scholarly journals Optical bandgap of semiconductor nanostructures: Methods for experimental data analysis

2017 ◽  
Vol 121 (23) ◽  
pp. 234304 ◽  
Author(s):  
R. Raciti ◽  
R. Bahariqushchi ◽  
C. Summonte ◽  
A. Aydinli ◽  
A. Terrasi ◽  
...  
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Semiconductor Nanostructures ◽  
Optical Bandgap ◽  
Experimental Data Analysis

THE “KVAZAR” PACKAGE FOR PATTERN RECOGNITION AND ITS APPLICATIONS

1993 ◽  
Vol 03 (04) ◽  
pp. 439-444 ◽  
Author(s):  
VLADIMIR S. KAZANTSEV
Keyword(s):  
Experimental Data ◽  
Pattern Recognition ◽  
Data Analysis ◽  
Linear Inequalities ◽  
Processing Data ◽  
Experimental Data Analysis ◽  
Ibm Pc

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.

scholarly journals Experimental Data Analysis During Initial In-DEBS Operation

2019 ◽  
Vol 17 (S) ◽  
pp. 81-95
Author(s):  
Young-Chul Choi ◽  
Won-Jin Cho ◽  
Jae Owan Lee ◽  
Geon Young Kim
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Experimental Data Analysis

scholarly journals Software Platform for European XFEL: Towards Online Experimental Data Analysis

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

Experimental Data Analysis of Nanoparticles for Enhanced Oil Recovery

2019 ◽  
Vol 58 (27) ◽  
pp. 12438-12450 ◽  
Author(s):  
Haifeng Ding ◽  
Na Zhang ◽  
Yandong Zhang ◽  
Mingzhen Wei ◽  
Baojun Bai
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Experimental Data Analysis

Integrating Experimental Data Analysis Through Online Modules

2013 ◽  
Author(s):  
Kumer V. Singh ◽  
Fazeel Khan ◽  
Neal S. Birchfield
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Student Perceptions ◽  
Mechanical Vibration ◽  
Mode Shapes ◽  
Wide Audience ◽  
Practical Applications ◽  
Learning Modules ◽  
Assessment Plans ◽  
Experimental Data Analysis

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.

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