hamed barangi

Blockchain is a distributed and undeniable digital ledger that stores transactions in a chain of high-security blocks. Blockchain solves security and privacy issues in different domains. This study aims to investigate a scientific study on blockchain security and privacy researches in Web of Science database to provide a status view of this area of research using scientometric techniques. The research community has 1226 records that have been indexed by blockchain researchers in the field of security and privacy over five years (between 2015 and 2019). In this article, the most influential countries, the network of cooperation between countries and top universities, top researchers, the most frequent keywords and cluster analysis of keywords in this field are examined. Based on the results of this study, it can be stated that security and privacy researches in the field of blockchain in ISI has been grown exponentially over the past five years, and blockchain has been mostly used to address security and privacy issues in IoT and its applications.

Model-Driven Software Engineering (MDSE) is a software development methodology that reduces the cost and production time of the final product by concentratingon a higher level of abstraction. The main focus of MDSE is to generate automated code by applying different types of transformations to high-level models. The effectiveness of MDSE has been proved in different domains for solving various types of problems.This research provides the bibliometric analysis of research in the field of MDSE. The population of the study consists of all MDSE articles indexed in the Web of Science database in ten years from 2010 to 2019. The work aims to identify the volume of scientific production, the most influential countries, universities, authors, and journals, the cooperation network among the countries, universities, and authors, keyword ranking, and Co-word analysis of keywords and titles of the articles. Keyword analysis revealed that Model Transformation and Model Checking are two very important clusters and topics of interest to researchers in this field. The results provide valuable insights that can be used as a guideline by both fresh and experienced researchers for the current state and future trend of MDSE research in different scientific disciplines to establish a baseline beforeinitiating an MDSE research project in the future.

The purpose of this study is to analyze the status of studies conducted in the field of sports media in the international arena. The statistical population of the present study is all articles of sport media including 1360 ones indexed in the ISI database since 1983 to 2016, which have been analyzed using Scientometrics and network analysis software. The analysis was done on the identification of quantitive nature of studies by time, superisr journals in terms of number of articles, geographical distribution of relevant studies, the collaberative network of countries and the most frequent keywords used in title, abstract and per terms. The results showed that from 1983 to 2016, the number of research conducted in the field of sports media has grown relative, from 9 papers in 1983 to 92 papers in 2016. MEDICINE AND SCIENCE IN SPORTS AND EXERCISE magazine published 133 articles with the largest share in sport media. The United States, 670 articles and 49% of published articles, has the largest share of sports media coverage. The words "sport", "medium", and "performance", with 138, 129, and 124, are the most frequent in the title and abstract of the published articles, and the keywords of rehabilitation, community and internet are the most frequent words in the keywords espectively of these articles.

Conducting a scientometrics study on Iran’s research in Computer Science in an international arena exposes an exact picture of its situation. The purpose of this study is an investigation of Iran’s global situation in Computer Science using scientometric techniques.
Bibliometric methodology and social network analysis are used as the research methods. The research population comprises Iran’s 23964 records in the field of Computer Science during 1987-2016¡ which have been retrieved from Web of Science.
Findings: Results indicated that Iran’s international research on Computer Science recienced 95502 citations, totally, which is 4 times per article. Moreover, “Genetic Algorithm”¡ “Neural Network”¡ and “Particle Swarm Optimization” are the most frequent keywords in the Computer Science studies published by Iranian researchers. Use of cluster analysis of both title and abstract terms led to the creation of 7 topical clusters in Iran’s Computer Science studies.
In general, according to the results of this research, it can be claimed that Iran's computer research has grown relatively during this thirty years, showing a share of 0.968 Iran and ranked 24th among all countries of the world. That seems a low rating. Since the realization of goals such as e-government and advancement in other sciences depends to a great extent on the development of computer science, the need for investment and comprehensive planning in this area is increasingly evident.