Abstract: A processor-implemented method, system, and/or computer program product defines multiple dimensional data gravity wells on a conformed dimensional data gravity wells membrane. Non-dimensional data objects are associated with dimension objects to define conformed dimensional objects. The conformed dimensional objects are parsed into an n-tuple that includes a pointer to one of the non-dimensional data objects, a probability that a non-dimensional data object has been associated with a correct dimension object, and a weighting factor of importance of the conformed dimensional object. A virtual mass of each parsed conformed dimensional object is calculated, in order to define a shape of multiple dimensional data gravity wells that are created when conformed dimensional objects are pulled into each of the dimensional data gravity well frameworks on a conformed dimensional data gravity wells membrane.

Abstract: At least one attribute type associated with an individual in a first record of a first database and one or more similar attribute types in record(s) of other second database(s) are located. The attribute types compared. Based on the comparison, a first weighted score for the first record and another weighted score for each other records are computed. The weighted score indicates a likelihood the particular attribute type is associated with a same individual as other attribute type(s) located in other record(s) and further accounts for a time delta between measurements of the attribute types. Confidence score outputs for the records are also computed. The confidence score output of a record is based on all weighted scores of that record and indicates a likelihood that record is associated with the same individual. At least one database is updated based on at least one of the confidence score outputs.

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 navigates through a database. A non-contextual data object, which ambiguously relates to multiple subject-matters, is associated with a context object to define a synthetic context-based object. 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 a first data node and a second data node within a database. In response to receiving a request for identifying and retrieving data from a data node that has a same context as the first data node, data from the second data node is retrieved.

Abstract: A processor-implemented method, system, and computer program product guides mobility-impaired pedestrians. A processor receives mobile tracking readings from each of multiple mobility assistance devices, and identifies pedestrian routes taken by the mobility assistance devices to a desired destination. The processor identifies multiple routes, each of which has more mobile tracking readings than other pedestrian routes. The processor associates a recurring public event to times during which mobile tracking readings were taken to a first pedestrian route, and associates a lack of the recurring public event to times during which mobile tracking readings were taken to a second pedestrian route. If the recurring public event is currently in progress along the first pedestrian route, then the processor transmits directions that describe the second pedestrian route at which the public event is not occurring.

Abstract: A computer-implemented method, system and/or computer program product manages data in a webpage. A processor receives an input to an input box located in a first webpage on a first network. This input is analyzed to determine whether there is match between a subject topic of the entered data and a first interest window on the first webpage, where the first interest window is reserved for data entries that are described by the subject topic. In response to a processor being unable to determine the subject topic of the entered data in the text entry box, the processor creates a new interest window in the first webpage.

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 computer implemented method, apparatus, and computer usable program code for finding skills and resources for a chaotic event. Skills data for the chaotic event are organized. A determination is made whether the skills and the resources are available in response to a receiving an identification of the skills and the resources that are required to manage the chaotic event. The skills and the resources are optimized based on requirements and constraints, potential skills, and enabling resources to determine optimized skills and optimized resources. The availability of the optimized skills and the optimized resources are verified. The optimized skills and the optimized resources are reoptimized in response to a determination that the optimized skills and the optimized resources are unavailable.

Abstract: A computer implemented method, apparatus, and computer program product of determining mechanisms of action for therapies. A first set of brain scans for each subject in a plurality of subjects generated at a first time period and a second set of brain scans for each subject generated at a second time period are received. Each subject is diagnosed with a given condition and received a given therapy. A set of changes in the set of brain scans is identified for the each subject based on a comparison of a first set of regions of interest in the first set of scans for each subject with a second set of regions of interest in the second set of scans for each subject. A set of typical changes attributable to the given therapy is identified. A mechanism of action for the given therapy is generated based on the set of typical changes.

Abstract: A system comprises a hashing logic, which executes instructions to convert raw data into a first logical address and payload data, where the first logical address describes metadata about the payload data. A hardware translation unit executes instructions to translate the first logical address into a first physical address on a storage device. A hardware load/storage unit stores the first logical address and the payload data at the first physical address on the storage device. A hardware exclusive OR (XOR) unit compares two logical address vectors to derive a Hamming distance between the two logical address vectors. A hardware retrieval unit retrieves other payload data that is stored at a second physical address whose second logical address is within a predefined Hamming distance from the first logical address, thus allowing payload data from the two logical addresses to be grouped/associated with one another.

