Abstract: In some implementations, a vehicle device may receive, from a controller area network (CAN) bus of a vehicle and for a time period, messages received by the CAN bus after an engine of the vehicle is turned on. The vehicle device may combine identifiers provided in unique addresses, of the messages received by the CAN bus, to generate a unique identifier, and may utilize the unique identifier to determine data identifying a year, a make, and a model of the vehicle. The vehicle device may utilize the data identifying the year, the make, and the model of the vehicle to determine non-standard parameter identifiers associated with an engine control module of the vehicle.

Abstract: A device may receive an arming signal associated with immobilizing a vehicle. The device may monitor, based on receiving the arming signal, a current associated with an electrical power output from a battery of the vehicle. The device may detect that a measurement of the current satisfies a threshold associated with an ignition component starting an engine of the vehicle. The device may control, based on detecting that the current satisfies the threshold, a bypass circuit to reduce the electrical power output to prevent the ignition component from starting the engine.

Abstract: In some implementations, a vehicle device may receive, from a controller area network (CAN) bus of a vehicle and for a time period, messages received by the CAN bus after an engine of the vehicle is turned on. The vehicle device may combine identifiers provided in unique addresses, of the messages received by the CAN bus, to generate a unique identifier, and may utilize the unique identifier to determine data identifying a year, a make, and a model of the vehicle. The vehicle device may utilize the data identifying the year, the make, and the model of the vehicle to determine non-standard parameter identifiers associated with an engine control module of the vehicle.

Abstract: A device may receive an arming signal associated with immobilizing a vehicle. The device may monitor, based on receiving the arming signal, a current associated with an electrical power output from a battery of the vehicle. The device may detect that a measurement of the current satisfies a threshold associated with an ignition component starting an engine of the vehicle. The device may control, based on detecting that the current satisfies the threshold, a bypass circuit to reduce the electrical power output to prevent the ignition component from starting the engine.

Abstract: A device may receive an arming signal associated with immobilizing a vehicle. The device may monitor, based on receiving the arming signal, a current associated with an electrical power output from a battery of the vehicle. The device may detect that a measurement of the current satisfies a threshold associated with an ignition component starting an engine of the vehicle. The device may control, based on detecting that the current satisfies the threshold, a bypass circuit to reduce the electrical power output to prevent the ignition component from starting the engine.

Abstract: This invention relates to a locking gimbal (10). More specifically, the invention relates to a locking gimbal (10) for automatically locking a gimballed object against motion arising from an external force (FE) applied thereto; and automatically releasing the gimballed object on removal of the external force (FE). The locking gimbal (10) includes a first object (12) pivotable about a first pivot axis (PF), a second object (14) movable along an arc cantered substantially at a second axis, a locking member (16) and a locking formation (18). The first object (12) defines a first reference axis (ARF) passing through the first pivot axis (PF) and a center of gravity (CGF) of the first object (12), whereas the second object (14) defines a second reference axis (ARS) passing through the second axis and a center of gravity (CGS) of the second object (14).

Abstract: Capacity of a database system and/or a computing system that includes a database can be effectively changed from a current computing capacity to another computing capacity. This can be achieved by causing usage capacity of at least one of resource to be changed when the database is active. By way of example, capacity of a database system can be regulated by delaying the execution of the database work based on a target capacity. As a result, database work can take relatively longer to complete when the capacity of a database is effectively regulated to be below its full capacity. In effect, a portion of available capacity (excess capacity) can be made inaccessible to the database. However, excess capacity can be used to manage various services of the database in accordance with one or more service criteria (e.g., Service Level Goals or Agreements).

Abstract: Excess capacity (or excess resources) can be used in a capacity controlled environment to effectively manage data storage of a database. In this context, excess capacity can, for example, be controlled used as needed, as configured and/or on a temporary basis. Management of data storage in a database can, for example, include operations associated with moving or relocating data of the database. Relocation of data can, for example, be performed to relocate data deemed to be “hot” data to a location that can provide a faster access time in order to improve the overall efficiency of the database system.

Abstract: Excess capacity of a database system can be used for learning activities in a controlled computing environment. In this context, excess capacity of a database system can be used as needed and/or on a temporary basis. Furthermore, learning activities can be performed without requiring the use of the capacity that is configured or has been allotted for various other database operations, including those deemed, especially by the users of database system, to serve a main function or a more important purpose. As a result, learning can be performed without adversely affecting other operations deemed to be more critical, especially by the users of databases. Learning activities associated with a database environment can, for example, include learning operations directed to optimization of database queries, for example, by using a basic feedback or an expanded or active learning.

