A storage intelligence server including a collector component to receive trace data related to data requests from agent applications executing on computerized devices, a storage component within which the trace data is stored, an analytics component to analyze the trace data to identify a malicious data request in real-time, defining an identified malicious data request, and a controller component having stored thereon a plurality of rules that can update a rule of the plurality of rules or generate a new rule for inclusion in the plurality of rules responsive to the identified malicious data request, defining an active rule, and transmit the active rule to at least one of the firewall and the router.

A storage intelligence server including a collector component to receive trace data related to data requests from agent applications executing on computerized devices, a storage component within which the trace data is stored, an analytics component to analyze the trace data to identify a malicious data request in real-time, defining an identified malicious data request, and a controller component having stored thereon a plurality of rules that can update a rule of the plurality of rules or generate a new rule for inclusion in the plurality of rules responsive to the identified malicious data request, defining an active rule, and transmit the active rule to at least one of the firewall and the router.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

A method includes receiving a designation of one or more first items that are to be included in a new table from a user, specifying, based on metadata related to second items included in each of a plurality of existing tables, an existing table from among the plurality of existing tables, the existing table including at least one of the designated one or more first items in the second items, specifying, based on other metadata related to an input item and an output item accompanied with execution of each of a plurality of programs, a program from among the plurality of programs, the program causing the designated one or more first items to be output as the output item when one of the second items included in the specified existing table is input as the input item, and outputting the specified existing table and the specified program.

An estimation unit (136) retrieves a subtree that matches a query to be estimated, from subtrees included in a syntax tree created from a query inserted into a Web request. In addition, the estimation unit (136) presents information for specifying the type of damage of an attack and an attack target, the information being associated in advance with the subtree obtained by the retrieval of the retrieval unit.

An estimation unit retrieves a subtree that matches a query to be estimated, from subtrees included in a syntax tree created from a query inserted into a Web request. In addition, the estimation unit presents information for specifying the type of damage of an attack and an attack target, the information being associated in advance with the subtree obtained by the retrieval of the retrieval unit.

A verifying entity of a decentralized system is configured to receive information associated with at least one ledger entry of a distributed ledger of the decentralized system, to verify at least a portion of one or more computations associated with the received information, to generate evidence of at least one error in the at least a portion of the one or more computations associated with the received information, and to associate the generated evidence with a public key of the verifying entity. The decentralized system may comprise a proof of space based mining system, and the at least one ledger entry of the distributed ledger may comprise at least one proof of space for the proof of space based mining system.

Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.

Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.

A system for predicting and prescribing actions for impacting policymaking outcomes may include at least one processor configured to access first information scraped from the Internet to identify, for a particular pending policy, information about a plurality of policymakers slated to make a determination on the pending policy. The processor may parse the scraped first information to determine an initial prediction relating to an outcome of the pending policy. The processor may access second information to identify an action likely to change at least one of the initial prediction and the propensity of at least one policymaker, to thereby generate a subsequent prediction corresponding to an increase in a likelihood of achieving the desired outcome. The processor may display to the system user a recommendation to take the action in order to increase the likelihood of achieving the desired outcome.