scholarly journals Wiki-Gendersort: Automatic gender detection using first names in Wikipedia

2020 ◽  
Author(s):  
Nicolas Bérubé ◽  
Gita Ghiasi ◽  
Maxime Sainte-Marie ◽  
Vincent Larivière
Keyword(s):  
Web Of Science ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Related Research ◽  
Gender Information ◽  
Research Questions ◽  
Gender Detection ◽  
The Web

Gender information is often absent from databases available to scholars, thus hindering the proper problematization, investigation, and answering of various gender-related research questions. Named-based algorithms represent the most simple, yet effective used gender detection methods: such methods proceed by generating first-name-to-gender mapping tables based on user records in a given dataset and then applying such mapping tables "in reversal" to other databases for completion or validation purposes. The present research aims to develop a gender detection algorithm focusing on the gender detection of eponymous Wikipedia pages and compare its performance to that of other well-known gender detection databases, using the author names indexed in the Web of Science.

Islamic social finance: a literature review and future research directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Laura Aibolovna Kuanova ◽  
Rimma Sagiyeva ◽  
Nasim Shah Shirazi
Keyword(s):  
Literature Review ◽  
Web Of Science ◽  
Islamic Finance ◽  
Future Research ◽  
Research Directions ◽  
Content Type ◽  
The Social ◽  
Future Research Directions ◽  
Research Questions ◽  
The Web

Purpose This paper aims to study the main trends of scientific research in Islamic finance’s social aspects to clarify place, role and functions, especially in the context of increasing social problems. To achieve this goal, this paper focuses on the social component of Islamic finance, analyzes publications on social Islamic finance in the Web of Science database, covering the period from 1979 to 2020, specify the geographical localization of research networks, determines the most cited authors and their scientific position. Design/methodology/approach The authors have applied several literature review techniques, a bibliometric citation and co-citation analysis, a co-authorship analysis and a review of the most cited papers. The analyzes’ results allow us to offer five future questions in Islamic social finance, zakat and waqf, which have not been investigated before and could influence Islamic social finance and Islamic finance research. Findings The authors also derive and summarize five leading future research questions. Research limitations/implications This is a limitation of using only the Web of Science Core Collection database as the premier resource and the most trusted citation index for the world’s scientific and scholarly research. Further study might expand the types of analyzed units, include more keywords and include other databases, such as Scopus. Originality/value This paper can be considered as an inspirational one to future researchers and policymakers in Islamic social finance.

scholarly journals Tensions Within the Ministry of Provenance: Reflections on Co-Creating a Research Game Together With Artists

2018 ◽  
Vol 50 (3) ◽  
pp. 329-358 ◽  
Author(s):  
Richard Wetzel ◽  
Khaled Bachour ◽  
Martin Flintham
Keyword(s):  
Game Design ◽  
Collaborative Research ◽  
Research Agenda ◽  
High Impact ◽  
Mitigation Strategies ◽  
Web Based ◽  
Related Research ◽  
Artistic Vision ◽  
Research Questions ◽  
The Web

Background. Research games are challenging to design as they seek to fulfil a research agenda as well as work as a game. We have successfully collaborated with a group of artists in a research game about people’s perception of provenance called The Apocalypse of the Ministry of Provenance (MoP). The web-based game ran for 6 months with a total of 1004 players signing up over its lifetime with 490 consenting to their data being used for research purposes. While the game allowed us to answer our provenance-related research questions, in this article we look at the game design process of such a collaborative research game. Aim. The co-creation approach created tensions that had to be carefully negotiated between everyone involved. The purpose of this article is to investigate the nature of these tensions, what has caused them, and how we managed (or failed) to mitigate them. This leads to recommendations for future researchers co-creating a research game with artists. Method. We use the form of a post-mortem reflection on the development of the game, based on our own experiences, a one-hour long interview with the two artists involved, and post-game phone interviews with players (n=8). Results. We identify the following three tensions that had a high impact on the overall process: 1) Translating research questions into engaging gameplay elements; 2) Creation of research-relevant content by artists; 3) Artistic vision conflicting with research agenda. We contextualize these tensions by describing six vignettes concerning our collaboration in rich detail that highlight the salient issues of the overall process and resulting game from different perspectives. Lastly, we present seven mitigation strategies on how to deal with the tensions or prevent them from arising. Conclusions. A collaboration with artists for the purpose of creating a research game is a rewarding but also challenging process. Overcoming the resulting tensions is possible by utilizing mitigation strategies that need to be implemented jointly between researchers and artists to guarantee the success as an engaging research game.

