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Brain-computer interfaces (BCIs), as a promising technology for rehabilitation, have attracted significant interest in the fields such as neurosciences, computer science, and biomedical engineering. Based on the expanded database of Science Citation Index, this paper analyzes bibliometrics in the field of BCI from 1990 to 2020 and discusses its potential research trends and prospects. The work provides a detailed overview of the BCI research status founded on the country, research area, institution, journal, author, citation, and keyword. A total of 7,880 papers suggest that the United States is leading the field of BCI research, followed by China and Germany. University of California system has produced the most publications, while the Graz University of Technology is leading the list for the h-index. Journal of Neural Engineering and IEEE Transactions on Neural Systems and Rehabilitation Engineering were identified to be the most productive journals in BCIs. Keywords analysis reflects that most research has focused on electroencephalography (EEG)-based BCIs to achieve a safe, real-time, stable link between the patient and artificial actuators. We can conclude by analyzing hot articles that new materials applied to neural probes may become the next hot topic. The typical paradigm of the BCI industry is the most urgent problem that can be solved in the standardization process. The rehabilitation applications appear as the initial driving force and ultimate goal for BCIs. This research can offer valuable references to BCI practitioners and provide data support for related studies. [ABSTRACT FROM AUTHOR]

Blockchain technology was bestowed through bitcoin; research has continuously stretched out its applications in different sectors, proving blockchain as a versatile technology expanded in non-financial use cases. In the healthcare industry, blockchain is relied upon to have critical effects. Although exploration here is generally new yet developing quickly, along these lines, researchers in computer science, healthcare information technology, and professionals are continually geared to stay up with research progress. The study presents an exhaustive study on blockchain as a technology in depth from all possible perspectives and its adoption in the healthcare sector. A mapping study has been conducted to search different scientific databases to identify the existing challenges in healthcare management systems and to analyze the existing blockchain-based healthcare applications. Though blockchain has inherent highlights, such as distributed ledger, encryption, consensus, and immutability, blockchain adoption in healthcare has challenges. This paper also provides insights into the research challenges in blockchain and proposes solution taxonomy through comparative analysis. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to identify the challenges, difficulties and opportunities for the SME sector in the Visegrad Group (V4) countries in the 21st century in the area of innovation and development, in particular digitalization. This research is justified by the prominent economic role of the SME sector and the key importance of adapting to the rapid pace of digitalization. Design/methodology/approach A literature review on this topic was used for the research, based on the Web of Science database. The scope of articles included in the survey was limited to peer-reviewed journal articles in English and published up to 2021. The process of selecting suitable studies for the search consisted of several steps, each of which aimed to include or exclude articles based on predefined criteria. Findings: The literature review has revealed significant gaps in the subject area. One of these is the lack of research on SMEs in the V4 countries. Another gap is the study of the relationship between SMEs and cloud computing from a computer science perspective, but other areas, not including the economic area, are less studied. Research limitations/implications: The limitations of the research include the database on which the study is based, the volume of the database and the criteria for the articles included in the study. Social implications: The study provides an overview for academics of who is working on the topic, from what aspect research has been done so far, and the links between publications. However, it may also be of interest to professionals interested in the subject area, if they want to see what areas are worth addressing, taking into account or just want to get a more comprehensive picture of the V4 SMEs in relation to digitalization. Originality/value: The importance of the study lies in the fact that it sheds light on the unanswered questions in the field and on the areas that have been little or not at all investigated by researchers. It can be used as a guideline for future studies in the field of cloud computing adoption by SMEs. [ABSTRACT FROM AUTHOR]

The objective of the study is to describe the world scientific production on gamification in the Scopus and Web of Science databases between the months of January 2020 and March 2022. We worked with a universe consisting of 754 documents from the database Web of Science and 1443 from Scopus. The results indicate that, in terms of the number of authors, Scopus has 1,336 and Web of Science, 2,223. The rate of collaboration between authors is slightly higher in Web of Science (3.18) compared to 3.05 in Scopus. Regarding the author with the highest production on the subject, Juho Hamari stood out, while the Lecture notes in computer science magazines in Scopus and the Sustainability magazine in WoS stood out as the media with the highest production of articles on gamification; On the other hand, Spain was the main country producing scientific evidence, and the type of scientific production that stood out was the original articles. The growth of scientific production on gamification is corroborated and further growth is forecast for the coming years. [ABSTRACT FROM AUTHOR]

