Hybrid Techniques For Postal Address Location

1988 ◽  
Author(s):  
Keith Mersereau ◽  
Mark Kuhner ◽  
Daniel Grieser
2021 ◽  
pp. 096228022098354
Author(s):  
N Satyanarayana Murthy ◽  
B Arunadevi

Diabetic retinopathy (DR) stays as an eye issue that has continuously developed in individuals who experienced diabetes. The complexities in diabetes cause harm to the vein at the back of the retina. In outrageous cases, DR could swift apparition disaster or visual impairment. This genuine impact had the option to charge through convenient treatment and early recognition. As of late, this issue has been spreading quickly, particularly in the working region, which in the end constrained the interest of an analysis of this disease from the most prompt stage. Therefore, that are castoff to protect the progressions of this disorder, revealing of the retinal blood vessels (RBVs) play a foremost role. The growth of an abnormal vessel leads to the development steps of DR, where it can be well known by extracting the RBV. The recognition of the BV for DR by developing an automatic approach is a major aim of our research study. In the proposed method, there are two major steps: one is segmentation and the second one is classification of affected retinal BV. The proposed method uses the Kinetic Gas Molecule Optimization based on centroid initialization used for the Fuzzy C-means Clustering. In the classification step, those segmented images are given as input to hybrid techniques such as a convolution neural network with bidirectional-long short-term memory (CNN with Bi-LSTM). The learning degree of Bi-LSTM is revised by using the self-attention mechanism for refining the classification accuracy. The trial consequences disclosed that the mixture algorithm achieved higher accuracy, specificity, and sensitivity than existing techniques.


2013 ◽  
Vol 2013 (1) ◽  
pp. 211 ◽  
Author(s):  
Yonghong Yao ◽  
Mihai Postolache ◽  
Yeong-Cheng Liou

2010 ◽  
Vol 88 (8) ◽  
pp. 815-830 ◽  
Author(s):  
Lesley R. Rutledge ◽  
Stacey D. Wetmore

The present work uses 129 nucleobase – amino acid CCSD(T)/CBS stacking and T-shaped interaction energies as reference data to test the ability of various density functionals with double-zeta quality basis sets, as well as some semi-empirical and molecular mechanics methods, to accurately describe noncovalent DNA–protein π–π and π+–π interactions. The goal of this work is to identify methods that can be used in hybrid approaches (QM/MM, ONIOM) for large-scale modeling of enzymatic systems involving active-site (substrate) π–π contacts. Our results indicate that AMBER is a more appropriate choice for the lower-level method in hybrid techniques than popular semi-empirical methods (AM1, PM3), and suggest that AMBER accurately describes the π–π interactions found throughout DNA–protein complexes. The M06–2X and PBE-D density functionals were found to provide very promising descriptions of the 129 nucleobase – amino acid interaction energies, which suggests that these may be the most suitable methods for describing high-level regions. Therefore, M06–2X and PBE-D with both the 6–31G(d) and 6–31+G(d,p) basis sets were further examined through potential-energy surface scans to better understand how these techniques describe DNA–protein π–π interactions in both minimum and nonminimum regions of the potential-energy surfaces, which is critical information when modeling enzymatic reaction pathways. Our results suggest that studies of stacked nucleobase – amino acid systems should implement the PBE-D/6–31+G(d,p) method. However, if T-shaped contacts are involved and (or) smaller basis sets must be considered due to limitations in computational resources, then M06–2X/6–31G(d) provides an overall excellent description of both nucleobase – amino acid stacking and T-shaped interactions for a range of DNA–protein π–π and π+–π interactions.


Sign in / Sign up

Export Citation Format

Share Document