Purpose: The main purpose of this research was to identify the rate of familiarity of Tehran University graduate students from Google Scholar database.Methodology: This research is applied one that has done through analytical survey research method. Researcher made questionnaire is used for data gathering. All of Tehran university graduate students form research community are included in this study. Sampling method is used to determine the sample group, due to the high number of students.Findings: Findings showed that the majority of students are aware of being free of Google Scholar search engine. However, the majority of graduate students at Tehran University are much less familiar with the advantages and disadvantages of various Google Scholar services. Overall, it was concluded that the level of familiarity of graduate students at Tehran University with Google scholar services was low.Conclusion: This research is the first one that concentrated on the level of familiarity of graduate students at Tehran University with Google Scholar database.

Aim: Scientific recommender systems have been developed to provide users with resources that are close to their information needs. The main objective of the present study was to compare the effectiveness of the related articles recommender systems in Google Scholar and Web of Science databases from the users’ perspectives. Methods: This is an applied research with comparative approach. The samples included both human and paper ones. The human samples consisted of 120 Ph. D. candidates at Shiraz University. From among each field, thirty students (i. e., totally 120 students) participated in the study. The paper samples consisted of 2, 400 related papers, 1200 of which were retrieved from Google Scholar, and 1, 200 of which were retrieved from Web of Science database. The data were collected by a questionnaire and software. Results: The results showed that users considered both Google Scholar and Web of Science databases as effective in retrieving the related articles. There were significant differences between each of the four areas of humanities, basic sciences, engineering, agriculture and veterinary science in terms of the effectiveness of the related articles function. In addition, both databases represented the least number of related articles and the largest number of unrelated articles in the area of humanities. Originality: Despite the importance of related articles recommender systems, there was no evidence that measures the effectiveness of related articles recommender systems in Web of Science and Google Scholar.

Purpose: The purpose of this study was to evaluate the effect of authority control on researchers' scientific productivity in Google Scholar and Research Gate databases. Methodology: This research as an applied and exploratory study compares authority control in Google Scholar and Research Gate Databases by using library, experimental, and comparative methods and analyzes its impact on researchers' scientific productivity. A total of 100 out of 2652 external and internal researchers in the field of information and science who had at least one article indexed in Web of Science and Scopus databases as well as one or more H-indexes between the ages of 2010 to 2018, using purposive sampling, were considered as the sample of this study. Findings: Google Scholar and Search Gate databases are not found except for a few key items such as small name, big name, organizational affiliation, researcher email, specific tools that can be helpful in obtaining of researcher’ s identity. Conclustion: Significant errors and failures in the authentication of researchers at both Google Scholar and Research Gate sites indicate a lack of documentation and organizing tools to solve challenges and issues that cause serious unforeseen damage and errors in the author's documentation control.

Background and aim: Citation is the most important scientific elements and assessment index among researchers, universities and research centers. The aim of this study was to compare the citations of researchers in the field of engineering in Scopus, Google Scholar and Google Books.Material and methods: This study investigated the relationship between citations using citation analysis and data were extracted from Scopus from 2008 to 2012. Totally, 100 subjects were randomly selected using Webometric Analyst, and the numbers of citations were transferred to SPSS and analyzed.Findings: Results showed that the median of citations to articles was 4, 6 and 1 in Scopus, Google Scholar and Google Books. Although there was no difference between the mean of Google Scholar and Scopus, it was found that the citations had high distribution based on variance values. Most of the citations to articles in Google Scholar, Scopus and Google Books were 1061, 652 and 72, respectively.Conclusion: There was a direct and significant relationship between the citations of Scopus and Google Scholar; therefore, the use of all three bases regardless of overlapping articles showed the better results in evaluation of scientific outputs. Moreover, even, assessing the scientific outputs can be performed through Google Scholar in case of lack of access to Scopus.

This research used documentary method and citation analysis to analyze the collected data. The statistical society of this research was formed by the indexed scientific documents of 117 researchers of institutions of Shahid Beheshti University in WoS, Scopus and Google Scholar databases. H and g indexes and m parameter of researchers were calculated through the combination of data gathered from these three databases. For this statistical society, the average numbers for h and g indexes were 0.85 and 2.66. Also the average number for m parameter was equal to 0.41. H-index, g-index and m parameter show a higher number in men’s group rather than women’s group. The highest measured h-index number in men's group was 23 and in women’s group, it was 18. Also the highest measured g-index in men’s group was 33 but in women’s group, it was 27. The highest m parameter for men’s group was 2.5 and for women’s group it was 2. H and g indexes and m parameter of 60 researchers (51.3% of the statistical population) were equal to zero. Total outcome of this study indicates that the majority of researchers in research institutions of Shahid Beheshti University have low h-index, g-index and m parameter. Also this study indicates that the researchers in Medical plants and drugs, Environmental Sciences and Laser and plasma research Institutions have a higher h-index, g-index and m parameter than researchers of Family research Institution and Quran miracle research Institution.

The aim of this study was to identify the effect of Altmetrics indexes of ResearchGate social network on scientometric indicators of Scopus, Web of Science, and Google Scholar citation databases. The present study is an applied research and descriptive-survey research that has been done by the scientometric method with the Altmetrics approach. The statistical population of the study includes Iranian researchers and writers in the field of nursing who in the period 2000-2019 and on the date of research (20/03/2020), had an indexed document in the Scopus citation database and were also a member of the scientific social network ResearchGate. The statistical sample of the study includes 158 high-profile authors introduced by Scopus. In addition to descriptive statistics, in the inferential statistics section, the correlation test between the studied indices has been used with the help of SPSS and Excel software.The research findings show that there is a significant relationship between most of the ResearchGate indices and the indices studied in Scopus, Web of Science, and Google Scholar. But there is no significant relationship between the index of followers with H-index indexes and citations received in Scopus and Web of Science databases. Examining the relationship between the number of citations received in Google Scholar, Scopus, and Web of Science databases shows that there is a significant relationship between the number of citations received in Scopus, Web of Science, and Google Scholar databases.

In this paper, we study the validity of the laws of thermodynamics in the form of a far parallel gravitational theory with an incomplete coupling between curves and scalar fields. To this end, we consider the FRW flat world, showing that the first and second laws of thermodynamics lie in its dynamic apparent horizon. We further assume that the universe is enclosed by the cosmological event horizon, such that in this case the first law of thermodynamics is valid, but the second law of thermodynamics is applied to the selected incomplete model, depending on the energy-momentum tensor components derived.

One of the most challenging and difficult aspects of translation is related to the translation of idioms by both machine systems and human translators. The problem arises from the recognition of the idioms on the one hand and translating them on the other hand. idiom recognition is not easy since an idiom may change its form based on the context in which it is used. Using systematic idiom collections and special rules to recognize idioms, the problem can be solved to a great extent. Moreover, the inclusion of a morphological as well as syntactic parser can greatly enhance the idiom recognition and translation process. The aim of this paper is twofold. First, we want to test Google Translate to see how well it is capable of translating idioms and next to provide means to improve the quality of translation of idioms by Google Translate.