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2752 results about "Upgrade" patented technology

Upgrading is the process of replacing a product with a newer version of the same product. In computing and consumer electronics an upgrade is generally a replacement of hardware, software or firmware with a newer or better version, in order to bring the system up to date or to improve its characteristics.

Slim terminal gaming system

A computer gaming system and method of operation thereof are provided that both drastically reduce the cost of gaming stations and allow contemporaneous access to multiple game programs from a single gaming station. The computer gaming system of the present invention allows for transparent modifications and upgrades to the gaming programs by executing gaming programs on a server/host computer connected to a plurality of client/terminal computers via communication pathways. Each client/terminal computer comprises a client/terminal program that allows input and output streams of the gaming program executed on the server/host computer to be separated and redirected to the client/terminal computers. Since the gaming programs are executed entirely on the server/host computer, with only wagering input and display output operations being executed on the client/terminal computers, the cost of the hardware and software required for each client/terminal computer is greatly reduced. A patron of a client/terminal computer can access any of the gaming programs executed on the server/host computer. Modifications and upgrades of the gaming programs only need to be performed on the server/host computer. By using a stereo head-mounted display together with a joystick input device and wireless communication pathways, the present invention allows a patron to participate in a mobile gaming environment.

Log-on service providing credential level change without loss of session continuity

A security architecture has been developed in which a single sign-on is provided for multiple information resources. Rather than specifying a single authentication scheme for all information resources, the security architecture associates trust-level requirements with information resources. Authentication schemes (e.g., those based on passwords, certificates, biometric techniques, smart cards, etc.) are employed depending on the trust-level requirement(s) of an information resource (or information resources) to be accessed. Once credentials have been obtained for an entity and the entity has been authenticated to a given trust level, access is granted, without the need for further credentials and authentication, to information resources for which the authenticated trust level is sufficient. The security architecture allows upgrade of credentials for a given session. This capability is particularly advantageous in the context of a single, enterprise-wide log-on. An entity (e.g., a user or an application) may initially log-on with a credential suitable for one or more resources in an initial resource set, but then require access to resource requiring authentication at higher trust level. In such case, the log-on service allows additional credentials to be provided to authenticate at the higher trust level. The log-on service allows upgrading and/or downgrading without loss of session continuity (i.e., without loss of identity mappings, authorizations, permissions, and environmental variables, etc.).

System And Methodology For Automatic Tuning Of Database Query Optimizer

System and methodology for automatic tuning of database query optimizer is described. In one embodiment, in a database system having an optimizer for selecting a query plan for executing a database query, a method of the present invention is described for automatically tuning query performance to prevent query performance regression that may occur during upgrade of the database system from a prior version to a new version, the method comprises steps of: in response to receiving a given database query for execution, specifying a query plan generated by the prior version's optimizer as a baseline best plan for executing the given database query; generating at least one new query plan using the new version's optimizer; learning performance for each new query plan generated by recording corresponding query execution metrics; if a given new query plan is observed to have better performance than the best plan previously specified, specifying that given new query plan to be the best plan for executing the given database query; if a given new query plan is observed to have worse performance than the best plan previously specified, specifying that given new query plan to be a bad plan to be avoided in the future; and automatically tuning future execution of the given database query by using the query plan that the system learned was the best plan.
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