scholarly journals Water research and collaboration in the Southern African Development Community

Water SA ◽  
2018 ◽  
Vol 44 (3 July) ◽  
Author(s):  
Anastassios Pouris
Keyword(s):  
South Africa ◽  
South African ◽  
Web Of Science ◽  
Southern African Development Community ◽  
Policy Implications ◽  
The South ◽  
Water Research ◽  
Related Research ◽  
African Development ◽  
The Web

This article investigates water-related research in the Southern African Development Community. Water issues are part of the region’s science and technology priorities as 4countries receive less rain than the global average of 860 mm/yr – Botswana with 400 mm/yr, Namibia with 254 mm/yr, South Africa with 497 mm/yr and Zimbabwe with 652 mm/yr. Furthermore, the international literature indicates that joint or internationally coordinated research has the potential to improve the scientific–technical quality of international agreements, prevent conflict and shape the way for appropriate management of the shared resources. Scientometric analysis using the Web of Science database is employed in order to identify the state of water research and collaboration in the SADC region. The Web of Science indexes a defined set of journals worldwide and the South African Government provides incentives/subsidies for publications indexed by this database. The results show that South Africa is the main producer (80%) of research publications in the region. Similarly, in the field of water research South Africa produces 75% of the region’s research. The SADC collaboration matrix in water-related research reveals that there is minimal, if any, collaborative research on the topic. Some seed-level research exists between South Africa, Zimbabwe and Namibia. The main funders of research are the South African National Research Foundation (NRF) (acknowledged in 180 publications), the Bill & Melinda Gates Foundation (72 publications), the National Institutes of Health (64 publications) and the Wellcome Trust (60 publications). Policy implications are discussed (e.g. the establishment of SADC Common Water Research Area; research support for the region, etc.).

scholarly journals Global Trends and Hotspots in Research on Rehabilitation Robots: A Bibliometric Analysis From 2010 to 2020

2022 ◽  
Vol 9 ◽  
Author(s):  
Xiali Xue ◽  
Xinwei Yang ◽  
Zhongyi Deng ◽  
Huan Tu ◽  
Dezhi Kong ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Task Analysis ◽  
Web Of Science ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Future Research ◽  
Rehabilitation Robot ◽  
Related Research ◽  
Rehabilitation Robots ◽  
The Web

Background: In recent years, with the development of medical science and artificial intelligence, research on rehabilitation robots has gained more and more attention, for nearly 10 years in the Web of Science database by journal of rehabilitation robot-related research literature analysis, to parse and track rehabilitation robot research hotspot and front, and provide some guidance for future research.Methods: This study employed computer retrieval of rehabilitation robot-related research published in the core data collection of the Web of Science database from 2010 to 2020, using CiteSpace 5.7 visualization software. The hotspots and frontiers of rehabilitation robot research are analyzed from the aspects of high-influence countries or regions, institutions, authors, high-frequency keywords, and emergent words.Results: A total of 3,194 articles were included. In recent years, the research on rehabilitation robots has been continuously hot, and the annual publication of relevant literature has shown a trend of steady growth. The United States ranked first with 819 papers, and China ranked second with 603 papers. Northwestern University ranked first with 161 publications. R. Riener, a professor at the University of Zurich, Switzerland, ranked as the first author with 48 articles. The Journal of Neural Engineering and Rehabilitation has the most published research, with 211 publications. In the past 10 years, research has focused on intelligent control, task analysis, and the learning, performance, and reliability of rehabilitation robots to realize the natural and precise interaction between humans and machines. Research on neural rehabilitation robots, brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeletons has attracted more and more attention.Conclusions: At present, the brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeleton rehabilitation robots are the research trends and hotspots. Future research should focus on the application of machine learning (ML), dimensionality reduction, and feature engineering technologies in the research and development of rehabilitation robots to improve the speed and accuracy of algorithms. To achieve wide application and commercialization, future rehabilitation robots should also develop toward mass production and low cost. We should pay attention to the functional needs of patients, strengthen multidisciplinary communication and cooperation, and promote rehabilitation robots to better serve the rehabilitation medical field.

