Abstract: A method for making an inference based on cumulative data. The method utilizes video, audio, and biometric devices to observe a retail environment for the presence of a customer. Once a customer is present, the method identifies every cohort to which the customer corresponds. Next, the method observes the customer as they peruse aisles in the retail environment. When the customer selects a product, the method identifies the selected product and searches the cohorts for alternate products to offer the customer. The method offers one alternate product to the customer and records to the cohorts whether the customer thereinafter accepts the method's offer and selects the alternate product or rejects the method's offer and continues perusing the retail environment aisles. The method continues observing the customer and offering alternate product until the customer leaves the retail environment.

Abstract: A computer implemented method, apparatus, and computer program product for developing neuropsychiatric treatment plans. A treatment plan generator receives a set of diagnoses for a patient. The treatment plan generator automatically analyzes medical information in a set of electronic medical literature sources for potential therapies associated with treatment of each identified condition in the set of diagnoses. The treatment plan generator identifies the potential therapies associated with the treatment of each diagnosed condition. The treatment plan generator selects a set of recommended therapies from the potential therapies based on portions of the medical literature describing each therapy in the potential therapies and a medical history for the patient. The treatment plan generator generates a treatment plan. The treatment plan comprises the set of recommended therapies to treat each diagnosed condition in the set of diagnoses.

Abstract: A computer implemented method, apparatus, and computer-usable program product for validating expected cohort behavior. In one embodiment, sensory data gathered by a set of multimodal sensor devices is processed to form a set of actual cohort behavior data. The sensory data comprises information associated with a cohort group. Each member of the cohort group shares at least one common attribute. The set of actual cohort behavior data is compared to a set of predicted cohort behavior models. The set of actual cohort behavior data comprises information describing actual behavior by members of the cohort group. The set of predicted cohort behavior models comprises information describing an expected behavior of members of the cohort group. A comparison result is generated. The comparison result indicates an accuracy of the set of predicted cohort behavior models.

Abstract: A computer implemented method, apparatus, and computer usable program product for generating an expected behavior model. The process parses event data derived from video data to identify behavioral patterns, wherein the event data comprises metadata describing events occurring in a selected environment. The process analyzes the behavioral patterns to identify a set of expected behavioral patterns occurring in the environment, and generates the expected behavioral model using the expected behavioral patterns.

Abstract: A computer implemented method, apparatus, and computer usable program product for identifying unexpected behavioral patterns. The process parses event data derived from video data to identify behavioral patterns, wherein the event data comprises metadata describing events occurring in a selected environment. The process analyzes the behavioral patterns to identify a set of expected behavioral patterns occurring in the selected environment, and generates an expected behavioral model using the expected behavioral patterns. Thereafter, the process forms a set of unexpected behavioral patterns from the behavioral patterns inconsistent with the expected behavioral model.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a pre/post security area within an airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives inference data comprising inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a security perimeter area surrounding an airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a first airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within an aircraft. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a gate area of an airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a first aircraft. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: Illustrative embodiments provide a computer implemented method, a data processing system, and a computer program product for adjusting cooling settings. The computer implemented method comprises analyzing a set of instructions of an application to determine a number of degrees by which a set of instructions will raise a temperature of at least one processor core. The computer implemented method further calculates a cooling setting for at least one cooling system for the at least one processor core. The computer implemented method adjusts the at least one cooling system based on the cooling setting. The step of analyzing the set of instructions is performed before the set of instructions is executed on the at least one processor core. The step of adjusting the at least one cooling system is performed before the set of instructions is executed on the at least one processor core.

Abstract: A computer-implemented method, system and computer program product of managing and sharing entries into a webpage are presented. The computer-implemented method receives an input to an input box located in a first webpage on a first network. This input is analyzed to determine its subject matter, and is then migrated into an appropriate subject box on the webpage. In one embodiment, the input is then shared with another webpage, for the same user, which is on a second network.

Abstract: A computer implemented method, apparatus, and computer program product for generating a cohort using sensor and actuator input data. A signal is received from a set of sensors and actuators associated with a set of objects. In response to a determination that the signal is in an analog format, the signal is converted from the analog format into a digital format to form digital signal data. The digital signal data is processed to identify sensor and actuator attributes associated with the set of objects. The digital signal data comprises metadata describing the identified sensor and actuator attributes. A set of cohorts is generated using the sensor and actuator attributes, wherein each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one sensor and actuator attribute in common.

