Studying the outputs and mapping the co-author network of Semnan University researchers in the Web of Science Indexes

Background and Objectives: One of the areas of research and study in Scientometrics is scientific collaborative studies. Katz and Martin (1997) define scientific collaboration as working with other researchers in order to achieve common goals for the production of new knowledge. This collaboration has several aspects one of which is co-authorship. Co-authorship can occur in scientific productions such as paper, notebooks and so on. In recent years, scientific collaboration, and especially co-authorship, has grown exponentially among authors and researchers. Perhaps this increasing growth can be attributed to the benefits that scientific collaboration holds for authors and their works. This research evaluates the scientific production of researchers based on Scientometrics indicators such as growth rate, cooperative indices, the most prolific researchers and their Hirsch index, analyzing the components of the co-authorship network of researchers, and investigating the structures existing in co-authorship networks using social network analysis and based on the Centrality measure such as degree, betweenness, eigenvectors and closeness. Also, the density measures, the coefficient of clustering, the distance between nodes and subgroups are also calculated and determined. The aim of this article was to study the scientific outputs of Semnan university researchers in term of quantitative indexes (number of outputs, research area, and year) and qualitative indexes (number of citations and H-Index). Mapping the co-author network of Semnan university researchers in the Web of Science database was the other purpose of the present paper. Methodology: The research was conducted based on Scientometrics methods. The research population included all the documents which mentioned Semnan University as their affiliation and were indexed in Web of Science from 1990 to 2015. Totally, 2106 documents were indexed in this timespan. The co-author network was mapped and analyzed by Coau.exe, Ucinet and Netdraw. In order to analyze the data, different software and measures were used. For this purpose, the data were first analyzed by coauthor.exe software and the authorship matrix was formed. The obtained matrix was a symmetric matrix 194 * 194, in which the diagonal cells were set to zero. Then the matrix was imported into the UCInet software to provide the proper format required for drawing software. After obtaining the outputs from the UCInet software, to draw up a map of the co-authorship the NetDraw software was used. Also, for all authors and researchers of the Semnan University, the h index was calculated using the Web of Science and the authors with the highest h index were identified. Findings: The results showed that Engineering (39%), Physics (19.5) and Mathematics (14%) were the subjects to which Semnan university researchers contributed. Totally, in the time span investigated, Iranian researchers produced 272019 documents out of which 2106 belonged to Semnan University. Therefore, this university ranked 30 among the Iranian universities. During the period studied, Semnan University produced 0.0049% of the universal scientific outputs. The results of the growth rate calculation indicated 43.22 for Semnan University researchers in the past fifty years that reveals a promising rising growth rate. Amjadi, Gorji and Orouji with 25, 23 and 15 H-Indexs ranked first to third, respectively. In term of citation, Amjadi ranked first with 2126 citations and Gorji with 1341 and Orouji with 629 citations were in the next ranks. Investigating the degree from among the centrality measurements was also calculated and the results showed that Gorji, Fereydoun and Asghari were in the top. The highest co-authoring rate occurred in 2005 which included 3 authors. As regards the fields of study, mathematics was the highest single-author subject. After obtaining the number of co-authorship of documents in different years, three indicators of co-authorship, including the cooperation index, degree of collaborative and Collaborative coefficient, were obtained, which showed that these collaborative indicators have increased significantly during the studied years. Also, there has been an increasing trend in two indicators of degree of collaborative and collaborative coefficient with several fluctuations over several years in general. The average of these three indicators for the whole years was 2.52, 0.84 and 0.50 respectively. Discussion: The results of data analysis showed that, although the flow of co-authorship among the Semnan University researchers has fluctuated in recent years, during the studied period, the researchers of Semnan University have tended to write co-authorship. Generally, documents with three authors were the most co-authorship. The results also showed that the co-authorship network of Semnan University researchers consisted of 6 main components and 7 isolated authors. The largest cluster composed of 171 authors. The smaller cluster comprised of 7 authors and the other clusters included two. Also, subject areas of engineering, physics and mathematics scored the highest number of articles among Semnan University researchers