Abstract: A method, system, and/or computer program product securely manages smart card transactions. A processing entity receives a smart card identifier from a smart card. The smart card identifier is a transaction-specific identifier for a transaction, and contains no financial data about a holder of the smart card. The smart card identifier is hidden from a second party to the transaction. The processing entity receives transaction data for the transaction from the second party, where the transaction data is blocked from the smart card. In response to determining that the transaction is valid, the processing entity issues a transaction confirmation to the smart card and a transaction approval to the second party to the transaction.

Abstract: A computer-implemented method, system, and/or computer program product detects contaminants in a pipe that is transporting a known fluid. A baseline vibration pattern is established from readings generated by a smart sensor that is affixed to the pipe. This baseline vibration pattern is caused by a flow of the known fluid as the known fluid travels through the pipe in an unadulterated form. Subsequent readings from the smart sensor are taken to generate a new vibration pattern. In response to the new vibration pattern being different, beyond a predefined range, from the baseline vibration pattern, the new vibration pattern is matched to a known vibration pattern in order to identify a specific contaminant of the known fluid.

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. If using the accuracy values and weighting values fails to adjust the downstream subcomponent to meet a predefined trustworthiness level for making a first type of prediction, then a new downstream computational process that produces a different second type of prediction is executed.

Abstract: A method, system, and computer program product for minimizing surprisal context data. The method comprising the steps of: identifying characteristics of a data event; receiving an input of rank of at least two identified characteristics of the data event; the computer generating a hierarchy of ranked, identified characteristics based on the rank of the at least two identified characteristics of the data event; and comparing the hierarchy of ranked, identified characteristics to a repository of reference artifacts arranged in characteristic context patterns. If at least one reference artifact arranged in characteristic context patterns from the repository matches the hierarchy of ranked, identified characteristics, the characteristic context pattern is stored as a surprisal context filter and compared to a data input of data events to detect anomalous events.

Abstract: A method, computer program product and system for generating and maintaining synthetic context events. The steps include searching a data structure of synthetic context-based objects and associated data for a pattern of context exhibited at a first specified frequency within a first specified time period; combining the synthetic context-based objects and associated data exhibiting the pattern of context exhibited at the first specified frequency within the first specified time period into a synthetic context event; and optimizing and maintaining the synthetic context event by searching the data structure for additional synthetic context-based objects and associated data exhibiting a same pattern of context at a second specified time period different than the first specified time period and adding the additional synthetic context-based objects and associated data to the synthetic context event.

Abstract: Biometric data, which identifies a set of biometric patterns, is received from a set of biometric sensors. The biometric data is processed to form digital biometric data that identifies attributes of the biometric data. Thereafter, a biometric cohort is generated using the digital biometric data. Each member of the set of biometric cohorts shares at least one biometric attribute in common.

Abstract: A processor-implemented method, system and/or computer program product allocates multiple resources from multiple organizations. A series of requests for multiple resources from multiple organizations is received. The multiple resources are required to accomplish a specific task, and each of the multiple resources is assigned a probability of consumption. Probabilities of availability of the multiple resources are then determined and transmitted to the organizations.

Abstract: A smart card comprises: a processing circuit; a memory that contains a protected object; an activity detector that receives a signal that describes a planned activity of a person who is in physical possession of the smart card; and an activity analyzer that evaluates features of the planned activity. In response to the activity analyzer determining that a predefined risk associated with the planned activity exceeds a predetermined value, the activity analyzer: issues an instruction to the person who is in physical possession of the smart card to provide a biomarker to a biosensor that is physically contained within the smart card; and receives, from the biosensor, real-time biometric data for the person who is in physical possession of the smart card.

Abstract: A method, system, and/or computer program product allocates computer processing work. One or more processors identify: an input data that is stored in a first computer for processing by a computer program; a virtual machine, stored in a second computer, that is capable of executing the computer program; a first set of constraint rules against moving the input data from the first computer; and a second set of constraint rules against moving the virtual machine from the second computer. The one or more processors assign a weight to each constraint rule, and sum the weight of all constraint rules that are applicable. In response to the first total constraint rule weight exceeding the second total constraint rule weight, movement of the input data from the first computer to the second computer is prohibited and the virtual machine is moved from the second computer to the first computer.

Abstract: A Lab On a Chip (LOC) has a Sample Preparation Module (SPM) coupled to a sample inlet, a microchannel coupled to the SPM, and an optic module optically proximate to the microchannel. The optic module holds multiple lenses, each of which has a different effective focal length, such that all fields of focus within the microchannel are covered as objects suspended within the liquid sample pass through the microchannel.