Bibliographic Network Research Articles

A BIBLIOMETRIC ANALYSIS OF ENGINEERING EDUCATION IN THE METAVERSE

The Metaverse is a persistent and shared digital environment that blends physical and virtual reality, allowing for advanced multisensory interactions. Its acceptance has grown significantly since the COVID-19 pandemic. Nevertheless, despite its potential benefits for education, there are notable gaps in assessing learning processes within the Metaverse, especially concerning legal limitations and government oversight. This study aims to enhance the educational experience by promoting innovative, interactive, and engaging learning environments in various engineering disciplines, thereby equipping students with the skills necessary for success in a rapidly evolving technological landscape.This paper investigates the use of the Metaverse in engineering education through bibliometric analysis to identify key trends, challenges, and opportunities. By employing advanced tools like Publish or Perish and VOSviewer, the study analyzes bibliographic networks and statistical data to map the scholarly landscape and impact of this technology. The bibliometric analysis offers quantitative insights into research trends, citation counts, and author influence, which are presented in tables and charts for better visualization. This paper aim to enhance our understanding of how digital and immersive technologies are reshaping educational practices and boosting student engagement, motivation, and outcomes. The analysis underscores the importance of ongoing research and investment in the Metaverse as a vital resource for contemporary education, especially in engineering disciplines that thrive on interactive and hands-on learning environments. This research, despite certain limitations, lays important groundwork for understanding how the Metaverse can transform engineering education. By thoroughly analyzing and delineating the current landscape, it seeks to provide valuable insights that will guide future investigations and practical applications.

Inductive Meta-Path Learning for Schema-Complex Heterogeneous Information Networks.

Heterogeneous Information Networks (HINs) are information networks with multiple types of nodes and edges. The concept of meta-path, i.e., a sequence of entity types and relation types connecting two entities, is proposed to provide the meta-level explainable semantics for various HIN tasks. Traditionally, meta-paths are primarily used for schema-simple HINs, e.g., bibliographic networks with only a few entity types, where meta-paths are often enumerated with domain knowledge. However, the adoption of meta-paths for schema-complex HINs, such as knowledge bases (KBs) with hundreds of entity and relation types, has been limited due to the computational complexity associated with meta-path enumeration. Additionally, effectively assessing meta-paths requires enumerating relevant path instances, which adds further complexity to the meta-path learning process. To address these challenges, we propose SchemaWalk, an inductive meta-path learning framework for schema-complex HINs. We represent meta-paths with schema-level representations to support the learning of the scores of meta-paths for varying relations, mitigating the need of exhaustive path instance enumeration for each relation. Further, we design a reinforcement-learning based path-finding agent, which directly navigates the network schema (i.e., schema graph) to learn policies for establishing meta-paths with high coverage and confidence for multiple relations. Extensive experiments on real data sets demonstrate the effectiveness of our proposed paradigm.

The role of artificial intelligence in sustainable water management in Asia: a systematic literature review with bibliographic network visualization

The role of artificial intelligence in sustainable water management in Asia: a systematic literature review with bibliographic network visualization

Bibliometric Analysis of the 100 Most-Cited Articles on the Methods of Shade-Matching in Dentistry.

The purpose of this bibliometric analysis is to identify the 100 most cited articles and delve into citation metrics to gain insights into the evolving trends in shade-matching methods in dentistry. Following PRISMA guidelines, two reviewers conducted a structured search in Scopus using keyword-based search strings. The top 100 articles were selected based on predefined criteria, and their bibliometric data were extracted. Harzing's Publish Or Perish and VOSviewer were used to generate the bibliographic network. Between 1989 and 2017, the top 100 articles were published and obtained citations ranging from 560 to 48. Twenty-eight articles received over 100 citations, deemed classic. The Journal of Prosthetic Dentistry and the United States of America were the primary contributors. In-vitro experimental studies employing restorative material samples were prevalent, with spectrophotometers being the favored method of color analysis. Using Python, Spearman's correlation coefficient resealed positive correlations between citation count and age of publication (r = 0.16, p = 0.12) and between citation count and the impact factor of the journal (r = 0.35, p < 0.05). However, a negative correlation was observed between citation density and age of publication (r = -0.46, p < 0.05). This study demonstrated a significant upward trajectory of citation count in shade-matching in dentistry, reflecting high-quality scientific contributions.