Abstract: A computer implemented method, apparatus, and computer program product for scoring deportment and comportment cohorts. A deportment and comportment cohort having a set of conduct attributes is received. The conduct attributes may include at least one of a facial expression, vocalization, body language, and social interactions. A deportment and comportment cohort score is calculated. The deportment and comportment cohort score is normalized to calculate an overall deportment and comportment cohort score using at least one of demographic data and patterns of historical conduct. The overall cohort score indicates an appropriateness of conduct displayed by a member of the deportment and comportment cohort. Thereafter, a predefined action is executed based on the overall deportment and comportment cohort score.

Abstract: The illustrative embodiments described herein provide a computer implemented method, apparatus, and computer program product for generating never-event cohorts. In response to receiving patient care data derived from a population of patients, the patient care data is processed to form digital patient care data. The digital patient care data includes metadata describing a set of patient care patterns associated with one or more patients in the population of patients. The digital patient care data is analyzed using cohort criteria to identify a set of never-event attributes from the set of patient care patterns. The cohort criteria specifies at least one never-event attribute from the set of never-event attributes for each cohort in a set of never-event cohorts. Thereafter, a set of never-event cohorts is generated.

Abstract: A computer implemented method, apparatus, and computer program product for generating receptivity cohorts. A receptivity cohort is identified. The receptivity cohort includes a set of members and conduct attributes for the set of members. Each conduct attribute in the set of conduct attributes describes at least one of a facial expression, vocalization, body language, and social interactions of a member in the set of members. Each conduct attribute is an indicator of receptiveness to a proposed future change in a set of circumstances associated with the set of members. Events metadata is received. The events metadata describes the set of circumstances associated with the set of members. The set of conduct attributes and the events metadata is analyzed to generate a receptivity score for the receptivity cohort. The receptivity score indicates a level of receptiveness of the set of members to the proposed future change in the set of circumstances.

Abstract: The illustrative embodiments described herein provide a computer implemented method, apparatus, and computer program product for generating retail cohorts. In an illustrative embodiment, retail data derived from a population of retail customers is received and processed to form digital retail data. The digital retail data includes metadata describing a set of retail patterns associated with one or more customers in the population of retail customers. The set of retail patterns form a set of retail attributes for cohort generation. The digital retail data is analyzed using cohort criteria to identify a set of retail cohorts based on the set of retail attributes. The cohort criteria specify at least one retail attribute from the set of retail attributes for each cohort in the set of retail cohorts. Thereafter, a set of retail cohorts are generated. The retail cohorts have members selected from the population of retail customers, and have the at least one retail attribute in common.

Abstract: A computer implemented method, apparatus, and computer program product for generating risk scores for specific risk cohorts. Digital sensor data associated with a specific risk cohort is received from a set of multimodal sensors. The specific risk cohort includes a set of identified cohort members. The digital sensor data includes metadata describing attributes associated with at least one cohort member in the set of identified cohort members. Description data for each cohort member in the set of identified cohort members is retrieved to form a set of cohort description data. The description data for each cohort member comprises data describing a previous history of the cohort member or a current status of the cohort member. The cohort member is a person, animal, plant, thing, or location. A specific risk score is generated for the specific risk cohort based on selected risk factors, the attributes associated with the at least one identified member, and the set of cohort description data.

Abstract: A computer implemented method, apparatus, and computer program product for generating risk scores for specific risk cohorts. Digital sensor data associated with a specific risk cohort is received from a set of multimodal sensors. The specific risk cohort includes a set of identified cohort members. The digital sensor data includes metadata describing attributes associated with at least one cohort member in the set of identified cohort members. Description data for each cohort member in the set of identified cohort members is retrieved to form a set of cohort description data. The description data for each cohort member comprises data describing a previous history of the cohort member or a current status of the cohort member. The cohort member is a person, animal, plant, thing, or location. A specific risk score is generated for the specific risk cohort based on selected risk factors, the attributes associated with the at least one identified member, and the set of cohort description data.