Scalable, Global, Optimal-bandwidth, Application-Specific Routing

2016 ◽  
Author(s):  
Ahmed H. Abdel-Gawad ◽  
Mithuna Thottethodi
Keyword(s):  
Optimal Bandwidth ◽  
Global Optimal ◽  
Application Specific

Cluster Generation and Network Component Insertion for Topology Synthesis of Application-Specific Network-on-Chips

2012 ◽  
Vol E95-C (4) ◽  
pp. 534-545 ◽  
Author(s):  
Wei ZHONG ◽  
Takeshi YOSHIMURA ◽  
Bei YU ◽  
Song CHEN ◽  
Sheqin DONG ◽  
...  
Keyword(s):  
Cluster Generation ◽  
Application Specific ◽  
Network Component

Automatic Registering and Stitching of TEM/STEM Image Mosaics

2013 ◽  
Author(s):  
Chung-Ching Lin ◽  
Franco Stellari ◽  
Lynne Gignac ◽  
Peilin Song ◽  
John Bruley
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Vlsi Circuit ◽  
Significant Progress ◽  
Research Areas ◽  
Automated Method ◽  
Transmission Electron ◽  
Stem Image ◽  
High Resolution Images ◽  
Global Optimal

Abstract Transmission Electron Microscopy (TEM) and scanning TEM (STEM) is widely used to acquire ultra high resolution images in different research areas. For some applications, a single TEM/STEM image does not provide enough information for analysis. One example in VLSI circuit failure analysis is the tracking of long interconnection. The capability of creating a large map of high resolution images may enable significant progress in some tasks. However, stitching TEM/STEM images in semiconductor applications is difficult and existing tools are unable to provide usable stitching results for analysis. In this paper, a novel fully automated method for stitching TEM/STEM image mosaics is proposed. The proposed method allows one to reach a global optimal configuration of each image tile so that both missing and false-positive correspondences can be tolerated. The experiment results presented in this paper show that the proposed method is robust and performs well in very challenging situations.

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

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