Stochastic Networks
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Kristen M. Biggar, N-BioS', 'PO_EMAI': None, 'PO_PHON': None}
Stochastic network theory has progressed along "micro" lines, with the          emphasis on detailed, structured models whose analysis has become               almost hopelessly complex.  An alternative, which the principal                 investigator will follow involves the study of aggregated systems which         can be modeled as control systems using the concept of Brownian motion.         The applications of such stochastic models extend to material and data          flow problems, common in transportation and computer technology.
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{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '1263', 'Text': 'PROBABILITY'}, {'Code': '1454', 'Text': 'SYSTEMS THEORY'}]
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