Flavonoids and other Non-Alkaloidal Constituents of Genus Erythrina: A Detailed Account of Phytochemical Review

2019 ◽  
Vol 23 ◽  
Author(s):  
Ninh The Son ◽  
Abdelsamed I. Elshamymistry
Keyword(s):  
Secondary Metabolites ◽  
Web Of Science ◽  
Herbal Medicines ◽  
Original Research ◽  
Chemical Structures ◽  
Fatty Acid Derivatives ◽  
Material Sources ◽  
Anti Cancer ◽  
Alkaloidal Constituents ◽  
The Web

: Genus Erythrina belongs to family Fabaceae, which widely distributed in tropical and subtropical areas, and has been applied in both traditional herbal medicines, and pharmacological uses. Original research articles and publications on overview of alkaloids related to this genus are available, but a supportive systematic review account highlighted phytochemical aspects of other types of secondary metabolites is now insufficient. Utilizing data information from SCI-Finder, Google Scholar, the Web of Science, Scopus, Science Direct, PubMed, Chemical Abstracts, ACS journals, Springer, Taylor Francis, Bentham Science and IOP Science, the reliable material sources of this systematic manuscript paper were obtained from the literature published from 1980s to now. A vast amount of data showed that the non-alkaloidal secondary metabolites obtained from genus Erythrina with various classes of chemical structures. Herein, approximately five hundred constituents were isolated comprising of flavonoids, terpenoids, saponins, phytosterols, phenols, arylbenzofurans, coumarins, alcohols, ceramides, mono-sugars and fatty acid derivatives. It resembles the previously phytochemical reports on the plants of differential genus of family Fabaceae, flavonoids reached to the high amount in plants of genus Erythrina. Numerous biological researches such as anti-microbacteria, anti-cancer, anti-virus using isolated compounds from Erythrina species suggested that secondary metabolites of Erythrina plants are now becoming promising agents for drug developments.

Multidimensional analysis of the state of Russian studies on the education issues over 1993–2016

2018 ◽  
pp. 50-62
Author(s):  
Дмитрий Рубвальтер ◽  
Dmitry Rubvalter ◽  
Александр Либкинд ◽  
Alexander Libkind ◽  
Валентина Маркусова ◽  
...  
Keyword(s):  
Web Of Science ◽  
The State ◽  
Multidimensional Analysis ◽  
Russian Regions ◽  
Global Flow ◽  
Educational Issues ◽  
Foreign Countries ◽  
High Level ◽  
The Web ◽  
Made In

A multidimensional analysis of the state of Russian studies on the education issues over 1993–2016 was carried out based on the materials of the data contained in the Web of Science (SSCI, A & HCI and SCI-E databases). There were determined the dynamics and trends of a number of relevant indicators, such as the number of Russian publications by year, the share of these publications in the global flow of publications on education issues, the dynamics of the share of publications made in co-authorship with foreign colleagues, etc. A number of distributions of Russian publications on educational issues was compiled and analyzed: by journals, by Russian regions and cities, by organizations and authors of the publications. It was found that most of these distributions were characterized by a high level of non-uniformity. A list of journals (125 titles) in which Russian works on education issues had been published was compiled. Russian organizations (308) and domestic researchers (about two thousand) engaged in studying the issues of education were identified. It was discovered that more than 200 organizations and about 400 academicians from 60 foreign countries had participated in Russian studies on the education issues.

scholarly journals Modelling community structure and temporal spreading on complex networks

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Vesa Kuikka
Keyword(s):  
Community Structure ◽  
Complex Networks ◽  
Community Detection ◽  
Network Structure ◽  
Network Connectivity ◽  
Network Models ◽  
Building Blocks ◽  
Detection Algorithm ◽  
Research Area ◽  
Detection Methods

AbstractWe present methods for analysing hierarchical and overlapping community structure and spreading phenomena on complex networks. Different models can be developed for describing static connectivity or dynamical processes on a network topology. In this study, classical network connectivity and influence spreading models are used as examples for network models. Analysis of results is based on a probability matrix describing interactions between all pairs of nodes in the network. One popular research area has been detecting communities and their structure in complex networks. The community detection method of this study is based on optimising a quality function calculated from the probability matrix. The same method is proposed for detecting underlying groups of nodes that are building blocks of different sub-communities in the network structure. We present different quantitative measures for comparing and ranking solutions of the community detection algorithm. These measures describe properties of sub-communities: strength of a community, probability of formation and robustness of composition. The main contribution of this study is proposing a common methodology for analysing network structure and dynamics on complex networks. We illustrate the community detection methods with two small network topologies. In the case of network spreading models, time development of spreading in the network can be studied. Two different temporal spreading distributions demonstrate the methods with three real-world social networks of different sizes. The Poisson distribution describes a random response time and the e-mail forwarding distribution describes a process of receiving and forwarding messages.