Evolutionary Stress Detection Framework through Machine Learning and IoT (MLIoT-ESD)

Background: Life nowadays is full of stress due to lifestyle changes and the modernera race. Almost everyone around us is suffering from stress and anxiety. Mostly, stress identification is done by medical practitioners in a very late stage in which suitable help measures cannot be provided and hence result in suicides or early age deaths due to cardiac arrest, etc. One major reason behind the delay is the time required in stress identification by traditional approaches, and above that, the amount of time and financial support expected is always not feasible to be available. Hence, in this paper, we proposed an evolutionary research framework for stress identification by the usage of both machine learning and IoT. Here, we also conducted a pilot study on 83 records available over the decade since 2014 using PRISMA guidelines, and a bibliographic network visualization was also performed using VOS viewer. Objectives: This study aimed to develop a stress detection framework using Machine Learning and the Internet of Things (IoT) as technology advanced over a decade. Methods: More than 80 research papers from honorable repositories like Scopus and Web of Science were gathered according to the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020, and the VOSviewer tool was further applied to construct the bibliographic depictions. Various datasets and methods used over ten years with their performance were also discussed. Results: This research was conducted to gather various types of stressors, the impact of various Machine Learning and IoT algorithms and concepts on various datasets and their respective results. Conclusion: Various available datasets and results with multiple algorithms were discussed in a crisp tabular form for better understanding. A methodology based on an amalgamation of Machine Learning and IoT was also proposed due to various research gaps available so that stress detection could be done in a cost-effective way.

At a Crossroads: Cataloguing Policy and Practice in Australian Libraries

ABSTRACT A survey of cataloguing and metadata policy and practice across Australian libraries was conducted as a follow-up on the author’s 2013 survey. Responses were collected from 86 libraries, including over half the country’s state and university libraries, as well as from 27 public library networks and 31 other types of library. On average, the libraries were spending 27 hours of staff time on cataloguing, although many more libraries reported a decline in cataloguing time than an increase. This trend was due to acquisitions being increasingly covered by record copy, and to competing demands on staff time, with retiring cataloguers not always being replaced. Nevertheless, large amounts of cataloguing, including original cataloguing, are still being performed by professional staff, with increasing attention being paid to making bibliographic access more culturally inclusive. On the other hand, libraries are presently relying on their bibliographic networks to publish their metadata as linked data, and hardly any are planning to move to BIBFRAME, while RDA’s ‘official toolkit’ is also proving problematic for some libraries. It is suggested that cataloguing in Australian libraries may be prioritised more if their metadata were made more discoverable and more usable by addressing the shortcomings of current systems and standards.

Industry 5.0's pillars and Lean Six Sigma: mapping the current interrelationship and future research directions

PurposeIn the evolving landscape of Industry 5.0 (I5.0), which emphasises sustainability, human-centricity and resilience, mapping the current interrelationship and future research directions, the role of Lean Six Sigma (LSS) methodology remains underexplored. Our study addresses this gap by examining the potential of LSS to support I5.0 while identifying areas for further investigation.Design/methodology/approachThis study's multifaceted approach, which includes systematic literature review (SLR), bibliographic network analysis (BNA) and expert validation (EV), provides a holistic exploration of the interaction between LSS and I5.0 as the basis for well-founded conclusions.FindingsThe analysis yields several valuable insights. Firstly, it demonstrates the absence of a direct link between LSS and I5.0. Secondly, the substantial body of literature analysed establishes connections between LSS and its pillars. Thirdly, the analysis identifies points of intersection, difference and similarity between LSS and I5.0, highlighting the potential of LSS to facilitate implementation of I5.0 through its proven methodologies, continuous improvement culture, risk management, error learning, human–machine collaboration and training and skill development.Originality/valueThis study pioneers the effort to realise the latent potential of LSS in the context of I5.0. Its systematic identification of the synergies between these paradigms fills a critical gap in the literature and gives policymakers, managers and researchers a guide for informed decision-making to maximise the benefits of I5.0 for individuals, companies, society and the planet.

Weighted degrees and truncated derived bibliographic networks

Weighted degrees and truncated derived bibliographic networks

Comparative analysis of the capabilities of WoS and eLibrary for analyzing bibliographic networks

This article presents a comparative analysis of two major scientific publication databases: Web of Science Core Collection and eLibrary – to identify their differences and unique opportunities for exploration of bibliographic networks of Russian scientific authors. Current shortage of tools and approaches for collection, processing and analysis of bibliographic data in the Russian language constitutes the relevance of this study. Empirical analysis is based on comparison of respective arrays of scientific publications in the field of sociology over the period of 2010-2021. We propose a set of comparison criteria including those related to the procedure of data access, quality of data management, quantitative and qualitative features of the data. Inspection of the databases based on the proposed criteria aids in identification of intersections between both the collections and the respective qualitative observations about them. We make conclusions regarding the comparative advantages and weaknesses of both databases in regards to their potential as the sole data source for bibliographic studies, and make recommendations for their effective use in research on Russian science.

