Benjamin Edward Lowe

US Patent:

20140026076, Jan 23, 2014

Filed:

Jul 17, 2012

Appl. No.:

13/550917

Inventors:

Jacquilene Jacob - Yonkers NY, US
Hock M. Ng - Westfield NJ, US
Benjamin M. Lowe - Short Hills NJ, US

International Classification:

G06F 3/033
G06F 3/048

US Classification:

715757, 345158

Abstract:

A system and method for real-time interactive collaboration between remote users communicating via one or more input devices adapted to provide alter documents, imagery and the like projected within a multidimensional virtual interactive space.

US Patent:

20160019564, Jan 21, 2016

Filed:

Jul 21, 2014

Appl. No.:

14/337057

Inventors:

- Basking Ridge NJ, US
Carol BECHT - Boonton NJ, US
Gopinath VENKATASUBRAMANIAM - Bridgewater NJ, US
Christopher M. SCHMIDT - Branchburg NJ, US
Benjamin LOWE - Short Hills NJ, US

International Classification:

G06Q 30/02
G06Q 10/06

Abstract:

Systems and methods for forecasting device return rates are described. Some implementations include initializing a model representing a device's readiness for market based on one or more key performance indicators (KPIs) of the device, the model being represented by a curve, computing differences between measured value of KPIs of the device and values of KPIs fitted to the curve, identifying an inflection point of the curve based on the computed differences, interpreting the shape of the curve based on the identified inflection point, a readiness index and the curvature of the curve and determining a state of readiness of the device based on the interpreted shape of the curve.

US Patent:

20150287059, Oct 8, 2015

Filed:

Apr 8, 2014

Appl. No.:

14/248191

Inventors:

- Basking Ridge NJ, US
Carol BECHT - Boonton NJ, US
Gopinath VENKATASUBRAMANIAM - Bridgewater NJ, US
Benjamin LOWE - Short Hills NJ, US
Christopher M. SCHMIDT - Branchburg NJ, US

Assignee:

CELLCO PARTNERSHIP D/B/A VERIZON WIRELESS - Basking Ridge NJ

International Classification:

G06Q 30/02
G06Q 10/06

Abstract:

Systems and methods for forecasting device return rates are disclosed. Some implementations include identifying correlations between device return cause codes and corresponding device return rates for one or more devices, computing, based on the identified correlations, correlation indexes for each of the device return cause codes, ranking the computed correlation indexes associated with each of the device return cause codes, selecting, a subset of device return cause codes, determining a relationship between the selected subset of the return cause codes and corresponding device return rates, mapping one or more measured key performance indicators (KPIs) of a particular device to return cause codes of the device, and estimating a device return rate for the particular device based on the mapped KPIs and the determined relationship.