International Business Machines Corporation

Ravi Mani

Ying Chen

Hovey Raymond Strong

Aaron Michael Cohen

David Bacarella

Joerg Meyer

Pratibha Jamdagneya Sharma

Lawrence Candes

Lisa Seacat DeLuca

Travis M Grigsby

Jeb R Linton

Carl Kraenzel

Trevor Livingston

A computer-implemented method includes crawling, by a web crawler, one or more webpages to gather information, resulting in gathered information. The computer-implemented method includes obtaining, by a honeypot logger, activity log data of one or more hackers that access a portion of honeypot content deployed by a honeypot. The computer-implemented method includes dynamically configuring, by a machine capable of learning, the honeypot using the activity log data and the gathered information.

Dynamically configuring a honeypot

A power service receives, from one or more battery enabled mobile devices, battery usage information for one or more locations within an area. A power service identifies, from the battery usage information, one or more battery usage impact factors that are location based that consume additional battery power for the area. A power service predicts, based on the one or more battery usage impact factors for the area a predicted battery consumption factor in the area. A power service updates one or more user schedules of users with one or more events scheduled in the area with an alert identifying the predicted battery consumption factor in the area.

Optimizing scheduled charging of battery enabled devices based on a predicted battery consumption factor for an area

A power service receives one or more types of individual current usage from one or more battery enabled devices. The power service receives a user schedule of predicted usage for the one or more battery enabled devices. The power service analyzes the one or more types of current usage and the predicted usage to identify a separate recommended charging time and charging location for each of the one or more battery enabled devices. The power service updates the user schedule to specify at least one event for scheduling each separate recommended charging time and charging location for each of the one or more battery enabled devices.

Scheduling optimized charging of battery enabled devices based on power usage impact data received from multiple sources

A power service receives, from battery enabled devices, battery charging information for multiple locations, wherein the battery charging information specifies the type of power source a device is being charged from and an amount of time charged. The power service analyzes the battery charging information for the locations to identify moving charging locations that change location. The power service filters the locations to identify locations where the type of power source is a power outlet. The power service filters the locations against a security map to identify a first selection of locations that are publicly accessible and a second selection of locations that require a security authorization. The power service generates a base map of the selection of locations. The power service specifies the base map for each user based on a schedule of the user identifying predicted locations and whether each particular user has a required security authorization.

Specifying a map of available locations for recharging battery enabled devices based on a schedule of predicted locations for a user

A power service receives a user schedule of one or more events each specifying predicted usage and predicted location for one or more battery enabled mobile devices. The power service accesses one or more battery usage impact factors for each predicted location. The power service analyzes the predicted usage and predicted location for each of the one or more events and the one or more battery usage impact factors to predict at least one recommended charging time and charging location for each of the one or more battery enabled mobile devices. The power service updates the user schedule to specify at least one charging event for each at least one recommended charging time and charging location.

Scheduling optimized charging of battery enabled devices based on battery usage impact factors and predicted usage received from multiple sources

A computer implemented method, a computer program product, and a data processing system display a user-defined email preview within a mail folder of an email client. A user can enter a user-defined preview text into a preview field associated with a particular email. When a preview of the email is shown in a mail folder, the user-defined preview text is shown as the email preview instead of a truncated portion of the email body.

Receiver side indication of preview content for template emails

Transforming a user-supplied DTD satisfying a first XML grammar into a PDTD satisfying a second XML grammar, including converting DTD declarations of alternate content to sequences, converting DTD declarations of optional content to mandatory content, converting DTD declarations of imbedded sequences to subsequences, and demoting attribute definitions of DTD elements having attributes to children of the DTD elements having attributes. Embodiments include converting recursions into repetitions, demoting imbedded compound repetitions from element declarations having imbedded compound repetitions, and demoting imbedded leaves from elements having imbedded leaves.

Tree construction for XML to XML document transformation

Graphical specification of an XML to XML transformation rule, including receiving a user's selection of a user-selected, optionally ambiguous, target leaf node, from a target tree of an initial target context, the target leaf node representing a target XML element to be mapped by the transformation rule; if the target leaf node is ambiguous, disambiguating the target leaf node; and adding the target leaf node to the transformation rule. Embodiments typically include receiving a user's selection of at least one user-selected, optionally ambiguous, source leaf node, from a source tree of an initial source context, wherein the source leaf node represents a source XML element to be mapped to the target leaf node by the transformation rule; if the source leaf node is ambiguous, disambiguating the source leaf node; and adding the user-selected source leaf node to the transformation rule.

Graphical specification of XML to XML transformation rules

Transforming a source XML document satisfying a source DTD into a target XML document satisfying a target DTD, transforming the source XML document into a source document tree, where the source XML document satisfies a first XML grammar and the source document tree satisfies a second XML grammar; converting the source document tree into a target document tree satisfying the second XML grammar; and transforming the target document tree into the target XML document, wherein the target XML document satisfies the first XML grammar.

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Scarsdale, NY, United States of America

Ravi Mani