Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: A non-spray-dried, dry-granulated ceramic particulate mixture including at least 40 wt % coal combustion fly ash and from 4 wt % to 9 wt % water. At least 90 wt % of the particles have a particle size of from 80 ?m to 600 ?m.

Abstract: A non-spray-drying, dry-granulation process for making a ceramic particulate mixture including from 4 wt % to 9 wt % water. At least 90 wt % of the particles have a particle size of from 80 ?m to 600 ?m. The process includes the steps of: (a) forming a precursor material; (b) subjecting the precursor material to a compaction step to form a compacted precursor material; (c) subjecting the compacted precursor material to a crushing step to form a crushed precursor material; and (d) subjecting the crushed precursor material to at least two air classification steps. One air classification step removes at least a portion of the particles having a particle size of greater than 600 ?m from the crushed precursor material, and the other air classification step removes at least a portion of the particles having a particle size of less than 80 ?m from the crushed precursor material.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: This application discloses a computing system implementing tools and mechanisms that can incorporate a security co-processor into a circuit design modeling an electronic device. The tools and mechanisms can configure the security co-processor to monitor at least a portion of the electronic device. The tools and mechanisms can generate at least one security action for the security co-processor to initiate when the security co-processor monitors the electronic device failing to conform to rules in a rules database.

Abstract: The application discloses a computing system to analyze a program to generate a control flow graph representing paths capable of being traversed through the program during execution. The computing system can translate the control flow graph into a constraint graph representation of the program. The computing system can utilize a constraint solver on the constraint graph to identify a set of test values associated with a coverage definition. The set of test values can prompt the program, during execution, to be exercised based on the coverage definition provided to the test program generation tool 300. The computing system can generate a test program configured to provide the set of input variable values to the program.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: This application discloses a computing system implementing tools and mechanisms that can incorporate a security co-processor into a circuit design modeling an electronic device. The tools and mechanisms can configure the security co-processor to monitor at least a portion of the electronic device. The tools and mechanisms can generate at least one security action for the security co-processor to initiate when the security co-processor monitors the electronic device failing to conform to rules in a rules database.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Methods and systems generate content-categorization hierarchies and assign each content object to a set of nodes in the hierarchies. Each hierarchy includes a series of levels, each level including nodes which represent a categorization. A node in a top level is connected with multiple nodes in a lower level via a direct path. Each content object is assigned to a set of nodes, such that assignment to a lower-level node also results in assignment to each higher-level node in the lower-level node's direct path to a top of the hierarchy. Metadata of the content object is then modified to include a set of tags, each tag being a term from an assigned node. Tags are used to categorize the content object, summarize of the content object, identify recommended content objects, identify content objects responsive to a search query, and/or identify other content objects to supplement the content object.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Abstract: Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.