Technological integration of lean manufacturing with industry 4.0 toward lean automation: insights from the systematic review and further research directions

PurposeOrganizations are continually improving their practices to improve operational performance. They already employ Lean Manufacturing techniques (LM) to reduce unnecessary waste. Industry 4.0 techniques enhance operational performance in association with LM. Despite the proven benefits of LM principles and the advancements offered by Industry 4.0 technologies, many organizations struggle to integrate these approaches effectively. This research paper explores how LM principles can be combined with Industry 4.0 technologies to provide valuable guidance for businesses looking to adopt lean automation strategies.Design/methodology/approachA systematic literature review on LM and Industry 4.0 was done to investigate the possible technical integration of both methods. Ninety-two articles are extracted systematically from the Scopus and Web of Science databases. This study states a systematic literature review, including quantitative analysis of bibliographic networks and cluster analysis, to identify emergent ideas and their further implementation.FindingsThe research findings highlight the positive impact of integrating lean production with Industry 4.0 techniques, benefiting organizations in achieving their goals. A lean automation integration framework is proposed based on the literature review and the findings.Practical implicationsThis study provides industry administrators and practitioners valuable guidance for enhancing organizational productivity. These implications can provide businesses with competitive advantages, enhance customer satisfaction, and enable them to adapt to the dynamic demands of the contemporary business environment.Originality/valueThis literature review study has substantially contributed to the technological integration of lean and Industry 4.0. The work has also identified potential emerging areas that warrant further research.

Global Overview of the Application of the Braun-Blanquet Approach in Research

Environmental classifications are of paramount importance for assessing the impacts of land-use changes, for prioritizing conservation efforts, and for developing effective management strategies to mitigate the negative impacts of human activities. The aim of our research was to provide as complete an analysis as possible of the studies that have been carried out using the Braun-Blanquet approach. The global review of studies based on the Braun-Blanquet approach includes 1168 papers and was conducted using the PRISMA 2009 methodological recommendations, strict criteria for the selection/quality of papers, and modern methods of data analysis and visualization using VOSviewer software developed by Nees Jan van Eck and Ludo Waltman (Centre for Science and Technology Studies (CWTS) of Leiden University in the Netherlands) (version 1.6.18), which ensures a representative sample, minimization of subjective judgements, and reliability of conclusions. It was noted that the number of publications on Braun-Blanquet is growing exponentially. This is an indication of the scientific interest in this methodology and its continuous further development. Based on a detailed analysis of the keywords, the main research directions and challenges are identified. These include improving the conceptual and methodological foundations of the Braun-Blanquet approach; improvement in regional vegetation classifications, synthesizing them and producing a comprehensive classification for large areas as a basis for biodiversity conservation and sustainable land use; expansion of the geography; compilation and updating of databases of phytosociological data; management of dynamics and vegetation; discussion of the important problem of continuity and discreteness of vegetation in the context of ecological classifications; and vegetation mapping. The top 20 journals publishing the most cited articles were identified, as well as the top 20 most cited journals whose high citation rate is due to the large number of high-quality articles. The analysis of the bibliographic network of papers in dynamics has shown that the structure of relationships is not constant and has changed significantly. The analysis of the authors’ publication activity showed that the vast majority of researchers have a low publication activity and have published only one to three papers. A peculiarity also emerges: if all the most cited authors are concentrated in Eurasia, then most of the most actively published authors are outside Eurasia. The importance of the Braun-Blanquet approach for the study and classification of forest vegetation should be emphasized. In this case, the Braun-Blanquet approach is integrated into forest typologies, increasing their ecological validity and environmental relevance.

Análise da Produção Científica em Oncológicos na Base de Dados Scopus

According to data from the United Nations, cancer is the second leading cause of death in the world. Due to its chemical properties, technetium-99m remains the most used radioisotope in the diagnosis of cancers. Thus, the present work analyzed through bibliometrics the characteristics of the world scientific production on technetium-99m, presented in articles from the Scopus database between 2001 and 2021. The search terms “(99mtc OR technetium OR technetium-99m) were used. AND (cancer OR tumor)”, with the filters “Title” and “Summary” in the search fields united by the Boolean operator “OR”. Then, the data were exported so that the construction and visualization of bibliographic networks could be carried out using the VOSviewer® program. The analysis of articles and journals showed that, in the number of publications, the United States, the Journal of Nuclear Medicine, The Netherlands Cancer Institute and the author Mishra, A.K. (India). Regarding the analyzes analyzed with VOSviewer®, the following stand out: the author Shuang Liu (co-citation of authors); and the words article and human (co-occurrence of keywords); Fan Wang (bibliographic coupling). It is hoped that this study will help stakeholders who have carried out research on technetium-99m radiopharmaceuticals to understand the scenario of scientific production.

