Dr. Tran graduated from the Pennsylvania State University College of Medicine in 2010. He works in Olney, MD and specializes in Pediatrics and Adolescent Medicine. Dr. Tran is affiliated with Medstar Montgomery Medical Center.
2011 to 2012 Computer Technician/Network AdministratorMid City Solar
2009 to 2011 Network Systems AdministratorCollege of the Sequoias Computer Electronics Technology Club
2007 to 2009
Education:
California State University 2009 to 2011 Bachelors of Science in Industrial Technology Network Systems AdministrationCollege of the Sequoias 2007 to 2009 Associates of ScienceDe Anza Community College Cupertino, CA 2003 to 2007 CertificateCollege of the Sequoias General Ed
Kyle J. Charlet - Morgan Hill CA, US Nathan D. Church - San Jose CA, US Kevin D. Hite - San Jose CA, US Christopher M. Holtz - San Jose CA, US Richard V. Tran - San Jose CA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 17/30
US Classification:
707722, 707E17014
Abstract:
Provided are techniques for processing structured content within Large Object (LOB) data that is stored in a column of a database table. Structural metadata describing structures that each define a different format of the structured content is stored. A request for data in the database table is received. The structural metadata is used to create an empty result set with columns defined by at least two of the structures. For each row of data in the database table that includes LOB data, control data is used to identify one of the structures to be applied to the structured content within the LOB data stored in that row of data, and the structured content within the LOB data in that row of data is mapped to the columns in the result set based on the identified one of the structures. The result set is returned.
Kyle J. Charlet - Morgan Hill CA, US Nathan D. Church - San Jose CA, US Kevin D. Hite - San Jose CA, US Christopher M. Holtz - San Jose CA, US Richard V. Tran - San Jose CA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 17/30
US Classification:
707722, 707E17014
Abstract:
Provided are techniques for processing structured content within Large Object (LOB) data that is stored in a column of a database table. Structural metadata describing structures that each define a different format of the structured content is stored. A request for data in the database table is received. The structural metadata is used to create an empty result set with columns defined by at least two of the structures. For each row of data in the database table that includes LOB data, control data is used to identify one of the structures to be applied to the structured content within the LOB data stored in that row of data, and the structured content within the LOB data in that row of data is mapped to the columns in the result set based on the identified one of the structures. The result set is returned.
Examples of techniques for rating and notifying volunteer responders are disclosed. Aspects include receiving a notification of a medical emergency at a first location and obtaining a plurality of candidate volunteer responders from a volunteer responder database. Aspects also include ranking the plurality of candidate volunteer responders based on a location of each of the plurality of candidate volunteer responders, a type of the medical emergency, and a characteristic of each of the plurality of candidate volunteer responders. Aspects further include notifying a highest ranked candidate volunteer from the plurality of candidate volunteer responders of the medical emergency, wherein the notification includes the type of the medical emergency and the first location.
Binary Large Object Platform For Interactively Analyzing And Editing Structural Metadata
- Armonk NY, US Nathan D. Church - San Jose CA, US Kevin D. Hite - Morgan Hill CA, US Richard V. Tran - San Jose CA, US
International Classification:
G06F 17/30 G06F 9/54 G06F 11/07
Abstract:
Embodiments include methods, systems and computer program products method for editing and correcting structural metadata associated a binary large object (BLOB). The computer-implemented method includes obtaining, using a processor, at least a portion of structural metadata associated with the BLOB. The processor converts one or more fields associated with the at least a portion of structural metadata and determines that the one or more fields generated one or more errors or null values. The processor provides an interface, wherein the interface is used to cause a first movement or edit the one or more fields. The processor determines that the first movement or edit of the one or more fields fixes the one or more errors or null values and provides an indication that the first movement or edit of the one or more fields has or has not fixed the one or more errors or null values.
Generating Instructional Variants Based On Natural Language Processing Of Comments Feed
A method, computer system, and a computer program product for generating an instructional variant is provided. The present invention may include identifying an instructional guide. The present invention may also include analyzing a user comments feed associated with the identified instructional guide. The present invention may further include, in response to determining that the analyzed user comments feed includes a modification to the identified instructional guide, generating a variant instructional guide including the modification to the identified instructional guide.
Dynamically Adding Custom Data Definition Language Syntax To A Database Management System
- ARMONK NY, US Kevin D. Hite - San Jose CA, US Richard V. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
A computer-implemented method includes receiving, via original Data Definition Language (DDL) syntax of a Database Management System (DBMS), a definition of custom DDL syntax. Metadata describing the custom DDL syntax is stored in a global catalog of the DBMS. A first DDL statement that utilizes the custom DDL syntax is received. The metadata describing the custom DDL syntax is read from the global catalog. The first DDL statement is processed, using a computer processor, according to the metadata.
- Armonk NY, US Kevin D. Hite - San Jose CA, US Richard V. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
Provided are techniques for interpreting invalid data that is a portion of a data set as valid data. A request is received to convert data from a first format to a second format for an application, wherein the data is a portion of a data set. It is determined that the data is invalid, wherein the invalid data cannot be processed by the application in the first format. It is determined whether the invalid data is to be interpreted as valid based on a flag. In response to determining that the invalid data is to be interpreted as valid, setting the invalid data to a new value in the second format that can be processed by the application.
- Armonk NY, US Kevin D. Hite - San Jose CA, US Richard V. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
Provided are techniques for interpreting invalid data that is a portion of a data set as valid data. A request is received to convert data from a first format to a second format for an application, wherein the data is a portion of a data set. It is determined that the data is invalid, wherein the invalid data cannot be processed by the application in the first format. It is determined whether the invalid data is to be interpreted as valid based on a flag. In response to determining that the invalid data is to be interpreted as valid, setting the invalid data to a new value in the second format that can be processed by the application.