scholarly journals An intelligent sampling framework for controlled experimentation and QoE modeling

2018 ◽  
Vol 147 ◽  
pp. 246-261 ◽  
Author(s):  
Muhammad Jawad Khokhar ◽  
Nawfal Abbassi Saber ◽  
Thierry Spetebroot ◽  
Chadi Barakat
Keyword(s):  
Intelligent Sampling ◽  
Controlled Experimentation

scholarly journals HESS Opinions On the use of laboratory experimentation: "Hydrologists, bring out shovels and garden hoses and hit the dirt"

2010 ◽  
Vol 14 (2) ◽  
pp. 369-382 ◽  
Author(s):  
M. G. Kleinhans ◽  
M. F. P. Bierkens ◽  
M. van der Perk
Keyword(s):  
Data Analysis ◽  
Laboratory Experiments ◽  
Field Work ◽  
Experimental Investigations ◽  
Top Down ◽  
Laboratory Experimentation ◽  
Controlled Experimentation ◽  
Modelling Approaches

Abstract. From an outsider's perspective, hydrology combines field work with modelling, but mostly ignores the potential for gaining understanding and conceiving new hypotheses from controlled laboratory experiments. Sivapalan (2009) pleaded for a question- and hypothesis-driven hydrology where data analysis and top-down modelling approaches lead to general explanations and understanding of general trends and patterns. We discuss why and how such understanding is gained very effectively from controlled experimentation in comparison to field work and modelling. We argue that many major issues in hydrology are open to experimental investigations. Though experiments may have scale problems, these are of similar gravity as the well-known problems of fieldwork and modelling and have not impeded spectacular progress through experimentation in other geosciences.

scholarly journals Development of surface reconstruction algorithms for optical interferometric measurement

2020 ◽  
Author(s):  
Dongxu Wu ◽  
Fengzhou Fang
Keyword(s):  
Surface Topography ◽  
Dynamic Range ◽  
Functional Performance ◽  
Theoretical Background ◽  
Optical Interferometry ◽  
Reconstruction Algorithms ◽  
Fringe Analysis ◽  
Intelligent Sampling ◽  
On Line ◽  
Accuracy And Repeatability

AbstractOptical interferometry is a powerful tool for measuring and characterizing areal surface topography in precision manufacturing. A variety of instruments based on optical interferometry have been developed to meet the measurement needs in various applications, but the existing techniques are simply not enough to meet the ever-increasing requirements in terms of accuracy, speed, robustness, and dynamic range, especially in on-line or on-machine conditions. This paper provides an in-depth perspective of surface topography reconstruction for optical interferometric measurements. Principles, configurations, and applications of typical optical interferometers with different capabilities and limitations are presented. Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensing and phase-shifting algorithm, are summarized. The new developments in measurement accuracy and repeatability, noise resistance, self-calibration ability, and computational efficiency are discussed. This paper also presents the new challenges that optical interferometry techniques are facing in surface topography measurement. To address these challenges, advanced techniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning are explored to improve the functional performance of optical interferometry in future manufacturing metrology.

The technique of controlled experimentation.

2011 ◽  
pp. 445-478
Author(s):  
Charles C. Peters ◽  
Walter R. Van Voorhis
Keyword(s):  
Controlled Experimentation
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