Studying the outputs and mapping the co-author network of Semnan University researchers in the Web of Science Indexes

Background and Objectives: One of the areas of research and study in Scientometrics is scientific collaborative studies. Katz and Martin (1997) define scientific collaboration as working with other researchers in order to achieve common goals for the production of new knowledge. This collaboration has several aspects one of which is co-authorship. Co-authorship can occur in scientific productions such as paper, notebooks and so on. In recent years, scientific collaboration, and especially co-authorship, has grown exponentially among authors and researchers. Perhaps this increasing growth can be attributed to the benefits that scientific collaboration holds for authors and their works. This research evaluates the scientific production of researchers based on Scientometrics indicators such as growth rate, cooperative indices, the most prolific researchers and their Hirsch index, analyzing the components of the co-authorship network of researchers, and investigating the structures existing in co-authorship networks using social network analysis and based on the Centrality measure such as degree, betweenness, eigenvectors and closeness. Also, the density measures, the coefficient of clustering, the distance between nodes and subgroups are also calculated and determined. The aim of this article was to study the scientific outputs of Semnan university researchers in term of quantitative indexes (number of outputs, research area, and year) and qualitative indexes (number of citations and H-Index). Mapping the co-author network of Semnan university researchers in the Web of Science database was the other purpose of the present paper. Methodology: The research was conducted based on Scientometrics methods. The research population included all the documents which mentioned Semnan University as their affiliation and were indexed in Web of Science from 1990 to 2015. Totally, 2106 documents were indexed in this timespan. The co-author network was mapped and analyzed by Coau.exe, Ucinet and Netdraw. In order to analyze the data, different software and measures were used. For this purpose, the data were first analyzed by coauthor.exe software and the authorship matrix was formed. The obtained matrix was a symmetric matrix 194 * 194, in which the diagonal cells were set to zero. Then the matrix was imported into the UCInet software to provide the proper format required for drawing software. After obtaining the outputs from the UCInet software, to draw up a map of the co-authorship the NetDraw software was used. Also, for all authors and researchers of the Semnan University, the h index was calculated using the Web of Science and the authors with the highest h index were identified. Findings: The results showed that Engineering (39%), Physics (19.5) and Mathematics (14%) were the subjects to which Semnan university researchers contributed. Totally, in the time span investigated, Iranian researchers produced 272019 documents out of which 2106 belonged to Semnan University. Therefore, this university ranked 30 among the Iranian universities. During the period studied, Semnan University produced 0.0049% of the universal scientific outputs. The results of the growth rate calculation indicated 43.22 for Semnan University researchers in the past fifty years that reveals a promising rising growth rate. Amjadi, Gorji and Orouji with 25, 23 and 15 H-Indexs ranked first to third, respectively. In term of citation, Amjadi ranked first with 2126 citations and Gorji with 1341 and Orouji with 629 citations were in the next ranks. Investigating the degree from among the centrality measurements was also calculated and the results showed that Gorji, Fereydoun and Asghari were in the top. The highest co-authoring rate occurred in 2005 which included 3 authors. As regards the fields of study, mathematics was the highest single-author subject. After obtaining the number of co-authorship of documents in different years, three indicators of co-authorship, including the cooperation index, degree of collaborative and Collaborative coefficient, were obtained, which showed that these collaborative indicators have increased significantly during the studied years. Also, there has been an increasing trend in two indicators of degree of collaborative and collaborative coefficient with several fluctuations over several years in general. The average of these three indicators for the whole years was 2.52, 0.84 and 0.50 respectively. Discussion: The results of data analysis showed that, although the flow of co-authorship among the Semnan University researchers has fluctuated in recent years, during the studied period, the researchers of Semnan University have tended to write co-authorship. Generally, documents with three authors were the most co-authorship. The results also showed that the co-authorship network of Semnan University researchers consisted of 6 main components and 7 isolated authors. The largest cluster composed of 171 authors. The smaller cluster comprised of 7 authors and the other clusters included two. Also, subject areas of engineering, physics and mathematics scored the highest number of articles among Semnan University researchers

Comparing "pick and place" task in spatial Augmented Reality versus non-immersive Virtual Reality for rehabilitation setting.

