Presentation | 2011-11-21 State Recognition of Remote Classrooms Using Fuzzy Classifiers : Toward Ubiquitous Classrooms Atsushi Inoue, Isaac Schlittenhart, Maxwell Yardley, |
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Abstract(in English) | Our ultimate goal is to establish technologies and guidelines so that remote classrooms are arranged ubiquitously. Sample arrangement may include: traditional schooling, teleconference calls, from a remote classroom, etc. While each arrangement has been reasonably well supported, there is hardly any technology that enables a good interface to instructors by seemlessly integrating all of above arrangements. We are developing a robust and intelligent autopilot in order to recognize states of students in a remote classroom that can be integrated in any of such cases. Such an autopilot is capable of informing instructors whether students in remote classrooms need attentions without imposing device operations. This autopilot utilizes fuzzy classifiers as a state recognizer (in a sense of Automata) in order to recognize various states of students in a remote classroom. In this paper, we report our progress, e.g. modeling, experiments and a system development - simple but robust. |
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Paper # | AI2011-17 |
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Committee | AI |
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Conference Date | 2011/11/14(1days) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | State Recognition of Remote Classrooms Using Fuzzy Classifiers : Toward Ubiquitous Classrooms |
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1st Author's Name | Atsushi Inoue |
1st Author's Affiliation | Eastern Washington University() |
2nd Author's Name | Isaac Schlittenhart |
2nd Author's Affiliation | Eastern Washington University |
3rd Author's Name | Maxwell Yardley |
3rd Author's Affiliation | Eastern Washington University |
Date | 2011-11-21 |
Paper # | AI2011-17 |
Volume (vol) | vol.111 |
Number (no) | 310 |
Page | pp.pp.- |
#Pages | 5 |
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