Roper St Francis Physician PartnersSweetgrass Endocrinology 2093 Henry Tecklenburg Dr STE 300E, Charleston, SC 29414 (843)4021575 (phone), (843)6067991 (fax)
Roper St Francis Physician PartnersSweetgrass Endocrinology 3510 N Hwy 17 STE 110, Mount Pleasant, SC 29466 (843)4021575 (phone), (843)6067991 (fax)
Education:
Medical School Ain Shams Univ, Fac of Med, Abbasia, Cairo, Egypt (330 04 Pr 1/71) Graduated: 1994
Procedures:
Electrocardiogram (EKG or ECG) Nutrition Therapy Vaccine Administration
Dr. Yacoub graduated from the Ain Shams Univ, Fac of Med, Abbasia, Cairo, Egypt (330 04 Pr 1/71) in 1994. He works in Mount Pleasant, SC and 1 other location and specializes in Endocrinology, Diabetes & Metabolism and Diabetes. Dr. Yacoub is affiliated with Bon Secours St Francis Hospital and Roper St Francis Mount Pleasant Hospital.
Isbn (Books And Publications)
Reuse Based Software Engineering : Techniques, Organizations, and Measurement
Amazon
Vp, Kindle
Amazon Nov 2008 - Nov 2011
Senior Manager, Media Technology
Amazon Nov 2008 - Nov 2011
Director, Kindle Content
Amazon Nov 2005 - Nov 2008
Senior Manager, Print on Demand
Hewlett-Packard 2003 - 2005
Expert, Research Scientist
Education:
West Virginia University 1997 - 1999
Cairo University 1989 - 1994
Us Army
Ssg
Hhb B
Ssg
201St Bfsb
Cryptologic Analyst
Education:
University of Washington 2013
Bachelors, Bachelor of Science
Skills:
Top Secret Weapons Defense Intelligence Army Operational Planning Physical Security Military Training Government Counterterrorism Command Force Protection Military Experience National Security Intelligence Analysis Military Security Clearance Military Operations Dod Combat Information Assurance
Sherif Yacoub - Mountain View CA, US Jean-Manuel Van Thong - Arlington MA, US John Burns - Barcelona, ES
Assignee:
Hewlett-Packard Development Company, L.P. - Houston TX
International Classification:
G06F 7/00 G06F 17/30
US Classification:
707736, 707758, 707899
Abstract:
An article is extracted from a document using a decision combiner to process a plurality of reading order alternatives. The text flow analysis generates the plurality of reading order alternatives of separate body text regions.
System And Method Using Multiple Automated Speech Recognition Engines
Hewlett-Packard Development Company, L.P. - Houston TX
International Classification:
G10L 15/04
US Classification:
704251, 704231, 704246, 704247, 704252
Abstract:
A system comprises a computer system comprising a central processing unit coupled to a memory and resource management application. A plurality of different automatic speech recognition (ASR) engines is coupled to the computer system. The computer system is adapted to select ASR engines to analyze a speech utterance based on resources available on the system.
Sherif M. Yacoub - Seattle WA, US Hanning Zhou - Seattle WA, US Jian Liang - Seattle WA, US
Assignee:
Amazon Technologies, Inc. - Reno NV
International Classification:
G06F 3/12
US Classification:
358 115, 358 11
Abstract:
A system and a method of customizing on-demand printed content are disclosed. In response to receiving a request from a consumer for on-demand printed content, content customization is determined. The determined customization is incorporated within the requested content and the on-demand printed content. Thereafter, and further responsive to the request, an on-demand printed copy of the requested content, including the incorporated customizations, is output for on-demand printing.
System And Method For Interactive Voice Response Enhanced Out-Calling
Sherif Yacoub - Mountain View CA, US Francois Vincent - Corenc, FR
Assignee:
Hewlett-Packard Development Company, L.P. - Houston TX
International Classification:
H04M 3/00
US Classification:
37926607, 379 8801, 379 8813, 379 8817, 379 8818
Abstract:
A system and method for managing telephone calls is disclosed. The method discloses: calling a contact; presenting the contact with a predetermined out-calling dialog; translating the contact's vocal responses to the dialog into textual words using selected interactive voice response algorithms; connecting the contact to a human operator after a predetermined portion of the out-calling dialog with the contact is completed; and providing the operator with the textual words. In one embodiment, the system discloses all means for implementing the method. In another embodiment, the system discloses: a contact database for storing information on the contact; a dialog database containing a predetermined out-calling dialog; a call manager for calling the contact and presenting the contact with the dialog; and an interactive voice response module for translating the contact's vocal responses to the dialog into textual words and storing the words in the contact database which are accessible to the operator.
Processing A Digital Image Of Content Using Content Aware Despeckling
Systems and methods for removing artifacts from a page of digital image are presented. More particularly, a digital image is obtained, the digital image having at least one page of content to be processed. A content bounding box is determined for the content of the page. Additionally, a set of segments is generating, the set corresponding to particular areas of the content within the content bounding box, each area associated with a type of content. For each segment of the set of segments, the following are performed. Despeckling criteria are selected for identifying artifacts according to the type associated with the segment. Artifacts are identified in the segment according to the despeckling criteria. The identified artifacts are then removed from the page. Thereafter, the updated digital image is stored in a content store.
Allocation Of Speech Recognition Tasks And Combination Of Results Thereof
Paul M. Burke - Bedford NH, US Sherif Yacoub - Mountain View CA, US
Assignee:
Hewlett-Packard Development Company, L.P. - Houston TX
International Classification:
G10L 15/00
US Classification:
704231, 704244
Abstract:
A system, method, computer-readable medium, and computer-implemented system for optimizing allocation of speech recognition tasks among multiple speech recognizers and combining recognizer results is described. An allocation determination is performed to allocate speech recognition among multiple speech recognizers using at least one of an accuracy-based allocation mechanism, a complexity-based allocation mechanism, and an availability-based allocation mechanism. The speech recognition is allocated among the speech recognizers based on the determined allocation. Recognizer results received from multiple speech recognizers in accordance with the speech recognition task allocation are combined.
A speech recognition system comprises exactly two automated speech recognition (ASR) engines connected to receive the same inputs. Each engine produces a recognition output, a hypothesis. The system implements one of two (or both) methods for combining the output of the two engines. In one method, a confusion matrix statistically generated for each speech recognition engine is converted into an alternatives matrix in which every column is ordered by highest-to-lowest probability. A program loop is set up in which the recognition outputs of the speech recognition engines are cross-compared with the alternatives matrices. If the output from the first ASR engine matches an alternative, its output is adopted as the final output. If the vectors provided by the alternatives matrices are exhausted without finding a match, the output from the first speech recognition engine is adopted as the final output. In a second method, the confusion matrix for each ASR engine is converted into Bayesian probability matrix.
System And Method For Providing Assistance In Speech Recognition Applications
A system and method for finding a message within a speech recognition application. An assistance manager is activated for forming a selection path and finding a message associated with the selection path.