Athar Mohammad Syed, Age 592105 Laburnum Ave, Charlotte, NC 28205

Athar Syed Phones & Addresses

2105 Laburnum Ave, Charlotte, NC 28205

1616 Wilmore Dr, Charlotte, NC 28203

1027 Linda Ln, Charlotte, NC 28211

1608 N Davidson St, Charlotte, NC 28206

4107 Walker Rd, Charlotte, NC 28211

Woodfin, NC

Fairview, NC

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Mentions for Athar Mohammad Syed

Career records & work history

Medicine Doctors

Athar Syed Photo 1

Athar Hamid Syed

Specialties:
Neurology
Education:
Grant Medical College (1969)

Athar Syed resumes & CV records

Resumes

Athar Syed Photo 34

Technician Manager

Location:
Charlotte, NC
Industry:
Banking
Work:
Bank of America
Technician Manager
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Athar Syed

Athar Syed Photo 36

Athar Syed

Athar Syed Photo 37

Athar Syed

Publications & IP owners

Us Patents

Decentralized Workflow Management System

US Patent:
2014023, Aug 21, 2014
Filed:
Feb 20, 2013
Appl. No.:
13/771620
Inventors:
- Charlotte NC, US
ATHAR SYED - Charlotte NC, US
SHYAAM SUNDAR NEELAM - Marietta GA, US
ZHU YIFEI - Alpharetta GA, US
DEBORAH A. COPES - Wethersfield CT, US
Assignee:
BANK OF AMERICA CORPORATION - Charlotte NC
International Classification:
G06Q 10/06
US Classification:
717102
Abstract:
Systems, methods and computer program products are disclosed that provide a decentralized workflow management system based on an enterprise componentized workflow application (ECWA). In some embodiments, the system includes self-contained components configured for process management, each component including a processor, a memory, and a set of instructions stored in the memory. The loosely-coupled components, with encapsulation, are plug-in configurable, JMX controlled, and throttle and safety enabled. Each component receives a responsibility injection and a capability injection, defining roles and abilities for the components, in order to accomplish business processes. The components define independently-deployed system nodes connected via communication conduits. The ECWA components provide an environment for decentralized workflow management that extends the BPMN model. The system unifies flow-oriented modeling and context-oriented architecture. As a result, the ECWA is appropriate for complex environments, such as artificial intelligence, due to its flexibility, high processing efficiency, and unifying development cycles.

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