Browsing by Subject "Longitudinal analysis"

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Open Access
Braph : a toolbox developed for brain graph analysis of various imaging modalities
(2017-03) Kakaei, Ehsan
Complex systems, like the human brain, are composed of a huge number of interacting elements showing complex patterns. Graph theory provides a mathematical toolbox for investigating the role of each element in these systems. With the rise of interest in applying this method for studying brain networks, several software have been developed to allow researches conduct brain network analysis. However, a comprehensive and an easy-to-use toolbox is still lacking. BRAPH is the first object-oriented toolbox that provides users the ability of constructing and analyzing brain networks out of data acquired from various imaging modalities. For this purpose, multiple graphical user interfaces (GUIs) have been designed that allow the users to import or build brain atlases, along with cohort of subjects, prior to starting the graph analysis. Various graph measures for both weighted graphs and binary graphs, comparison between groups, comparison with random graphs, longitudinal analysis and statistical analysis, are only some of the analysis tools embedded in BRAPH.
Open Access
Longitudinal analysis of search engine query logs - temporal coverage
(2012) Yılmaz, Oğuz
The internet is growing day-by-day and the usage of web search engines is continuously increasing. Main page of browsers started by internet users is typically the home page of a search engine. To navigate a certain web site, most of the people prefer to type web sites’ name to search engine interface instead of using internet browsers’ address bar. Considering this important role of search engines as the main entry point to the web, we need to understand Web searching trends that are emerging over time. We believe that temporal analysis of returned query results by search engines reveals important insights for the current situation and future directions of web searching. In this thesis, we provide a large-scale analysis of the evolution of query results obtained from a real search engine at two distant points in time, namely, in 2007 and 2010, for a set of 630000 real queries. Our analyses in this work attempt to find answers to several critical questions regarding the evolution of Web search results. We believe that this work, being a large-scale longitudinal analysis of query results, would shed some light on those questions.