Abstract: Taste and smell classification from multilanguage descriptions can be performed by extracting, by one or more processors using natural language processing, a text including one or more words associated with taste and smell perceptions from an input received from a plurality of users. The input includes multilanguage information regarding at least one of changes in smell and changes in taste perceived by each of the plurality of users. Feature vectors are generated for the text extracted from the input using global vectors, and a distance between the feature vectors and a plurality of reference descriptors associated with taste and smell is calculated for determining a similarity between the text and the reference descriptors and creating a training dataset based on which a classification model is generated for categorizing the plurality of users according to the at least one of changes in smell and changes in taste.

Abstract: Taste and smell classification from multilanguage descriptions can be performed by extracting, by one or more processors using natural language processing, a text including one or more words associated with taste and smell perceptions from an input received from a plurality of users. The input includes multilanguage information regarding at least one of changes in smell and changes in taste perceived by each of the plurality of users. Feature vectors are generated for the text extracted from the input using global vectors, and a distance between the feature vectors and a plurality of reference descriptors associated with taste and smell is calculated for determining a similarity between the text and the reference descriptors and creating a training dataset based on which a classification model is generated for categorizing the plurality of users according to the at least one of changes in smell and changes in taste.

Abstract: Embodiments of the invention include methods, systems, and computer program products for determining stroke onset. Aspects of the invention include determining a baseline behavioral model for a user and receiving real-time user data from a personal portable device. Aspects of the invention also include analyzing the real-time user data to determine the presence of an abnormal event. Aspects of the invention also include, based at least in part on a determination that the abnormal event is present, conducting a plurality of stroke analyses to generate a plurality of impairment characteristics. Aspects of the invention also include integrating the plurality of impairment characteristics, comparing the integrated plurality of impairment characteristics to the baseline behavioral model and outputting a stroke onset determination.

Abstract: An embodiment of the invention may include a method, computer program product and system for operating an electronic display device. An embodiment may include displaying, using a first refresh rate, first content on a first partition of a display area of the electronic display device. An embodiment may include displaying, using a second refresh rate, second content on a second partition of the display area of the electronic display device. The first refresh rate is different from the second refresh rate.

Abstract: An embodiment of the invention may include a method, computer program product and system for operating an electronic display device. An embodiment may include displaying, using a first refresh rate, first content on a first partition of a display area of the electronic display device. An embodiment may include displaying, using a second refresh rate, second content on a second partition of the display area of the electronic display device. The first refresh rate is different from the second refresh rate.

Abstract: Embodiments of the invention include methods, systems, and computer program products for determining stroke onset. Aspects of the invention include determining a baseline behavioral model for a user and receiving real-time user data from a personal portable device. Aspects of the invention also include analyzing the real-time user data to determine the presence of an abnormal event. Aspects of the invention also include, based at least in part on a determination that the abnormal event is present, conducting a plurality of stroke analyses to generate a plurality of impairment characteristics. Aspects of the invention also include integrating the plurality of impairment characteristics, comparing the integrated plurality of impairment characteristics to the baseline behavioral model and outputting a stroke onset determination.

Abstract: Systems, methods, and computer-readable media are described for predicting consumer response to a stimulus based on olfactory characteristics of the stimulus. An intrinsic factor score associated with a product can be determined based on an intrinsic attribute of the stimulus, and optionally, further based on data indicative of historical consumer response to olfactory characteristics of the stimulus. A social factor score associated with a user can also be determined using available olfactory preference data associated with the user and/or data representative of one or more social signals indicative of a predicted response of the user to olfactory characteristics of the stimulus. A collaborative filtering technique can be employed to determine a recommendation score for the stimulus using the intrinsic factor score and the social factor score. The recommendation score can be compared to a threshold value to determine whether to recommend the stimulus to the user.

Abstract: A system for random number generation may include non-volatile memory, and a random number stored on the non-volatile memory. The system may also include a key linked to the random number. The system may further include a computer-apparatus designed to use the random number based upon the key.

Abstract: A system for random number generation may include non-volatile memory, and a random number stored on the non-volatile memory. The system may also include a key linked to the random number. The system may further include a computer-apparatus designed to use the random number based upon the key.

Abstract: A method of implementing verification of a complex workflow includes partitioning the workflow into modules, wherein the modules have inputs, processing steps and outputs; selecting, from the workflow, one of the partitioned modules for independent verification by challenge thereof; running, with a computing device, a challenge of the selected module, the challenge comprising comparing reference outputs to outputs of the selected module, wherein reference inputs are received by the selected module and the reference outputs are generated using the reference inputs and one of an ideal performing module or a well-established module; determining whether outputs of the selected module meet verification criteria with respect to the reference outputs, and based on the determining, implementing one of: declaring the selected module verified; subdividing the selected module into smaller modules and repeating the challenge on the smaller modules; or declaring the selected module not verified.

Abstract: A system for random number generation may include non-volatile memory, and a random number stored on the non-volatile memory. The system may also include a key linked to the random number. The system may further include a computer-apparatus designed to use the random number based upon the key.

Abstract: A system for random number generation may include non-volatile memory, and a random number stored on the non-volatile memory. The system may also include a key linked to the random number. The system may further include a computer-apparatus designed to use the random number based upon the key.

Abstract: A method of implementing verification of a complex workflow includes partitioning the workflow into modules, wherein the modules have inputs, processing steps and outputs; selecting, from the workflow, one of the partitioned modules for independent verification by challenge thereof; running, with a computing device, a challenge of the selected module, the challenge comprising comparing reference outputs to outputs of the selected module, wherein reference inputs are received by the selected module and the reference outputs are generated using the reference inputs and one of an ideal performing module or a well-established module; determining whether outputs of the selected module meet verification criteria with respect to the reference outputs, and based on the determining, implementing one of: declaring the selected module verified; subdividing the selected module into smaller modules and repeating the challenge on the smaller modules; or declaring the selected module not verified.