Shortest distance computation is one of the widely researched areas in theoretical computer science and graph databases. Distance labeling are well-known for improving the performance of shortest distance queries. One of the best distance labeling approaches is Pruned Landmark Labeling (PLL). PLL is a 2-hop distance labeling which prunes a lot of unnecessary labels while doing breadth-first-search. Another well-known 2-hop labeling is Pruned Highway Labeling (PHL) which is designed for undirected road networks. Both PLL and PHL suffer from the problem of large index size. In this paper, we propose two approaches to address the problem, one is to compress the PLL index as well as the graph for directed graphs; the other is to compress undirected road networks using linear sets, which are essentially maximal-length non-branching paths. Our aim is to reduce the index size and index construction time without significantly compromising query performance. Extensive experiments with real world datasets confirm the effectiveness of our approaches. [ABSTRACT FROM AUTHOR]

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In the paper, the important role of tools and distributed IT resources in the dynamic development of astrophysics, astronomy, and space exploration are discussed. New possibilities and approaches to conducting research in the field of astronomy and astrophysics with the use of cloud computing and advanced data visualization techniques are also presented. Finally, some examples of the use of digital sky survey databases in scientific research are shown. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the latest trends in mobile technologies used in the education of the hearing impaired. Technology integration studies in the literature generally focus on visual dictionaries, sign language, word exercises or story books. In addition, it is seen that the studies report the results, not the process. However, there are few studies that describe the holistic technology integration process with a holistic approach. The study was conducted using qualitative research methodology, document analysis and related content analysis. Working with the keywords "mobile technology and hearing impaired" in Web of Science database is based on the analysis of published documents. All articles published in Web of Science have been examined. Affiliated universities of the distribution, subject areas, document types, country / regions and author themes by years were examined. Various findings reveal in terms of determining the importance of the analysis of the studies published in Web of Science database on the hearing impairments through mobile learning in terms of content. A total of 54 studies were analysed. It was concluded that the most studies related to technology were carried out in 2001 and 2019. It turns out that the first study was carried out in 2001. When literature review was done, it was concluded that most studies were conducted in 2019. It was also concluded that the most studies were in the field of Computer Science Theory Methods. It is mostly published as a full text. When looking at the scanning areas in the Web of Science index, it was seen that the most study area is in the Conference Proceedings Citation Index- Science area. When the universities of the researchers were analysed, it was also concluded that the researcher who carried out the most research was from Anadolu University. Although technology is very important in education, the effects of mobile learning on the hearing impaired should be further investigated and results should be shared. [ABSTRACT FROM AUTHOR]

Quantum Machine Learning (QML) is one of the core research fields in the larger paradigm of Quantum Computing (also known alternatively as Quantum Information). In recent years, researchers have taken deep interest in QML, given the potential time and cost advantages that solutions to real-life problems using QML algorithms provide, in comparison to their classical (or digital) machine learning equivalents. This is still a very new and exciting area of research with new algorithms and their uses being developed almost every other day. Deep research interest in this area has picked up only in the past 5–6 years. Given the background, this paper focuses on studying Scopus and Web of Science databases for the past 6 years (2014–2019) to identify various publication trends in the areas of Quantum Machine Learning. The authors have done an in-depth study of the Scopus and Web of Science publication data pertaining to this area and have come up with interesting insights. The survey covers 276 publications in Scopus and 154 publications in Web of Science. From the Scopus database, it is found that there has been a consistent growth in the number of publications in this period. Four research areas, namely, Physics, Astronomy, Computer Science, and Mathematics, have contributed 68.1% of the research publications. The USA leads the top 10 countries with nearly half (49.2%) of the research publications. A total of 148 patents have been published with 94 of these being published in the last four years (2016–2019). This essentially translates to one patent for every two publications. The Web of Science database, though bringing out 154 publications in the period, shows similar trends across the metrics. We have carried out a comparative study of some of the metrics in Scopus and Web of Science databases. Overall the study identifies the top 10 Institutions, authors, and research journals. [ABSTRACT FROM AUTHOR]

