G CF-Observable Parameter Space for Twist and Pose Measurements

2005 ◽  
pp. 235-239
Author(s):  
Tine Lefebvre ◽  
Herman Bruyninckx ◽  
Joris De Schutter
Keyword(s):  
Parameter Space ◽  
Observable Parameter

scholarly journals A high-dimensional look at VIPERS galaxies

2014 ◽  
Vol 10 (S306) ◽  
pp. 369-371
Author(s):  
Benjamin R. Granett ◽  
Keyword(s):  
Complex Formation ◽  
Dimensional Analysis ◽  
Parameter Space ◽  
Local Environment ◽  
Density Field ◽  
High Dimensional ◽  
Redshift Survey ◽  
Cosmological Tests ◽  
Residual Correlations ◽  
Observable Parameter

AbstractWe investigate how galaxies in VIPERS (the VIMOS Public Extragalactic Redshift Survey) inhabit the cosmological density field by examining the correlations across the observable parameter space of galaxy properties and clustering strength. The high-dimensional analysis is made manageable by the use of group-finding and regression tools. We find that the major trends in galaxy properties can be explained by a single parameter related to stellar mass. After subtracting this trend, residual correlations remain between galaxy properties and the local environment pointing to complex formation dependencies. As a specific application of this work we build subsamples of galaxies with specific clustering properties for use in cosmological tests.

Detachment of biofilm bacteria due to variations in nutrient supply

1998 ◽  
Vol 37 (4-5) ◽  
pp. 211-214 ◽  
Author(s):  
Linda K. Sawyer ◽  
Slawomir W. Hermanowicz
Keyword(s):  
Phase Contrast ◽  
Digital Image Analysis ◽  
Specific Growth ◽  
Nutrient Supply ◽  
Surface Shear Stress ◽  
Surface Shear ◽  
Nutrient Limitations ◽  
Contrast Microscopy ◽  
Biofilm Bacteria ◽  
Observable Parameter

Growth and detachment rates of an environmental isolate of Aeromonas hydrophila attached to a surface were determined under varying nutrient supply conditions in a complex medium. Growth and detachment of cells were observed in real time using phase contrast microscopy in glass parallel plate flow chambers. Surface shear stress was controlled in all experiments at 3 N m−2. Images were taken every 15 min. Digital image analysis was used to determine specific growth and detachment rates. An observable parameter proportional to the nutrient depletion at the surface due to transfer limitations was used to indicate nutrient limitations. Specific detachment rates increased as the depletion parameter increased, indicating that nutrient limitations cause this bacterium to detach at greater rates.

Investigation of the applicability domains of the bubble cluster mathematical model

2011 ◽  
Vol 8 (1) ◽  
pp. 65-73
Author(s):  
E.Sh. Nasibullaeva ◽  
I.Sh. Akhatov
Keyword(s):  
Mathematical Model ◽  
Parameter Space ◽  
Acoustic Field ◽  
Initial Radius ◽  
Large Drop ◽  
Bubble Cluster ◽  
The Mathematical Model

The mathematical model of a bubble cluster subjected to an acoustic field is investigated. In this model the cluster is considered as a large drop containing a liquid and a set of microbubbles. Areas of applicability of the mathematical model of the bubble cluster in the parameter space (α, R_0) are constructed, where α is the bubble concentration in the cluster; R_0 is the initial radius of the cluster.

Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine

2019 ◽  
Vol 22 (1) ◽  
pp. 6-17 ◽  
Author(s):  
Elisabeth Reinhardt ◽  
Ahmed M. Salaheldin ◽  
Monica Distaso ◽  
Doris Segets ◽  
Wolfgang Peukert
Keyword(s):  
Parameter Space ◽  
Space Exploration ◽  
Rapid Characterization

scholarly journals Search Acceleration of Evolutionary Multi-Objective Optimization Using an Estimated Convergence Point

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 129 ◽  
Author(s):  
Yan Pei ◽  
Jun Yu ◽  
Hideyuki Takagi
Keyword(s):  
Parameter Space ◽  
Statistical Tests ◽  
Distribution Characteristic ◽  
Multi Objective Optimization ◽  
Pareto Improvement ◽  
Pareto Solutions ◽  
Pareto Solution ◽  
Multi Objective ◽  
Objective Space ◽  
Convergence Point

We propose a method to accelerate evolutionary multi-objective optimization (EMO) search using an estimated convergence point. Pareto improvement from the last generation to the current generation supports information of promising Pareto solution areas in both an objective space and a parameter space. We use this information to construct a set of moving vectors and estimate a non-dominated Pareto point from these moving vectors. In this work, we attempt to use different methods for constructing moving vectors, and use the convergence point estimated by using the moving vectors to accelerate EMO search. From our evaluation results, we found that the landscape of Pareto improvement has a uni-modal distribution characteristic in an objective space, and has a multi-modal distribution characteristic in a parameter space. Our proposed method can enhance EMO search when the landscape of Pareto improvement has a uni-modal distribution characteristic in a parameter space, and by chance also does that when landscape of Pareto improvement has a multi-modal distribution characteristic in a parameter space. The proposed methods can not only obtain more Pareto solutions compared with the conventional non-dominant sorting genetic algorithm (NSGA)-II algorithm, but can also increase the diversity of Pareto solutions. This indicates that our proposed method can enhance the search capability of EMO in both Pareto dominance and solution diversity. We also found that the method of constructing moving vectors is a primary issue for the success of our proposed method. We analyze and discuss this method with several evaluation metrics and statistical tests. The proposed method has potential to enhance EMO embedding deterministic learning methods in stochastic optimization algorithms.

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