Further development of microarea analysis techniques for determining nitrogen in steels

1987 ◽  
Vol 91 (1-6) ◽  
pp. 135-137 ◽  
Author(s):  
Siegfried Baumgartl ◽  
Achim Rüdiger Büchner ◽  
Willy-Günther Burchard ◽  
Hans-Joachim Dudek ◽  
Eberhard Norbert Haeussler ◽  
...  
Keyword(s):  
Analysis Techniques ◽  
Microarea Analysis ◽  
Further Development

Further development of microarea analysis techniques for determining nitrogen in steels

1987 ◽  
Vol 91 (1-6) ◽  
pp. 145-147 ◽  
Author(s):  
Harald Hantsche ◽  
Hans Joachim Dudek
Keyword(s):  
Analysis Techniques ◽  
Microarea Analysis ◽  
Further Development

Further development of microarea analysis techniques for determining nitrogen in steels

1987 ◽  
Vol 91 (1-6) ◽  
pp. 143-145 ◽  
Author(s):  
Hans Joachim Dudek ◽  
Harald Hantsche
Keyword(s):  
Analysis Techniques ◽  
Microarea Analysis ◽  
Further Development

Further development of microarea analysis techniques for determining nitrogen in steels

1987 ◽  
Vol 91 (1-6) ◽  
pp. 148-149 ◽  
Author(s):  
Daniel Schalkoord ◽  
Werner Rehbach ◽  
Ernst Schauf ◽  
Paul Schwaab
Keyword(s):  
Analysis Techniques ◽  
Microarea Analysis ◽  
Further Development

Further development of microarea analysis techniques for determining nitrogen in steels

1987 ◽  
Vol 91 (1-6) ◽  
pp. 140-141 ◽  
Author(s):  
Siegfried Baumgartl ◽  
Achim R�diger B�chner ◽  
Willy -G�nther Burchard ◽  
Eberhard Norbert Haeussler ◽  
Peter Karduck ◽  
...  
Keyword(s):  
Analysis Techniques ◽  
Microarea Analysis ◽  
Further Development

Student-Teacher: The Learning Machine as an Instructional Device

1988 ◽  
Vol 4 (1) ◽  
pp. 57-70
Author(s):  
Carol Scheftic ◽  
George Darlington Wood
Keyword(s):  
Functional Analysis ◽  
Expert System ◽  
Socratic Method ◽  
Educational Tool ◽  
System Technology ◽  
Solution Strategy ◽  
Analysis Techniques ◽  
Acquisition Device ◽  
Learning Machine ◽  
Further Development

This article presents QUERIOUS, an educational tool based on expert system technology, functional analysis techniques, and Socratic method. Using a knowledge acquisition device originally developed to allow specialists to impart their knowledge to expert systems, our tool asks students questions, leads them through functional analysis of a problem and, in effect, induces them to teach the system their solution strategy. An existing prototype is described, and a proposal for further development is presented.

scholarly journals Analytical Dissection of an Automotive Li-Ion Pouch Cell

Batteries ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 67 ◽  
Author(s):  
Kovachev ◽  
Schröttner ◽  
Gstrein ◽  
Aiello ◽  
Hanzu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Measured Data ◽  
Li Ion Batteries ◽  
Complete Sample ◽  
Analytical Methodology ◽  
Preparation Methods ◽  
Analysis Techniques ◽  
Sample Preparation Procedure ◽  
Li Ion ◽  
Further Development

Information derived from microscopic images of Li-ion cells is the base for research on the function, the safety, and the degradation of Li-ion batteries. This research was carried out to acquire information required to understand the mechanical properties of Li-ion cells. Parameters such as layer thicknesses, material compositions, and surface properties play important roles in the analysis and the further development of Li-ion batteries. In this work, relevant parameters were derived using microscopic imaging and analysis techniques. The quality and the usability of the measured data, however, are tightly connected to the sample generation, the preparation methods used, and the measurement device selected. Differences in specimen post-processing methods and measurement setups contribute to variability in the measured results. In this paper, the complete sample preparation procedure and analytical methodology are described, variations in the measured dataset are highlighted, and the study findings are discussed in detail. The presented results were obtained from an analysis conducted on a state-of-the-art Li-ion pouch cell applied in an electric vehicle that is currently commercially available.

scholarly journals Quality characterization of wine cork stoppers using computer vision

OENO One ◽  
2005 ◽  
Vol 39 (4) ◽  
pp. 209 ◽  
Author(s):  
Augusta Costa ◽  
Helena Pereira
Keyword(s):  
Mean Values ◽  
Maximum Area ◽  
Analysis Techniques ◽  
Increasing Trend ◽  
Porosity Coefficient ◽  
Medium Quality ◽  
Further Development ◽  
Cork Stoppers ◽  
Image Analysis Techniques

<p style="text-align: justify;">Image analysis techniques were applied on the surface of wine cork stoppers (tops and lateral cylindrical surface) of seven commercial quality classes to characterize their porosity. An increasing trend from the best to the worst quality classes was found for features related to area of pores (i.e. maximum length and width or pore maximum area) and concentration variables (i.e. porosity coefficient or number of pores per 100 cm2). Shape variables were rather constant and mean values showed no differences between quality classes. Variation of the pores characteristics within each quality class was large especially in the mid-quality range. Therefore there were no statistically significant differences to allow the isolation of the all quality classes and overlapping was particularly important in the medium-quality classes. The reduction of grading into only three quality classes allowed to isolate statistically different subsets based on porosity coefficient and number of pores per 100 cm2. These variables can be selected for further development into quality grades specification of wine cork stoppers.</p>

scholarly journals How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques

2018 ◽  
Author(s):  
Breght Vandenberghe ◽  
Stephen Depuydt ◽  
Arnout Van Messem
Keyword(s):  
Machine Vision ◽  
Large Scale ◽  
Three Dimensional ◽  
Plant Phenotyping ◽  
Small Scale ◽  
Dimensional Approach ◽  
Crop Monitoring ◽  
Analysis Techniques ◽  
Further Development ◽  
3D Representations

Machine vision technology is moving more and more towards a three-dimensional approach, and plant phenotyping is following this trend. However, despite its potential, the complexity of the analysis of 3D representations has been the main bottleneck hindering the wider deployment of 3D plant phenotyping. In this review we provide an overview of typical steps for the processing and analysis of 3D representations of plants, to offer potential users of 3D phenotyping a first gateway into its application, and to stimulate its further development. We focus on plant phenotyping applications where the goal is to measure characteristics of single plants or crop canopies on a small scale in research settings, as opposed to large scale crop monitoring in the field.

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