The aim of the present study is to visualize the dynamics of conceptual clusters, hidden patterns and emerging knowledge of "cybernetics in Middle Eastern countries" subject area in a global scale based on the co-word analysis of scientific outcomes indexed in the Web of Science database. This research is an applied one, performed with the co-word analysis method and analytical approach. The population includes 2280 keywords from 705 records in the cybernetics subject area in Middle Eastern countries, published in 7 journals indexed in the Web of Science database until 2018. To have a coherence set of data and create the co-occurrence matrix, RavarPreMap software applied. Then, using SPSS 16 and VOSViewer, the subjects were clustered and mapped. Specifications of co-word networks such as centrality and density illustrated using UCInet software in the form of a strategic diagram. Thereby, the situation and evolutionary branches of the cybernetics subject area revealed in Middle Eastern countries. The trend of scientific productions in cybernetics in Middle Eastern counties is incremental. Computer science, with 444 records, is the core subject in the mentioned studies. Researchers' intellectual structures are identifiable in 12 clusters. The most significant cluster is the twelfth one, named master data mining algorithms and including 20 keywords. The distribution of clusters in the strategic diagram shows that Clusters 1, 2, and 4 are core issues in the subject area. Furthermore, they are mature and coherent, being studied at the core of the research area, having a core and developable role. The coword analysis is a proper and powerful method in discovering and visualizing science and knowledge, tracking sciences, studying the trend of conceptual dynamicity, identifying and analyzing researchable fields in the subject area of cybernetics. This strategic approach can drastically help research planners and policy-makers as well as governmental authorities. [ABSTRACT FROM AUTHOR]

The automatic classification of abstract sentences into its main elements (background, objectives, methods, results, conclusions) is a key tool to support scientific database querying, to summarize relevant literature works and to assist in the writing of new abstracts. In this paper, we propose a novel deep learning approach based on a convolutional layer and a bidirectional gated recurrent unit to classify sentences of abstracts. First, the proposed neural network was tested on a publicly available repository containing 20 thousand abstracts from the biomedical domain. Competitive results were achieved, with weight-averaged Precision, Recall and F1-score values around 91%, and an area under the ROC curve (AUC) of 99%, which are higher when compared to a state-of-the-art neural network. Then, a crowdsourcing approach using gamification was adopted to create a new comprehensive set of 4111 classified sentences from the computer science domain, focused on social media abstracts. The results of applying the same deep learning modeling technique trained with 3287 (80%) of the available sentences were below the ones obtained for the larger biomedical dataset, with weight-averaged Precision, Recall and F1-score values between 73 and 76%, and an AUC of 91%. Considering the dataset dimension as a likely important factor for such performance decrease, a data augmentation approach was further applied. This involved the use of text mining to translate sentences of the computer science abstract corpus while retaining the same meaning. Such approach resulted in slight improvements (around 2 percentage points) for the weight-averaged Recall and F1-score values. [ABSTRACT FROM AUTHOR]

The recent appearance of low cost virtual reality (VR) technologies – like the Oculus Rift, the HTC Vive and the Sony PlayStation VR – and Mixed Reality Interfaces (MRITF) – like the Hololens – is attracting the attention of users and researchers suggesting it may be the next largest stepping stone in technological innovation. However, the history of VR technology is longer than it may seem: the concept of VR was formulated in the 1960s and the first commercial VR tools appeared in the late 1980s. For this reason, during the last 20 years, 100s of researchers explored the processes, effects, and applications of this technology producing 1000s of scientific papers. What is the outcome of this significant research work? This paper wants to provide an answer to this question by exploring, using advanced scientometric techniques, the existing research corpus in the field. We collected all the existent articles about VR in the Web of Science Core Collection scientific database, and the resultant dataset contained 21,667 records for VR and 9,944 for augmented reality (AR). The bibliographic record contained various fields, such as author, title, abstract, country, and all the references (needed for the citation analysis). The network and cluster analysis of the literature showed a composite panorama characterized by changes and evolutions over the time. Indeed, whether until 5 years ago, the main publication media on VR concerned both conference proceeding and journals, more recently journals constitute the main medium of communication. Similarly, if at first computer science was the leading research field, nowadays clinical areas have increased, as well as the number of countries involved in VR research. The present work discusses the evolution and changes over the time of the use of VR in the main areas of application with an emphasis on the future expected VR's capacities, increases and challenges. We conclude considering the disruptive contribution that VR/AR/MRITF will be able to get in scientific fields, as well in human communication and interaction, as already happened with the advent of mobile phones by increasing the use and the development of scientific applications (e.g., in clinical areas) and by modifying the social communication and interaction among people. [ABSTRACT FROM AUTHOR]

