Abstract: A processor-implemented method, system, and/or computer program product guides mobility-impaired pedestrians. Mobile tracking readings are received from multiple mobility assistance devices, each of which has an affixed tracking device. Based on these mobile tracking readings, multiple pedestrian routes for mobility-impaired pedestrians, including an optimal pedestrian route that has the highest tracking history to a desired destination, are generated.

Abstract: A processor-implemented method, system, and/or computer program product generates a recommendation for a worker to be included in a project team. A requisite skill set that is not presently needed, but will be needed in the future, by a project team is determined. Historical data that describe antecedent conditions, which caused a historical worker to obtain the requisite skill set, is received. A candidate worker's current skill set data is adjusted with skill set enhancers, which are available to members of the project team, to generate a predicted future skill set of the candidate worker. In response to the needed requisite skill set matching the predicted future skill set of the candidate worker, a recommendation is generated for adding that candidate worker to the project team.

Abstract: A computer implemented method, system, and/or computer program product generates deportment and comportment cohorts. Digital sensor data comprises event metadata describes a set of events associated with an individual. Descriptive data about the individual is retrieved by data mining a combination of online sources and off-line sources. A set of conduct analysis models is selected based on event metadata and available description data. The event metadata and the description data are analyzed in the set of conduct analysis models to form a deportment and comportment cohort, where the deportment and comportment cohort comprises attributes identifying a demeanor and manner of the individual.

Abstract: A processor-implemented method, system, and/or computer program product derives and utilizes a context object to generate a synthetic context-based object. A context object for a non-contextual data object is derived by contextually searching a document, which contains multiple instances of the non-contextual data object, according to a profile of a particular user. The non-contextual data object is associated with the derived context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with a data store in a data structure that contains heterogeneous data stores having different formats.

Abstract: A processor-implemented method, system, and/or computer program product allocates computer processing work. Input data, which has been deemed to be in need of processing, is stored in a first computer. A virtual machine that is capable of processing the input data is stored on a second computer. A first set of constraint rules contains constraint rules against moving the input data from the first computer, and a second set of constraint rules contains constraint rules against moving the virtual machine from the second computer. Based on the first and second constraint rules, either the virtual machine is moved to the first computer or the input data is moved to the second computer.

Abstract: A computer hardware-implemented method, system, and/or computer program product prevents a cascading failure in a complex stream computer system causing an untrustworthy output from the complex stream computer system. Multiple upstream subcomponents in a complex stream computer system generate multiple outputs, which are used as inputs to a downstream subcomponent, wherein the multiple upstream subcomponents execute upstream computational processes. Each upstream computational process is examined to determine an accuracy of each identified output. An accuracy value is assigned to each of the multiple outputs from the upstream subcomponents, and weighting values are assigned to each of the inputs to the downstream subcomponent. The accuracy values and weighting values are utilized to dynamically adjust inputs to the downstream subcomponent until an output from the downstream subcomponent meets a predefined trustworthiness level.

Abstract: A processor-implemented method, system, and/or computer program product generates and utilizes a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects. A non-contextual data object is associated with a context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object. A dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects is constructed for handling requests for data stores.

Abstract: A processor-implemented method, system, and/or computer program product derives and utilizes a context object to generate a synthetic context-based object. A context object for a non-contextual data object is derived by contextually searching a document that contains multiple instances of the non-contextual data object. The non-contextual data object is associated with the derived context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with a data store in a data structure that contains heterogeneous data stores that hold data of different formats.

Abstract: A processor-implemented method, system, and/or computer program product measures and displays facets in context-based conformed dimensional data gravity wells. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane. Data from the multiple context-based conformed dimensional data gravity wells then populates nodes in a data model. A displayed appearance of the particular context-based conformed dimensional data gravity well is dynamically adjusted according to how many parsed synthetic context-based objects are pulled into the particular context-based conformed dimensional data gravity well.

Abstract: A computer implemented method, system, and/or computer program product generates deportment and comportment cohorts. Digital sensor data, which is derived by analyzing multimodal sensor data, comprises event metadata which describes a set of events associated with an individual. Descriptive data about the individual is retrieved by data mining a combination of online sources and off-line sources. A set of conduct analysis models is selected based on event metadata and available description data. The event metadata and the description data are analyzed in the set of conduct analysis models to form a deportment and comportment cohort, where the deportment and comportment cohort comprises attributes identifying a demeanor and manner of the individual.