scholarly journals Thirty Years of Human Rights Study in the Web of Science Database (1990–2020)

2021 ◽  
Vol 18 (4) ◽  
pp. 2131
Author(s):  
Priscilla Paola Severo ◽  
Leonardo B. Furstenau ◽  
Michele Kremer Sott ◽  
Danielli Cossul ◽  
Mariluza Sott Bender ◽  
...  
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Human Rights ◽  
Network Analysis ◽  
Reproductive Health ◽  
Web Of Science ◽  
Health Issues ◽  
Human Beings ◽  
Field Of Study ◽  
The Web

The study of human rights (HR) is vital in order to enhance the development of human beings, but this field of study still needs to be better depicted and understood because violations of its core principles still frequently occur worldwide. In this study, our goal was to perform a bibliometric performance and network analysis (BPNA) to investigate the strategic themes, thematic evolution structure, and trends of HR found in the Web of Science (WoS) database from 1990 to June 2020. To do this, we included 25,542 articles in the SciMAT software for bibliometric analysis. The strategic diagram produced shows 23 themes, 12 of which are motor themes, the most important of which are discussed in this article. The thematic evolution structure presented the 21 most relevant themes of the 2011–2020 period. Our findings show that HR research is directly related to health issues, such as mental health, HIV, and reproductive health. We believe that the presented results and HR panorama presented have the potential to be used as a basis on which researchers in future works may enhance their decision making related to this field of study.

scholarly journals A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

2021 ◽  
Vol 18 (3) ◽  
pp. 952 ◽  
Author(s):  
Leonardo B. Furstenau ◽  
Bruna Rabaioli ◽  
Michele Kremer Sott ◽  
Danielli Cossul ◽  
Mariluza Sott Bender ◽  
...  
Keyword(s):  
Decision Making ◽  
Network Analysis ◽  
Web Of Science ◽  
Future Research ◽  
Future Trends ◽  
Damage Prevention ◽  
Over Time ◽  
The Web

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight ‘CHLOROQUINE’, ‘ANXIETY’, ‘PREGNANCY’ and ‘ACUTE-RESPIRATORY-SYNDROME’, among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: “Damage prevention and containment of COVID-19” and “Comorbidities and diseases caused by COVID-19”, which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.

scholarly journals A generalised approach for high-throughput instance segmentation of stomata in microscope images

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Hiranya Jayakody ◽  
Paul Petrie ◽  
Hugo Jan de Boer ◽  
Mark Whitty
Keyword(s):  
High Throughput ◽  
Imaging Techniques ◽  
Detection Algorithm ◽  
Input Image ◽  
Detection Methods ◽  
Sample Collection ◽  
High Throughput Analysis ◽  
General Applicability ◽  
Additional Image ◽  
Bounding Boxes

Abstract Background Stomata analysis using microscope imagery provides important insight into plant physiology, health and the surrounding environmental conditions. Plant scientists are now able to conduct automated high-throughput analysis of stomata in microscope data, however, existing detection methods are sensitive to the appearance of stomata in the training images, thereby limiting general applicability. In addition, existing methods only generate bounding-boxes around detected stomata, which require users to implement additional image processing steps to study stomata morphology. In this paper, we develop a fully automated, robust stomata detection algorithm which can also identify individual stomata boundaries regardless of the plant species, sample collection method, imaging technique and magnification level. Results The proposed solution consists of three stages. First, the input image is pre-processed to remove any colour space biases occurring from different sample collection and imaging techniques. Then, a Mask R-CNN is applied to estimate individual stomata boundaries. The feature pyramid network embedded in the Mask R-CNN is utilised to identify stomata at different scales. Finally, a statistical filter is implemented at the Mask R-CNN output to reduce the number of false positive generated by the network. The algorithm was tested using 16 datasets from 12 sources, containing over 60,000 stomata. For the first time in this domain, the proposed solution was tested against 7 microscope datasets never seen by the algorithm to show the generalisability of the solution. Results indicated that the proposed approach can detect stomata with a precision, recall, and F-score of 95.10%, 83.34%, and 88.61%, respectively. A separate test conducted by comparing estimated stomata boundary values with manually measured data showed that the proposed method has an IoU score of 0.70; a 7% improvement over the bounding-box approach. Conclusions The proposed method shows robust performance across multiple microscope image datasets of different quality and scale. This generalised stomata detection algorithm allows plant scientists to conduct stomata analysis whilst eliminating the need to re-label and re-train for each new dataset. The open-source code shared with this project can be directly deployed in Google Colab or any other Tensorflow environment.

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