Integrating Experimental Data Analysis Through Online Modules

Author(s):  
Kumer V. Singh ◽  
Fazeel Khan ◽  
Neal S. Birchfield

In various universities, including Miami University (MU), an undergraduate course in vibrations may be offered in a lecture-only format. However, several concepts in vibrations, such as natural frequencies, damping, mode shapes etc., may be improved immensely from experimental demonstrations and hands-on activities for students to fully grasp the concept and its application. In recent years, several online experiments and resources have been developed in the area of dynamical systems and controls in order to provide an experiential learning environment. With the support of the National Science Foundation, a series of Computational-Experimental (ComEx) learning modules are being developed for integrating experimental, computational and validation studies in the mechanical and manufacturing engineering curriculum at MU. These learning modules are web based and are intended for dissemination to a wide audience extending beyond the students at MU. In this paper, salient features of these online learning modules, which integrate experimental data analysis for mechanical vibration course, are presented. Three different group activities associated with these modules are presented with specific details of the activities, assessment plans, and student perceptions of the modules. The content of these modules is evolving based on feedback from students and external, expert evaluators. It is anticipated that such learning studios can be used by instructors who teach lecture based vibration and control courses, and this resource will yield more insight into the theory, computation and practical applications of essential concepts in this area.

Author(s):  
VLADIMIR S. KAZANTSEV

The package of applied programs named KVAZAR has been elaborated to be used for classification, diagnostic, predicative, experimental data analysis problems. The package may be used in medicine, biology, geology, economics, engineering and some other problems. The algorithmical base of the package is the method of pattern recognition, based on the linear inequalities and committee constructions. Other algorithms are used too. The package KVAZAR is intended to be used with IBM PC AT/XT. The range of processing data is bounded by 40,000 numbers.


Author(s):  
Young-Chul Choi ◽  
Won-Jin Cho ◽  
Jae Owan Lee ◽  
Geon Young Kim

2018 ◽  
Vol 39 (9) ◽  
pp. 1170-1178 ◽  
Author(s):  
S. A. Bobkov ◽  
A. B. Teslyuk ◽  
S. I. Zolotarev ◽  
M. Rose ◽  
K. A. Ikonnikova ◽  
...  

2019 ◽  
Vol 58 (27) ◽  
pp. 12438-12450 ◽  
Author(s):  
Haifeng Ding ◽  
Na Zhang ◽  
Yandong Zhang ◽  
Mingzhen Wei ◽  
Baojun Bai

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