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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
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Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Jamshidi, M., Châtelain, J.-F., Rimpault, X., & Balazinski, M. (2022). Tool condition monitoring based on the fractal analysis of current and cutting force signals during CFRP trimming. International Journal of Advanced Manufacturing Technology, 121(11-12), 8127-8142. External link
Jamshidi, M., Châtelain, J.-F., Rimpault, X., & Balazinski, M. (2022). Tool Condition Monitoring Using Machine Tool Spindle Electric Current and Multiscale Analysis while Milling Steel Alloy. Journal of Manufacturing and Materials Processing, 6(5), 115 (12 pages). External link
Jamshidi, M., Rimpault, X., Balazinski, M., & Chatelain, J.-F. (2020). Fractal analysis implementation for tool wear monitoring based on cutting force signals during CFRP/titanium stack machining. International Journal of Advanced Manufacturing Technology, 106(9-10), 3859-3868. External link
Jamshidi, M. (2018). Tool Wear Monitoring Based on Fractal Analysis of Cutting Force Signals While Machining Titanium Alloy Within CFRP/Titanium Stack [Master's thesis, École Polytechnique de Montréal]. Available