education (FELTE), University of Languages and International Studies (ULIS), Vietnam National University Hanoi (VNU), who were being trained to be English teachers. Self-report questionnaire and semi-structured interviews were employed to collect quantitative and qualitative data respectively. As indicated by the results, remarkable pedagogical skills and excellent content knowledge are highly expected for TEFL. Further qualitative analysis shows that this ideal image stems from pre-service teachers’ conception of TEFL’ roles as transmitters of knowledge, and that teaching is considered a profession with certain sets of expertise required. Overall, the research has demonstrated FELTE pre-service teachers’ expectations of teacher qualities, which to some extent, also revealed their didactic beliefs. These findings are hoped to offer implications for both student teachers and trainers working in EFL teacher education.

A novel approach to extended fuzzy TOPSIS based on new divergence measures for renewable energy sources selection

In recent years, the selection of appropriate renewable energy sources is an extremely significant issue that affects the environmental development and economic growth. To tackle the concern, various authors have concentrated on preferring desirable energy source(s) adopting decision-making approaches under different fuzzy sets methods. In this regard, in the present study, a new divergence measure is proposed for ranking and choosing the renewable energy sources in multi-criteria decision-making problems based on fuzzy TOPSIS, and it is compared to some existing methods. Then, a set of experts related to renewable energy sources is selected to evaluate possible alternatives amongst conflicting criteria. Moreover, the fuzzy decision matrix and criteria weights are measured using linguistic values that are transformed into fuzzy values. Furthermore, the weight of each energy source decision expert is evaluated by the proposed method. Next, the importance of criteria is computed by an extensive maximizing deviation method inspired by fuzzy divergence measure. Finally, the problem of choosing a renewable energy source is considered to show the thorough execution process of the introduced method. The proposed method’s strength lies in its capability of providing effective solutions where there is a shortage of quantitative information.