Michael H Boyle

US Patent:

6647983, Nov 18, 2003

Filed:

Mar 6, 2001

Appl. No.:

09/681248

Inventors:

Dexter G. Smith - Columbia MD
Michael P. Boyle - Severna Park MD
Protagoras N. Cutchis - Highland MD
William R. Allmon - Catonsville PA

Assignee:

The Johns Hopkins University - Baltimore MD

International Classification:

A62B 902

US Classification:

12820524, 12820511

Abstract:

A low-pressure valve enabling precise control of a fluid flow rate through the valve during cyclical operation of the valve. The valve is useful for controlling air delivery to a patient as part of a portable ventilator. The valve comprises a housing having an inlet and two outlets and. A wiper plate and an orifice plate are disposed inside of the housing. Transverse movement of the wiper plate relative to the orifice plate , powered for example by a servomotor , simultaneously and alternatively covers and uncovers various openings in the orifice plate. The total flow through the valve is thereby divided between the two outlets and.

US Patent:

20160149943, May 26, 2016

Filed:

Nov 16, 2015

Appl. No.:

14/941999

Inventors:

- Falls Church VA, US
Michael P. Boyle - Ellicott City MD, US
Christopher C. Valentino - Stevensville MD, US

International Classification:

H04L 29/06
G06N 99/00
G06N 7/00

Abstract:

Described herein are embodiments of a system and method for network data characterization and/or classification that overcome the defects of the prior art. These and other advantages are achieved by a method for network data characterization. The method includes receiving network events, wherein at least some of the events include content, converting the received content into data messages, in which at least some of the data messages include the content and metadata describing an event and the content, routing the data messages to a plurality of analyzers based on specified message criteria to which each analyzer subscribes, each of one or more analyzers that received the routed data messages analyzing the content within the data messages in order to characterize the content, in which the one or more analyzers include at least one machine-learning analyzer that classifies the content with a confidence percentage that indicates the probability that the content is malign or the confidence that a prediction that the content is malign is correct, outputting the characterization results of the one or more analyzers, and comparing the output characterization results against a plurality of criteria to determine subsequent action to take based on the characterization results.