Abstract: Excess capacity available to a database system in a capacity controlled environment can be effectively managed. In particular, excess capacity that is not made available for normal operations of a database system can be used to manage errors, especially situations that may hinder expected performance of the database system. In addition, excess capacity can be used to optimize or further optimize database queries, especially those that meet a criterion (e.g., not fully optimize, not optimized as expected).

Abstract: This invention relates to a locking gimbal (10). More specifically, the invention relates to a locking gimbal (10) for automatically locking a gimballed object against motion arising from an external force (FE) applied thereto; and automatically releasing the gimballed object on removal of the external force (FE). The locking gimbal (10) includes a first object (12) pivotable about a first pivot axis (PF), a second object (14) movable along an arc cantered substantially at a second axis, a locking member (16) and a locking formation (18). The first object (12) defines a first reference axis (ARF) passing through the first pivot axis (PF) and a centre of gravity (CGF) of the first object (12), whereas the second object (14) defines a second reference axis (ARS) passing through the second axis and a centre of gravity (CGS) of the second object (14).

Abstract: A first workload that contains logged predicates contained in database queries is received. A subset of the predicates is selected based on costs associated with the predicates. A compressed workload is formed using the selected subset of the predicates. Indexes are then selected based on the compressed workload.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. Resource usage of one or more resources of the computer system are monitored. A condition code representative of the monitored resource usage is stored. A cost model is modified using the stored condition code. A query execution plan is generated for the database query using the modified cost model. The query execution plan is then executed in order to retrieve data from a database stored on the computer system, wherein the retrieved data is presented to a user for subsequent use and analysis.

Abstract: A system, method, and computer-readable medium that facilitate the optimization of frequently executed queries via automated index creation are provided. Standard optimizer strategies for dynamic index creation are utilized with query frequency information taken from a system's request cache. The described mechanisms provide a process of determining what indexes would be beneficial to query performance based on decisions and information from the optimizer that is ultimately responsible for the choice of index usage. Further, the plan cache is utilized in a manner that provides reliable information about the historical and anticipated frequency of specific queries.

Abstract: Excess capacity (or excess resources) can be used in a capacity controlled environment to effectively manage data storage of a database. In this context, excess capacity can, for example, be controlled used as needed, as configured and/or on a temporary basis. Management of data storage in a database can, for example, include operations associated with moving or relocating data of the database. Relocation of data can, for example, be performed to relocate data deemed to be “hot” data to a location that can provide a faster access time in order to improve the overall efficiency of the database system.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. A query execution plan for the database query is generated using estimated cost information; one or more steps of the query execution plan are executed to retrieve data from a database stored on the computer system. Actual cost information is generated for each of the executed steps, and the estimated cost information is re-calculated using the actual cost information. One or more resource allocation rules defined on one or more steps of the query execution plan are executed, based on the estimated cost information, wherein the resource allocation rules include one or more defined actions. The estimated cost information may be re-calculated using the actual cost information when confidence in the estimated cost information is low, but the estimated cost information may not be re-calculated when confidence in the estimated cost information is high.

Abstract: A system, method, and computer-readable medium that provide automatic and dynamic control of optimizer settings in a large complex system environment are provided. The optimizer may pursue more aggressive query execution plans and switch to a more conservative approach in cases of actual observed inaccuracies.

Abstract: Excess capacity available to a database system in a capacity controlled environment can be effectively managed for maintenance and/or tuning activities. In this context, excess capacity can be used as needed and/or on a temporary basis. Furthermore, maintenance and/or tuning activities can be performed without requiring the use of the configured or allotted capacity. As a result, these operations can be performed without adversely affecting other operations which may be deemed more critical by the users of databases. System maintenance and tuning (or fine tuning) of a database environment can, for example, include operations associated with “Physical Tuning,” and “Index Tuning”. Some exemplary operations include collecting Statistics, analyzing a database workload, sampling, analyzing an execution plan, creating indexes.

Abstract: An improved workload management system and method for a database system. The improved workload management system evaluates certain workload management rules dynamically at key points during database query execution rather than relying on enforcement prior to query activation. In the case of product join operations, the workload management system evaluates the potential impact on system performance by the product join operation after input tables have been populated, but prior to the execution of the join operation. Delaying workload management enforcement to this point ensures that the sizes of inputs and outputs are reliably known and improves system performance impact estimates at a point early enough to prevent any serious performance degradation from an inefficient product join.

Abstract: Excess capacity available to a database system in a capacity controlled environment can be effectively managed. In particular, excess capacity that is not made available for normal operations of a database system can be used to manage errors, especially situations that may hinder expected performance of the database system. In addition, excess capacity can be used to optimize or further optimize database queries, especially those that meet a criterion (e.g., not fully optimize, not optimized as expected).