Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Various embodiments of the invention allow to detect and analyze gestures, such as tapping and swiping patterns, that a user performs in the process of interacting with a computing device to determine the user's mood therefrom, so as to initiate an appropriate response. In certain embodiments, this is accomplished, without requiring labeled training data, by monitoring a user-device interaction via sensors and analyzing the sensor data based on contextual data via a processor to determine a gesture and one or more properties associated with an emotional state of the user. A response is generated based on the identified emotional state.

Abstract: In one embodiment, a method includes determining real-time location information for a transportation item. The method further includes determining real-time route information for a plurality of vehicles, the plurality of vehicles comprising a vehicle-in-transit actively transporting the transportation item. In addition, the method includes analyzing, via the real-time location information and the real-time route information, a route efficiency of the plurality of vehicles relative to an intended destination of the transportation item. Further, the method includes selecting a replacement vehicle from among the plurality of vehicles based, at least in part, on a result of the analyzing. Additionally, the method includes initiating physical transfer of the transportation item from the vehicle-in-transit to the replacement vehicle.

Abstract: The present invention relates generally to a prediction of health risk. Aspects of the present invention include using a general model to model a user's health risk. In embodiments of the present invention the general model is modified to a user's specific behaviors or inputs. In embodiments of the present invention the model is compared to actual data obtained by sensors in everyday consumer products. In embodiments of the present invention, based on the outcome of the comparison, an emergency response can be triggered and or health and wellness improvement behaviors can be suggested.

Abstract: Various embodiments of the invention allow to detect and analyze gestures, such as tapping and swiping patterns, that a user performs in the process of interacting with a computing device to determine the user's mood therefrom, so as to initiate an appropriate response. In certain embodiments, this is accomplished, without requiring labeled training data, by monitoring a user-device interaction via sensors and analyzing the sensor data based on contextual data via a processor to determine a gesture and one or more properties associated with an emotional state of the user. A response is generated based on the identified emotional state.

Abstract: In a computer capable of executing a superscalar and a very long instruction word instruction wherein the computer has compiled a number of primitive operations that can be executed in parallel into a single instruction having multiple parcels and each of the parcels correspond to an operation, the invention is an improved instruction cache to store all potential subsequent instructions and a method to select the subsequent instruction when several possible branches of execution are probable and must be evaluated. All branch conditions and all addresses of potential subsequent instructions of an instruction are replicated and stored in the instruction cache. All potential subsequent instructions are stored in the same block of the instruction cache having the same next address; individual instructions are identified by the replicated offset addresses. Further the instruction cache is divided into minicaches, each minicache to store one parcel, which allows rapid autonomous execution of each parcel.

Abstract: CPU overhead is minimized through tracking speculative exceptions (202) for later processing during exception resolution (204) including pointing to the addresses of these speculative instructions, and resolving (204) these exceptions by correcting (206) what caused the exception and re-executing (208) the instructions which are known to be in a taken path. Tracking speculative exceptions has two components which use an exception bit which is set in response to an exception condition (213). The invention tracks an original speculative exception which occurs when a speculative instruction whose operand(s) do not have any exception bits set encounters an exception condition. Speculative exception resolution is triggered when a non-speculative instruction--which is in the taken path of a conditional branch--uses an operand from a register having its exception bit set. The presence of an exception condition and a non-speculative instruction yields an exception signal (220) to exception resolution (204).