Michael P O'Connell

US Patent:

6849422, Feb 1, 2005

Filed:

May 31, 2000

Appl. No.:

09/583891

Inventors:

Timothy M. Wiles - Reisterstown MD, US
David J. Turner - Owings Mills MD, US
Michael A. O'Connell - Durham NC, US
Giovanni Parmigiani - Baltimore MD, US
Merlise Clyde - Durham NC, US

Assignee:

Becton, Dickinson and Company - Franklin Lakes NJ

International Classification:

C12Q 102

US Classification:

435 29

Abstract:

A system and method for analyzing samples, such as biological samples, to accurately and effectively determine the susceptibility of the samples to antimicrobial materials, so as to determine minimum inhibitory concentration (MIC) values for the respective samples and antimicrobial materials. At each of a plurality of time intervals, the system and method directs a plurality of different analyzing light wavelengths, such as red, green and blue wavelengths, onto each of a plurality of sample wells, and detects a respective resultant light wavelength emanating from the respective sample wells for each of the analyzing light wavelengths. The system and method uses resultant light wavelengths to generate at least two growth indicator characteristic curves representing, for example, the redox state and turbidity characteristics of the sample wells. The system then uses the redox state and turbidity characteristics of sample wells containing the same antimicrobial material to determine the MIC value for that material in relation to the sample contained in those wells.

US Patent:

D541189, Apr 24, 2007

Filed:

Jun 20, 2006

Appl. No.:

29/261720

Inventors:

Michael Shane O'Connell - Palmyra NY, US

International Classification:

1105

US Classification:

D11125

US Patent:

20040063168, Apr 1, 2004

Filed:

Oct 27, 2003

Appl. No.:

10/694122

Inventors:

Timothy Wiles - Reisterstown MD, US
David Turner - Owings Mills MD, US
Michael O'Connell - Durham NC, US
Giovanni Parmigiani - Baltimore MD, US
Merlise Clyde - Durham NC, US

International Classification:

C12Q001/02

US Classification:

435/029000

Abstract:

A system and method for analyzing samples, such as biological samples, to accurately and effectively determine the susceptibility of the samples to antimicrobial materials, so as to determine minimum inhibitory concentration (MIC) values for the respective samples and antimicrobial materials. At each of a plurality of time intervals, the system and method directs a plurality of different analyzing light wavelengths, such as red, green and blue wavelengths, onto each of a plurality of sample wells, and detects a respective resultant light wavelength emanating from the respective sample wells for each of the analyzing light wavelengths. The system and method uses resultant light wavelengths to generate at least two growth indicator characteristic curves representing, for example, the redox state and turbidity characteristics of the sample wells. The system then uses the redox state and turbidity characteristics of sample wells containing the same antimicrobial material to determine the MIC value for that material in relation to the sample contained in those wells.

US Patent:

20220383163, Dec 1, 2022

Filed:

Aug 10, 2022

Appl. No.:

17/885170

Inventors:

- Palo Alto CA, US
Michael O'CONNELL - Durham NC, US
Daniel J ROPE - Reston VA, US

Assignee:

TIBCO Software Inc. - Palo Alto CA

International Classification:

G06N 5/04
G06F 16/2458
G06F 16/26
G06F 16/28
G06N 20/00
G06F 16/9035

Abstract:

A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.

US Patent:

20210103832, Apr 8, 2021

Filed:

Jan 23, 2020

Appl. No.:

16/751051

Inventors:

- Palo Alto CA, US
Michael O'CONNELL - Durham NC, US
Daniel J. ROPE - Reston VA, US

International Classification:

G06N 5/04
G06F 16/2458
G06F 16/9035
G06F 16/28
G06N 20/00
G06F 16/26

Abstract:

A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.

US Patent:

20210019324, Jan 21, 2021

Filed:

Mar 11, 2019

Appl. No.:

16/501120

Inventors:

- Palo Alto CA, US
Michael O'Connell - Durham NC, US

International Classification:

G06F 16/25
G06F 16/2455

Abstract:

A system, method, and computer-readable medium for extracting the samples from big data to extract most information about the relationships of interest between dimensions and variables in the data repository. More specifically, extracting information from lame data repositories follows an adaptive process that uses systematic sampling procedures derived from optimal experimental designs to target from a large data set specific observations with information value of interest for the analytic task under consideration. The application of adaptive optimal design to guide exploration of large data repositories provides advantages over known big data technologies.

US Patent:

20200387814, Dec 10, 2020

Filed:

Jun 8, 2020

Appl. No.:

16/895337

Inventors:

- Palo Alto CA, US
Thomas HILL - Tulsa OK, US
Daniel ROPE - Reston VA, US
Michael O'CONNELL - Durham NC, US
Gaia PAOLINI - Canterbury, GB
Eric HSU - Hoboken NJ, US

International Classification:

G06N 5/04
G06N 20/00

Abstract:

A system for generating algorithmic models comprising a function module to generate a desirability function, an automated machine learning module, and a UI module. The desirability function defines a single desirability value based on an algorithmic model accuracy criteria, criteria for algorithmic model quality, criteria for model fidelity, and criteria for the benefits and cost of model deployment. Specific hard and soft constraints regarding these and other user-defined criteria can also be specified by the user. The automated machine learning module generates an algorithmic model by training the algorithmic model against a model data set, identifying the model with the greatest desirability with respect to all criteria as combined via the desirability function. The UI module generates a user interface to display the overall desirability as well as all model criteria configured by the user. The displayed criteria and desirability are selectable and definable.

US Patent:

20190283932, Sep 19, 2019

Filed:

Jun 5, 2019

Appl. No.:

16/432241

Inventors:

- Armonk NY, US
WILLIAM J. GREEN - Cary NC, US
MICHAEL D. O'CONNELL - ROCHESTER MN, US
SHARON T. SPAULDING - Highland NY, US

International Classification:

B65D 19/38
B66F 9/12

Abstract:

A pallet gap filler for a pallet and a lift is provided. The pallet gap filler includes filling and engaging elements. The filling element is insertible into a portion of a space defined between tines of the lift and one or more of top and bottom decks and blocks and/or stringers separating the top and bottom decks of the pallet. The filling element is configured to assume a first configuration during filling element insertion and a second configuration in which, following filling element insertion, the filling element fixes relative orientations of the pallet and the lift. The engaging element is actuatable with the filling element initially assuming the first configuration to cause the filling element to assume the second configuration.