THE USE OF DIGITAL TECHNOLOGY IN UNIVERSITY LEARNING THROUGH A BIBLIOMETRIC APPROACH

The article proposes a bibliometric analysis of digitalization in higher education. Based on research conducted in October 2023, the study explored 967 articles in the Web of Science (WOS) database. It highlights the growing importance of digitalization in higher education institutions and explores emerging trends in teaching practices and learning patterns. The study reveals a spike in publications in 2021-2022, likely in response to the COVID-19 pandemic and the transition to online learning. The most active countries in publications on the subject are Russia and Germany accounting for more than 45% of articles. In addition, the analysis of bibliographic networks identified collaborations between authors and the most cited articles, while the analysis of key terms highlighted important research topics such as e-learning and digitalization. This bibliometric study sheds valuable light on an abundant field of research at the heart of the current transformations in higher education. However, additional analyses are needed to follow the rapid evolution of digital education in all its richness and diversity.

The supporting role of Artificial Intelligence and Machine/Deep Learning in monitoring the marine environment: a bibliometric analysis

The widespread interest towards a sustainable and effective monitoring of the environment is increasingly demanding the development of modern and more affordable technologies to support or even replace the traditional time-consuming, high-cost sampling surveys at a multi-scale level. Researchers are highly benefitting from the recent enormous progresses achieved in the Artificial Intelligence (AI) field, with Machine/Deep Learning (ML/DL) applications increasing at sight. This gives a remarkable contribution to the environmental monitoring at sea, further allowing to develop efficient, smart and low-cost solutions to support the wide variety of tasks dealing with this objective. This study explores the global scientific literature on AI and ML/DL applications for the environmental monitoring over the last years. The VOSviewer software has been used to create maps based on the bibliographic network data: this allowed to display the relationships among scientific journals, researchers, and countries and to analyze the co-occurrence of different terms connected to the research. The resulting bibliometric analysis aims at verifying the major research interests and at providing the community with interesting findings and new perspectives on this very important topic, highlighting the great potential and flexibility of these methodologies and the excellent achievements they obtained in the last years.

Effect of similarity measures in diffusion prediction on homogeneous and heterogeneous bibliographic network

This paper evaluates the effect of similarity measures in predicting diffusion on homogeneous and heterogeneous bibliographic networks. The bibliographic network is analyzed within a homogeneous network and heterogeneous network, where a co-author relationship exists for the former, and multiple types of meta paths are considered for the latter. The supervised learning method is used to predict whether a node will be active with a topic or not. The features are extracted as the activation probability of a node, which represents the maximum of the activation probabilities of the neighbors of this node. In a homogeneous network, the activation probability from the activated node to the inactive node is measured based on one relationship co-author with basic similarity measures while it can be calculated based on diverse meta paths with dissimilar meta path-based similarity measures in the heterogeneous network. We performed our analysis on three different datasets. Our experimental results show that diffusion prediction in bibliographic networks provides better accuracy among heterogeneous networks than among homogeneous networks and that the Bayesian similarity measure provides the best efficiency.

GSim: A Graph Neural Network Based Relevance Measure for Heterogeneous Graphs

Heterogeneous graphs, which contain nodes and edges of multiple types, are prevalent in various domains, including bibliographic networks, social media, and knowledge graphs. As a fundamental task in analyzing heterogeneous graphs, relevance measure aims to calculate the relevance between two objects of different types, which has been used in many applications such as web search, recommendation, and community detection. Most of existing relevance measures focus on homogeneous networks where objects are of the same type, and a few measures are developed for heterogeneous graphs, but they often need the pre-defined meta-path. Defining meaningful meta-paths requires much domain knowledge, which largely limits their applications, especially on schema-rich heterogeneous graphs like knowledge graphs. Recently, the Graph Neural Network (GNN) has been widely applied in many graph mining tasks, but it has not been applied for measuring relevance yet. To address the aforementioned problems, we propose a novel GNN-based relevance measure, namely GSim. Specifically, we first theoretically analyze and show that GNN is effective for measuring the relevance of nodes in the graph. We then propose a context path-based graph neural network (CP-GNN) to automatically leverage the semantics in heterogeneous graphs. Moreover, we exploit CP-GNN to support relevance measures between two objects of any type. Extensive experiments demonstrate that GSim outperforms existing measures.