Background: Web-based, free-text documents on science and technology have been increasing growing on the web. However, most of these documents are not immediately processable by computers slowing down the acquisition of useful information. Computational ontologies might represent a possible solution by enabling semantically machine readable data sets. But, the process of ontology creation, instantiation and maintenance is still based on manual methodologies and thus time and cost intensive. Method: We focused on a large corpus containing information on researchers, research fields, and institutions. We based our strategy on traditional entity recognition, social computing and correlation. We devised a semi automatic approach for the recognition, correlation and extraction of named entities and relations from textual documents which are then used to create, instantiate, and maintain an ontology. Results: We present a prototype demonstrating the applicability of the proposed strategy, along with a case study describing how direct and indirect relations can be extracted from academic and professional activities registered in a database of curriculum vitae in free-text format. We present evidence that this system can identify entities to assist in the process of knowledge extraction and representation to support ontology maintenance. We also demonstrate the extraction of relationships among ontology classes and their instances. Conclusion: We have demonstrated that our system can be used for the conversion of research information in free text format into database with a semantic structure. Future studies should test this system using the growing number of free-text information available at the institutional and national levels. [ABSTRACT FROM AUTHOR]

In this article, we test the hypothesis that computer science papers asking questions (i.e., those with a question mark at the end of their title) are cited more frequently than those that do not have this property. To this end, we analyze a data set of almost two million records on computer science papers indexed in the Web of Science database and focus our investigation on the mean number of citations per paper of its specific subsets. The main finding is that the average number of citations per paper of the so-called "asking papers" is greater by almost 20% than that of other papers, and that this difference is statistically significant. [ABSTRACT FROM AUTHOR]

Since 2016, "fake news" has been the main buzzword for online misinformation and disinformation. This term has been widely used and discussed by scholars, leading to hundreds of publications in a few years. This report provides a quantitative analysis of the scientific literature on this topic by using frequency analysis of metadata and automated lexical analysis of 2,368 scientific documents retrieved from Scopus, a large scientific database, mentioning "fake news" in the title or abstract. Findings show that until 2016 the number of documents mentioning the term was less than 10 per year, suddenly rising from 2017 and steadily increasing in the following years. Among the most prolific countries are the U.S. and European countries such as the U.K., but also many non-Western countries such as India and China. Computer science and social sciences are the disciplinary fields with the largest number of documents published. Three main thematic areas emerged: computational methodologies for fake news detection, the social and individual dimension of fake news, and fake news in the public and political sphere. There are 10 documents with more than 200 citations, and two papers with a record number of citations. [ABSTRACT FROM AUTHOR]

Background: Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific literature in relation to the application of these technologies in medicine.Objective: We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research.Methods: The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts.Results: The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering.Conclusions: The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients. [ABSTRACT FROM AUTHOR]

Timelines have been used for centuries and have become more and more widely used with the development of social media in recent years. Every day, various smart phones and other instruments on the internet of things generate massive data related to time. Most of these data can be managed in the way of timelines. However, it is still a challenge to effectively and efficiently store, query, and process big timeline data, especially the instant recommendation based on timeline similarities. Most existing studies have focused on indexing spatial and interval datasets rather than the timeline dataset. In addition, many of them are designed for a centralized system. A timeline index structure adapting to parallel and distributed computation framework is in urgent need. In this research, we have defined the timeline similarity query and developed a novel timeline index in the distributed system, called the Distributed Triangle Increment Tree (DTI-Tree), to support the similarity query. The DTI-Tree consists of one T-Tree and one or more TI-Trees based on a triangle increment partition strategy with the Apache Spark. Furthermore, we have provided an open source timeline benchmark data generator, named TimelineGenerator, to generate various timeline test datasets for different conditions. The experiments for DTI-Tree’s construction, insertion, deletion, and similarity queries have been executed on a cluster with two benchmark datasets that are generated by TimelineGenerator. The experimental results show that the DTI-tree provides an effective and efficient distributed index solution to big timeline data. [ABSTRACT FROM AUTHOR]

A review is presented for the web site and resource database "Synthesis Digital Library of Engineering and Computer Science," hosted by Morgan and Claypool Publishers, found at www.morganclaypool.com.

A review is presented for the web site and research service "Proquest Computer Science Collection," published by ProQuest, found at www.proquest.com.

The article reviews the web site "CRCnetBASE 2.0," hosted by CRC Press, found at www.crcnetbase.com.

The article reviews the web site io-port.net, located at http://www.io-port.net/.

This article reviews "CSA Illustrata Technology," an online database of computer science and part of the www.proquest.com web site.

The article reviews several web sites related to information technology in the U.S. including www.informationtechnologycrossing.com, Search Data Management and the www.cwnp.com from the Certified Wireless Network Professional.

This article reviews the web site crcnetbase.com, an online database of computer science reference books.