EXTRACT PHASE

2006 ◽  
Vol e ◽  
Keyword(s):  
Extract Phase

Phase Learning to Extract Phase from Forelimb(s) and Hindlimb(s) Movement in Real Time

2021 ◽  
Author(s):  
Dollapom Anopas ◽  
Junquan Lin ◽  
Seng Kwee Wee ◽  
Peh Er Tow ◽  
Sing Yian Chew ◽  
...  
Keyword(s):  
Real Time ◽  
Extract Phase

Solvent extraction of chlorinated compounds from soils and hydrodechlorination of the extract phase

2009 ◽  
Vol 162 (2-3) ◽  
pp. 661-667 ◽  
Author(s):  
Fabio Murena ◽  
Francesco Gioia
Keyword(s):  
Solvent Extraction ◽  
Chlorinated Compounds ◽  
Extract Phase

scholarly journals Direct estimation method to extract phase velocities of Rayleigh waves in microtremors using circular arrays

2005 ◽  
Vol 58 (6) ◽  
pp. 643-651 ◽  
Author(s):  
Hidetaka Shiraishi ◽  
Tatsuro Matsuoka ◽  
Hiroshi Asanuma
Keyword(s):  
Rayleigh Waves ◽  
Estimation Method ◽  
Direct Estimation ◽  
Phase Velocities ◽  
Circular Arrays ◽  
Extract Phase

Serum Copper and Iron on a Single Sample

1958 ◽  
Vol 4 (1) ◽  
pp. 43-48 ◽  
Author(s):  
B Zak ◽  
N Ressler
Keyword(s):  
Quantitative Determination ◽  
Serum Sample ◽  
Organic Material ◽  
Serum Copper ◽  
Inorganic Salts ◽  
Organic Extract ◽  
Phenanthroline Complex ◽  
Extract Phase ◽  
Determination Of Copper

Abstract A procedure has been described for the quantitative determination of copper and iron in one serum sample. The sera are wet ashed to destroy organic material, leaving inorganic salts available in the residue for the subsequent spectrophotometric determination of iron as the ferrous-1,10-phenanthroline complex in the aqueous phase, and copper as the cuprous-2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline in an organic extract phase.

scholarly journals DEMODULATION BY COMPLEX-VALUED WAVELETS FOR STOCHASTIC PATTERN RECOGNITION

2003 ◽  
Vol 01 (01) ◽  
pp. 1-17 ◽  
Author(s):  
JOHN DAUGMAN
Keyword(s):  
Pattern Recognition ◽  
Image Coding ◽  
Degrees Of Freedom ◽  
Statistical Independence ◽  
Wavelet Image ◽  
Decision Environments ◽  
Coarse Quantization ◽  
Complex Valued ◽  
Shared Structure ◽  
Extract Phase

Samples from stochastic signals having sufficient complexity need reveal only a little unexpected shared structure, in order to reject the hypothesis that they are independent. The mere failure of a test of statistical independence can thereby serve as a basis for recognizing stochastic patterns, provided they possess enough degrees-of-freedom, because all unrelated ones would pass such a test. This paper discusses exploitation of this statistical principle, combined with wavelet image coding methods to extract phase descriptions of incoherent patterns. Demodulation and coarse quantization of the phase information creates decision environments characterized by well-separated clusters, and this lends itself to rapid and reliable pattern recognition.

scholarly journals Separation of Coal Tar Distillate by Solvent Extraction —Separation of Extract Phase Using Distillation—

2006 ◽  
Vol 49 (6) ◽  
pp. 326-334 ◽  
Author(s):  
Chris Salim ◽  
Ryuichi Egashira
Keyword(s):  
Solvent Extraction ◽  
Coal Tar ◽  
Extraction Separation ◽  
Extract Phase

FT-IR Study Of Rare Earth Naphthenates In The Extract Phase

1985 ◽  
Author(s):  
Jinguang Wu ◽  
Hongcheng Gao ◽  
Tianzhu Jin ◽  
Dian Chen ◽  
Nai Shi ◽  
...  
Keyword(s):  
Rare Earth ◽  
Ft Ir ◽  
Ir Study ◽  
Extract Phase

scholarly journals Phasertng: directed acyclic graphs for crystallographic phasing

