Automated extraction of classes from legacy systems

2003 ◽  
pp. 170-184 ◽  
Author(s):  
Andrey A. Terekhov
Keyword(s):  
Legacy Systems ◽  
Automated Extraction

High throughput semi-automated extraction method for the creation of a collection from microbial fermentations of fungi and Actinomycetes

Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
JR Tormo ◽  
N Tabanera ◽  
D Conway ◽  
P Ramos ◽  
A Redondo ◽  
...  
Keyword(s):  
High Throughput ◽  
Extraction Method ◽  
Automated Extraction ◽  
The Creation

A Distributed-Ledger, Edge-Computing Architecture for Automation and Computer Integration in Semiconductor Manufacturing

2020 ◽  
pp. 13-29
Author(s):  
Da-Yin Liao
Keyword(s):  
Semiconductor Manufacturing ◽  
Manufacturing Systems ◽  
Edge Computing ◽  
Legacy Systems ◽  
Software Framework ◽  
Computer Integration ◽  
Computing Architecture ◽  
Disruptive Technologies ◽  
Distributed Ledger ◽  
Operational Structure

Contemporary 300mm semiconductor manufacturing systems have highly automated and digitalized cyber-physical integration. They suffer from the profound problems of integrating large, centralized legacy systems with small islands of automation. With the recent advances in disruptive technologies, semiconductor manufacturing has faced dramatic pressures to reengineer its automation and computer integrated systems. This paper proposes a Distributed-Ledger, Edge-Computing Architecture (DLECA) for automation and computer integration in semiconductor manufacturing. Based on distributed ledger and edge computing technologies, DLECA establishes a decentralized software framework where manufacturing data are stored in distributed ledgers and processed locally by executing smart contracts at the edge nodes. We adopt an important topic of automation and computer integration for semiconductor research &development (R&D) operations as the study vehicle to illustrate the operational structure and functionality, applications, and feasibility of the proposed DLECA software framework.

Workflow-based method for customizing J2EE legacy systems

2009 ◽  
Vol 29 (7) ◽  
pp. 1760-1763 ◽  
Author(s):  
Fan ZHANG ◽  
Feng YUAN ◽  
Yong-ji WANG
Keyword(s):  
Legacy Systems

Incremental Modernization of Legacy Systems

2001 ◽  
Author(s):  
Santiago Comella-Dorda ◽  
Grace A. Lewis ◽  
Pat Place ◽  
Dan Plakosh ◽  
Robert C. Seacord
Keyword(s):  
Legacy Systems

Automated extraction of domain knowledge in practice

2020 ◽  
Author(s):  
Yang Li ◽  
Sandro Schulze ◽  
Helene Hvidegaard Scherrebeck ◽  
Thomas Sorensen Fogdal
Keyword(s):  
Domain Knowledge ◽  
Automated Extraction ◽  
Knowledge In Practice

scholarly journals Shared Molecular Mechanisms of Hypertrophic Cardiomyopathy and Its Clinical Presentations: Automated Molecular Mechanisms Extraction Approach

Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 785
Author(s):  
Mila Glavaški ◽  
Lazar Velicki
Keyword(s):  
Cardiovascular Disease ◽  
Hypertrophic Cardiomyopathy ◽  
Open Access ◽  
Molecular Mechanisms ◽  
Scientific Literature ◽  
Automated Extraction ◽  
Clinical Presentations ◽  
Machine Reading ◽  
Pathway Databases

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease with a prevalence of 1 in 500 people and varying clinical presentations. Although there is much research on HCM, underlying molecular mechanisms are poorly understood, and research on the molecular mechanisms of its specific clinical presentations is scarce. Our aim was to explore the molecular mechanisms shared by HCM and its clinical presentations through the automated extraction of molecular mechanisms. Molecular mechanisms were congregated by a query of the INDRA database, which aggregates knowledge from pathway databases and combines it with molecular mechanisms extracted from abstracts and open-access full articles by multiple machine-reading systems. The molecular mechanisms were extracted from 230,072 articles on HCM and 19 HCM clinical presentations, and their intersections were found. Shared molecular mechanisms of HCM and its clinical presentations were represented as networks; the most important elements in the intersections’ networks were found, centrality scores for each element of each network calculated, networks with reduced level of noise generated, and cooperatively working elements detected in each intersection network. The identified shared molecular mechanisms represent possible mechanisms underlying different HCM clinical presentations. Applied methodology produced results consistent with the information in the scientific literature.

Sign in / Sign up

Export Citation Format

Share Document