Introducing computer games to the rehabilitation market led to development of numerous Virtual Reality (VR) training applications. Although VR has provided tremendous benefit to the patients and caregivers, it has inherent limitations, some of which might be solved by replacing it with Augmented Reality (AR). The task of pick-and-place, which is part of many activities of daily living (ADL's), is one of the major affected functions stroke patients mainly expect to recover. We developed an exercise consisting of moving an object between various points, following a flash light that indicates the next target. The results show superior performance of subjects in spatial AR versus non-immersive VR setting. This could be due to the extraneous hand-eye coordination which exists in VR whereas it is eliminated in spatial AR

Using visible and near infrared spectroscopy to estimate carbonates and gypsum in soils in arid and subhumid regions of Isfahan, Iran

Soils in arid and semi-arid regions are strongly affected by the accumulation of carbonates, gypsum and other, more soluble, salts. Carbonates and gypsum both have a considerable influence on soil properties, especially the chemical properties of the soil solution. The development of reliable, fast and inexpensive methods to quantify the amounts of carbonates and gypsum in soil is therefore important. Visible and near infrared (vis-NIR) spectroscopy is a non-destructive, rapid and cheap method for measuring several soil properties simultaneously. However, research on vis-NIR spectroscopy in quantifying carbonates and gypsum is limited. Therefore, this study evaluated the efficiency of vis-NIR spectroscopy in quantifying carbonates and gypsum in surface soils using partial least-squares regression (PLSR) compared with standard laboratory methods and compared PLSR with a feature-specific method using continuum removal (CR). Carbonates and gypsum in a total of 251 sieved and air-dried topsoil samples from Isfahan Province in central Iran were measured by standard laboratory methods and vis-NIR spectroscopy (350–2500 nm wavelength range). In parallel, PLSR and the feature-specific method based on CR spectra were used to predict carbonates and gypsum. The PLSR model efficiency (E) for carbonates and gypsum in the validation set was 0.52 and 0.80, respectively. The PLSR model resulted in better predictions than the feature-specific method for both soil properties. Because of the unique absorption features of gypsum, which did not overlap with other soil properties, predictions of gypsum resulted in higher E values and lower errors than predictions of carbonates

Introducing a new rock abrasivity index using a scaled down disc cutter

Rock abrasivity influences wear of cutting tools and consequently, performance of mechanized tunneling machines. Several methods have been proposed to evaluate rock abrasivity in recent decades, each one has its own advantages. In this paper, a new method is introduced to estimate wear of disc cutters based on rock cutting tests using scaled down discs (i.e. 54 and 72 mm diameter). The discs are made of H13 steel, which is a common steel type in producing real-scale discs, with hardness of 32 and 54 HRC. The small-scale linear rock cutting machine and a new abrasion test apparatus, namely University of Tehran abrasivity test machine, are utilized to perform the tests. Tip width of the worn discs is monitored and presented as the function of the accumulated test run to classify the rock abrasion. Abrasivity tests show that by increasing the UCS of the rock samples, wear rate is doubled gradually that reveals the sensitivity of the test procedure to the main parameters affecting the abrasivity of hard rocks. For the rocks with the highest UCS, the normal wear stops after performing 5 to 10 rounds of the tests, and then, deformation of the disc tip is detectable. Two abrasivity indices are defined based on the abrasivity tests results and their correlations with CAI and UCS are established. Comparison of the established correlations in this study with previous investigations demonstrates the sensitivity of the indices to the parameters affecting wear of the disc cutters and repeatability of the outputs obtained from abrasivity tests using scaled down discs. Findings of this study can be used to enhance the accuracy of rock abrasivity classifications