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Understanding the Correlations between Social Attention and Topic Trends of Scientific Publications

. Scott and Varian (2014) predicted weekly initial claims for unemployment and monthly retail sales using Google Trends and Google Correlate data. These evidences indicate that a range of patterns can be discovered by analyzing people’s behaviors and their topically relevant online activities in social media. In a similar vein, the proposed work seeks to understand whether there is the correlation between the major social media Google Trend and scientific topics in academic publications. Correlation analysis identifies the degree of relationship or dependency between

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Methods and Practices for Institutional Benchmarking based on Research Impact and Competitiveness: A Case Study of ShanghaiTech University

proliferation, cell lung cancer and hippo pathway. These six clusters have a strong linkage correlation ( Figure 2b) . Compared to Univ E, it seems that ShanghaiTech has narrower research coverage and the linkage connections are sparser, which might be one of the reasons of relatively lower citations and impact. The distributions themselves should be compared cautiously. Each institution has its selected focuses in research topics so the maps will naturally differ. Moreover, in itself such a map does not provide information on the quality, impact or leading capacity. Hence

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Waterfilling: Balancing the Tor network with maximum diversity

IEEE Computer Security Foundations Symposium , pages 3–12. IEEE, 2009. [22] A. Johnson, C. Wacek, R. Jansen, M. Sherr, and P. Syverson. Users get routed: Traffic correlation on tor by realistic adversaries. In Proceedings of the 20th ACM conference on Computer and Communications Security (CCS 2013) , November 2013. [23] J. Juen, A. Johnson, A. Das, N. Borisov, and M. Caesar. Defending tor from network adversaries: A case study of network path prediction. Proceedings on Privacy Enhancing Technologies , 2015(2):171–187, 2015. [24] B. N. Levine, M. K

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Possibilities to Use a Virtual Opponent for Enhancements of Reactions and Perception of Young Karate Athletes


We conducted a virtual reality (VR) training with ten sessions, performed by fifteen young karate athletes, who responded to attacks of a virtual opponent to improve their response behavior and their decision-making. The control groups continued with their normal training. Results of the Friedman tests with subsequent Dunn-Bonferroni post-hoc-tests and estimation of effect sizes showed that the karate specific response behavior (measured by a movement analysis) improved significantly due to the training. The parameters time for response (as the time for the attack initiation) and response quality improved with large effect sizes for the intervention groups, whereas the control groups demonstrated improvements with only small effect sizes. The unspecific response behavior (analyzed by two forms of the reaction test of the Vienna test system) did not show any significant changes. Paired t-tests revealed an improvement in attack recognition. While in the pretests, the intervention groups responded to late movement stages of the attack (execution of the main phase), they responded to early movement stages (reduction of distance and preparing steps) in the posttests. Furthermore, Friedman-tests and bivariate correlation analysis showed that the intervention groups were highly motivated to perform the VR training because of the new and safe learning conditions.

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How Users Search the Mobile Web: A Model for Understanding the Impact of Motivation and Context on Search Behaviors

-structured interviews with participants. 3.3 Data Analysis Methods In this paper, we define mobile search context as the personal attributes and surroundings of the participants when doing mobile search, including the physical environment (e.g. indoor, outdoor, and specific place) and the social environment (e.g. alone or with others). There are 12 defined dimensions of participants’ mobile search context ( Table 1 ), which can be divided into three categories. We get this information from the structured diary and the phone log, and do correlation analysis or difference

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Is Participating in MOOC Forums Important for Students? A Data-driven Study from the Perspective of the Supernetwork

than the average forum participants. From these studies, it is not hard to find that there is a distinct correlation between forum participation and higher grades. Other researches addressing the MOOC forum include Yang et al. (2014) explored how peer relations in MOOC forums influence student dropout rates. Rossi et al. (2014) and Stump et al. (2013) both analyzed forum content and classified discussion forum posts. Using standard social network analytic techniques, Yang et al. (2013) explored factors related to student behavior and social positioning

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Digitizing Dunhuang Cultural Heritage: A User Evaluation of Mogao Cave Panorama Digital Library

.9 Synchronicity 4 4.0 Correlation analyses among task completion time, success rate, user satisfaction, and interactivity reveal that satisfaction and interactivity are significantly correlated (Spearman’s rank-order correlation coefficient ρ = 0.864, p = 0.000). In other words, the higher rates on interactivity participants gave, the higher satisfaction levels they would have as well. Besides, the results also show a positive and moderate correlation between task completion time and success rate, indicating that the more time spent on completing the tasks

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Comparative Study of Trace Metrics between Bibliometrics and Patentometrics

proven by their above-average C / P values. Figure 2 Academic traces T l , T 2 , and ST ; citations per paper ( C / P ), and h -index for the top 30 universities in computer sciences (2010–2014). Table 1 shows Pearson (bottom left part of the table, with no background) and Spearman (top right part of the table, with a gray background) correlation coefficients among T 1 , T 2 , ST , C / P , and the h -index. The three trace metrics can be divided into two groups: The first group contained T 1 and ST , which had high correlation

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Gauging a Firm’s Innovative Performance Using an Integrated Structural Index for Patents

Tables A2 and A3 ), and calculated the corresponding Sh index. 4.3 Statistical Methods To observe the relationship between the S h ( Y ) and a firm’s profits, we use two different statistical methods: We calculated the Spearman rank correlation coefficient between the eight companies, mean S h ( Y ) and mean SS h ( Y ) values and total profits over the period from 2006 to 2010. A nested case-control (NCC) study. This type of study is an observational study whereby a case-control approach is employed within an established cohort ( Bornehag et al

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Mining Related Articles for Automatic Journal Cataloging

To measure the quality of retrieved related articles through the content-similarity-based approach, we use the following metrics. 2.4.1 Pearson Correlation Coefficients To measure how well the related journals generated based on content similarity correlate with the ranking of journals, we used the article usage data in the log. Suppose X = [ x 1 , x 2 ,…, x n ] and Y = [ y 1 , y 2 ,…, y n ] are a series of predicted and actual clicking numbers of n articles, respectively, the sample correlation coefficient is used to estimate the Pearson

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