Identity Work in Athletes: A Systematic Review of the Literature.

The identity work process allows athletes to achieve a continuous development, revision, and maintenance of themselves. It provides insight into their self-perceptions and particularly intensifies during critical life events. While this process has been widely acknowledged, scant attention has been given to explicitly identifying the specific activities (i.e., identity work modes) involved in athletic identity work and integrating an overarching framework to inform coherent and continuous identities. Thus, we conducted a systematic review of the athletic identity literature to assess how this perspective is represented. Following the PRISMA guidelines, we reviewed 54 articles and analyzed the overall characteristics, bibliographical networks, and accumulated empirical findings. Through this process, we were able to identify the impact of having a strong athletic identity on key variables within and outside of sport. Based on the findings, we examined how identity work modes are depicted and discussed in the literature. Further discussion on how athletic identity literature can contribute to the broader body of knowledge is outlined.

A decade of integrated reporting studies: state of the art and future research implications

PurposeOver the past decade, researchers have witnessed an exponential growth in the number of publications on IR. This paper aims to understand the state of the art of the research field and to highlight the areas where further academic research is needed, guiding developments in theory, research, policy and practices.Design/methodology/approachThe authors apply the dynamic literature review method called “Systematic Literature Network Analysis”, which combines systematic literature review and bibliographic network analysis. Furthermore, to overcome some of the limitations connected to the methodology, the authors integrate the literature with a manual content analysis of papers.FindingsIR adoption and practices and their determinants represent the most analyzed aspects of literature. Over time, attention has been paid to more specific issues, such as the relationship between IR and other disclosure mechanisms, IR quality and its assurance, the critical analysis of the IR framework and principles and difficulties in IR adoption. Although the literature on IR can be considered to be in its mature stage, many aspects are still under-researched, so there is plenty of space for future research.Originality/valueThe authors propose the following main issues as subjects to be investigated in future studies: IR is not simply an evolution of sustainability reporting, but an innovative communication tool; the debate on who the recipients of value are (shareholders or stakeholders) and on what the definition of value adopted by IR is still remains an open issue; more attention should be given to the role of IR as a managerial tool, which could support strategy formation and communication, and influence internal processes of performance measurement and evaluation; what the future of IR will be in light of recent EU Corporate Sustainability Reporting Directive and new ISSB's standards is still an open question. From a methodological perspective, little is known about structured approaches in accounting studies. The authors confirm how methodologies, such as that of this paper, may be exploited as a tool to support dynamic analysis for setting the agendas for future studies in the accounting field.

Recent trends of potential medicinal uses of rice bran with its composition and bibliographic analysis

AbstractRice is an essential crop, growing in nearly every part worldwide. Grains are the most common rice plant part consumed as food; however, other plant parts also have some significant values apart from grains. Rice bran is the outer layer of the rice grain, an excellent source of various phenolic, flavonoid, and phytoactive compounds. This review article discusses the various compounds found in rice bran with their structure and properties. Different medicinal properties of rice bran are also discussed in this review article. Several constituents of rice bran show anticancerous activity through various mechanisms like cell cycle arrest and regulation of apoptotic factors. Anti‐inflammatory, antidiabetic, antihypertensive, and cholesterol‐lowering are the other activities of rice bran, briefly explained in the article, along with their mechanism of action. A bibliographic network, including keyword bibliography analysis and a three‐field plot, has also been discussed to show the trends and network of common keywords in the recently published documents in the Scopus database. Overall, this review explores the rice bran compositions with their structures, activity, and various medicinal uses of rice bran, which can be proven an efficient oil source for nutritional purposes.

A Bibliographic Review and Meta-Analysis of the Effect of Teaching Behaviors on Learners’ Performance in Videotaped Lectures

Although the discussion about the influence of the instructor-present videos has become a hot issue in recent years, the potential moderators on the effectiveness of an on-screen instructor have not been thoroughly synthesized. The present review systematically retrieves 47 empirical studies on how the instructors’ behaviors moderated online education quality as measured by learning performance via a bibliographic study using VOSviewer and meta-analysis using Stata/MP 14.0. The bibliographic networks illustrate instructors’ eye gaze, gestures, and facial expressions attract more researchers’ attention. The meta-analysis results further reveal that better learning performance can be realized by integrating the instructor’s gestures, eye guidance, and expressive faces with their speech in video lectures. Future studies can further explore the impact of instructors’ other characteristics on learning perception and visual attention including voice, gender, age, etc. The underlying neural mechanism should also be considered via more objective technologies.