Trends and Advancements in Genome Data Compression and Processing Algorithms

2021 ◽  
pp. 163-170
Author(s):  
Sanjeev Kumar
Keyword(s):  
Data Compression ◽  
Genome Data ◽  
Processing Algorithms

scholarly journals The impact of irreversible image data compression on post-processing algorithms in computed tomography

2020 ◽  
Vol 26 (1) ◽  
pp. 22-27
Author(s):  
Daniel Pinto dos Santos ◽  
◽  
Conrad Friese ◽  
Jan Borggrefe ◽  
Peter Mildenberger ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Data Compression ◽  
Image Data ◽  
Post Processing ◽  
Processing Algorithms ◽  
Image Data Compression ◽  
The Impact

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

Analysis of field uniformity and quantitative evaluation of subsurface pitting corrosion in conductors via GPEC

2020 ◽  
Vol 64 (1-4) ◽  
pp. 19-29
Author(s):  
Shuting Ren ◽  
Yong Li ◽  
Bei Yan ◽  
Jinhua Hu ◽  
Ilham Mukriz Zainal Abidin ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Eddy Current ◽  
Pitting Corrosion ◽  
Gradient Field ◽  
Uniform Field ◽  
Eddy Current Method ◽  
Optimal Position ◽  
Pulsed Eddy Current ◽  
Field Uniformity ◽  
Processing Algorithms

Structures of nonmagnetic materials are broadly used in engineering fields such as aerospace, energy, etc. Due to corrosive and hostile environments, they are vulnerable to the Subsurface Pitting Corrosion (SPC) leading to structural failure. Therefore, it is imperative to conduct periodical inspection and comprehensive evaluation of SPC using reliable nondestructive evaluation techniques. Extended from the conventional Pulsed eddy current method (PEC), Gradient-field Pulsed Eddy Current technique (GPEC) has been proposed and found to be advantageous over PEC in terms of enhanced inspection sensitivity and accuracy in evaluation and imaging of subsurface defects in nonmagnetic conductors. In this paper two GPEC probes for uniform field excitation are intensively analyzed and compared. Their capabilities in SPC evaluation and imaging are explored through simulations and experiments. The optimal position for deployment of the magnetic field sensor is determined by scrutinizing the field uniformity and inspection sensitivity to SPC based on finite element simulations. After the optimal probe structure is chosen, quantitative evaluation and imaging of SPC are investigated. Signal/image processing algorithms for SPC evaluation are proposed. Through simulations and experiments, it has been found that the T-shaped probe together with the proposed processing algorithms is advantageous and preferable for profile recognition and depth evaluation of SPC.

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