2021 ◽  
Vol 77 (1) ◽  
pp. 1-10
Author(s):  
Airlie J. McCoy ◽  
Duncan H. Stockwell ◽  
Massimo D. Sammito ◽  
Robert D. Oeffner ◽  
Kaushik S. Hatti ◽  
...  
Keyword(s):  
Directed Acyclic Graph ◽  
Directed Acyclic Graphs ◽  
Molecular Replacement ◽  
Molecular Fragments ◽  
Graph Data ◽  
Acyclic Graphs ◽  
Structure Solution ◽  
Experimental Phasing ◽  
Graph Management ◽  
Extract Phase

Crystallographic phasing strategies increasingly require the exploration and ranking of many hypotheses about the number, types and positions of atoms, molecules and/or molecular fragments in the unit cell, each with only a small chance of being correct. Accelerating this move has been improvements in phasing methods, which are now able to extract phase information from the placement of very small fragments of structure, from weak experimental phasing signal or from combinations of molecular replacement and experimental phasing information. Describing phasing in terms of a directed acyclic graph allows graph-management software to track and manage the path to structure solution. The crystallographic software supporting the graph data structure must be strictly modular so that nodes in the graph are efficiently generated by the encapsulated functionality. To this end, the development of new software, Phasertng, which uses directed acyclic graphs natively for input/output, has been initiated. In Phasertng, the codebase of Phaser has been rebuilt, with an emphasis on modularity, on scripting, on speed and on continuing algorithm development. As a first application of phasertng, its advantages are demonstrated in the context of phasertng.xtricorder, a tool to analyse and triage merged data in preparation for molecular replacement or experimental phasing. The description of the phasing strategy with directed acyclic graphs is a generalization that extends beyond the functionality of Phasertng, as it can incorporate results from bioinformatics and other crystallographic tools, and will facilitate multifaceted search strategies, dynamic ranking of alternative search pathways and the exploitation of machine learning to further improve phasing strategies.

Principle of a Parallel Vision System Adapted to Textures

1998 ◽  
Vol 12 (03) ◽  
pp. 355-378
Author(s):  
Anne M. Landraud-Lamole
Keyword(s):  
Filter Bank ◽  
Vision System ◽  
Artificial Vision ◽  
Filter Function ◽  
Visual Cells ◽  
Spatial Frequencies ◽  
Orientation Axis ◽  
Multichannel Filtering ◽  
Computational Simplicity ◽  
Extract Phase

A number of methods for classifying textures and for segmentation of textured images make use of multichannel filtering techniques because of their computational simplicity. On the other hand, biological experiments have shown the existence and the properties of visual channels and make it possible for us to select the "best" filter bank. In a performing artificial vision system, three important problems are to be solved: the rigorous sampling of the spatial frequencies, the scale related problem and parallel processing. This paper presents a mathematical solution to the logarithmic 1-D sampling of the spatial frequencies of a signal characterized by its energy spectrum. This solution obeys the signal theory. It is then extended to the 2-D sampling of the output energy image generated by what we call a "homothetic filter bank". While verifying the Shannon theorem, our system is compatible with the visual cells' sensitivities to frequencies and orientations. Scale problems are often encountered in computer vision, especially in methods using multichannel filtering. Our approach gives us a representation of an input textured image with a continuous multiresolution. With this representation, an interpretation of the information content of the image, invariant to scale and to orientation, is made possible. Any scale change in the image is represented by a simple translation along a logarithmic frequency-axis. In the same manner, a rotation corresponds to a translation along a linear orientation-axis. In our "homothetic visual-filter bank" (HFB) theory, it is shown that the frequency-filter function can be changed according to the application under consideration. In cases where texture discrimination is difficult, e.g. if two different textures have the same power spectrum, the solution may be to extract phase information using a classical complex Gabor function. But, we have shown that in order to design a parallel vision system, it is more pertinent to use the differences of Gaussian functions (DOG) which are real functions.

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