Abstract: A method, computer program product and system for managing an overload of signals on a network due to usage by a large number of users on the network during an event, comprising: detecting a cluster of communication on the network, determining a physical location of a centroid of the cluster of the communication on the network, associating the physical location of the centroid to be the approximate physical location of the event; reviewing information within cluster of communication being sent through the network regarding the event; categorizing the event based on a predetermined set of rules; determining bandwidth limitations of the network for users within a determined proximity to the physical location of the event; determining the resources necessary to respond to and resolve the event; and allocating bandwidth of the network based upon the resources and the proximity of users to the physical location of the event.

Abstract: A method, a system and a computer program product for determining whether a change in value of a data item relating to an entity being tracked within a cohort is statistically and contextually significant. A computer captures a plurality data items relating to the entity being tracked at a time N+1. The value of the data item at time N+1 is compared to a value of a historical data item at time N. If the value of the data item at time N+1 is different from the value of the historical data item at time N, determining that a change has occurred. If a change in a data item has occurred, determining whether the change in the data item is related to the entity being tracked is statistically and contextually significant in n space on multiple dimensions.

Abstract: A method, a system and a computer program product for determining whether a change in value of a data item relating to an entity being tracked within a cohort is statistically and contextually significant. A computer captures a plurality data items relating to the entity being tracked at a time N+1. The value of the data item at time N+1 is compared to a value of a historical data item at time N. If the value of the data item at time N+1 is different from the value of the historical data item at time N, determining that a change has occurred. If a change in a data item has occurred, determining whether the change in the data item is related to the entity being tracked is statistically and contextually significant in n space on multiple dimensions.

Abstract: A processor-implemented method, system, and/or computer program product generate and utilize a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects. A non-contextual data object is associated with a context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object. A dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects is then constructed for handling requests for data stores.

Abstract: A processor-implemented method, system, and/or computer program product measures and displays facets in context-based conformed dimensional data gravity wells. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane. Data from the multiple context-based conformed dimensional data gravity wells then populates nodes in a data model. A displayed appearance of the particular context-based conformed dimensional data gravity well is dynamically adjusted according to the how closely each of the multiple parsed synthetic context-based objects matches said at least one context object and/or at least one dimension object.

Abstract: A method, system, and/or computer program product determines conditions of intermodal shipping containers on a cargo ship. A processor establishes a baseline composite vibration pattern from readings generated by multiple vibration sensors that are affixed to multiple intermodal shipping containers on a cargo ship. Subsequent readings are taken from the multiple vibration sensors to generate a new composite vibration pattern. The processor also receives humidity readings from humidity sensors that are affixed to interiors of the multiple intermodal shipping containers, and then combines the humidity readings with the new composite vibration pattern to create a vibration/humidity pattern.

Abstract: A method, system, and/or computer program product enables the secure debugging of a software application. A server receives a secure software application from a client. The secure application is designed to execute within the server, and access to data used by the secure software application is protected by a security object, which allows a processor within the server to access the data used by the secure software application without permitting data to exit unprotected from the processor. The server also receives a secure sidecar debugging application from the client. The secure sidecar debugging application is designed to debug the secure application, but cannot be used by the server. If there is an error in execution of the secure software application within the server, the server transmits the secure software application to the client, where it is debugged using the secure sidecar debugging application.

Abstract: A method, system, and/or computer program product securely generates and/or manages a virtual card on a mobile device. The mobile device receives a protected application, which initially cannot be accessed by an operating system for execution by a processor. The mobile device also receives a security object, which is used to convert the received protected application into an executable application that can be utilized by the operating system for execution by the processor. The executable application is then executed by the processor to act as a virtual card, which provides a functionality of a predefined physical electronic or magnetic-stripe card.

Abstract: A processor-implemented method, system, and/or computer program product derives and utilizes a context object to generate a synthetic context-based object. A context object for a non-contextual data object is derived by contextually searching a document that contains multiple instances of the non-contextual data object. The non-contextual data object is associated with the derived context object to define a synthetic context-based object, where the non-contextual data object ambiguously relates to multiple subject-matters, and where the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object. The synthetic context-based object is then associated with at least one specific data store, which includes data that is associated with data contained in the non-contextual data object and the context object.

Abstract: A method, system, and computer program product for minimizing surprisal context data. The method includes the steps of: identifying characteristics of a data event; receiving an input of rank of at least two identified characteristics of the data event; generating a hierarchy of ranked, identified characteristics based on the rank of the identified characteristics of the data event; and comparing the hierarchy of ranked, identified characteristics to a repository of characteristic context patterns. If at least one reference artifact of the characteristic context pattern matches the hierarchy of ranked, identified characteristics, the characteristic context pattern is broken into pieces, storing the pieces that matched the hierarchy. The stored pieces are then combined into a surprisal context filter pattern with context determined to be probabilistically present within a specified degree of certainty in a data input and compared to a data input of data events to detect anomalous events.