Abstract: An example operation may include one or more of receiving, by a blockchain node, a request to transfer an asset, generating a blockchain transaction, obtaining one or more rules from a smart contract corresponding to a smart contract identifier, and comparing one or more parameters to the one or more rules to obtain a risk level. In response to the risk level being greater than a threshold, the example operation includes not executing the blockchain transaction. In response to the risk level not being greater than the threshold, the example operation includes executing the transaction. The request includes the smart contract identifier and the one or more parameters. The asset includes one of a trade item or a service to be performed. The blockchain transaction includes the smart contract identifier and the one or more parameters.

Abstract: An exemplary method includes obtaining a training set of code data that includes deprecated code; training a multi-layer neural network on the training set of code data to predict usage events for the deprecated code; predicting usage events for the deprecated code, in a first set of code data, using the trained multi-layer neural network; estimating a value of risk associated with the deprecated code in response to the predicted usage events; comparing the estimated value of risk to a threshold; and, in response to the estimated value of risk exceeding the threshold, implementing an ameliorative action regarding the deprecated code.

Abstract: A user situational context and user's computing device context is detected based on input data. Content associated with the user's computing device and an importance factor associated with the content is determined. A risk factor associated with disclosing the content is determined based on the importance factor. A controlling action is triggered to control the content.

Abstract: A smart lens system may include a hardware processor coupled to a smart contact lens, which may include a microprocessor, an image capturing sensor, and a wireless communication interface. The smart lens system may determine reading factors associated with a user with respect to the user reading content item, based on data related to the user's physiological movements captured by the smart contact lens. The reading factors may include a user's cognitive state determined at least from analyzing data representing the user's physiological movements. Responsive to determining that the user's cognitive state is above a threshold value, the smart lens system may generate an assistive action associated with the content item and transmit a signal to at least one assistive device to perform the assistive action. The assistive device performs the assistive action responsive to receiving the signal.

Abstract: A method includes producing a user profile in response to user data; obtaining context for estimating the duration of a down-time; estimating the duration of the down-time; determining experience enhancement factors in response to the user profile and the estimated duration of the down-time; determining an activity selection model in response to the context, the user data, and the experience enhancement factors; generating personalized engaging activities by applying the activity selection model to a plurality of potential activities; partitioning the estimated duration of the down-time into segments; sequencing the personalized engaging activities to fit into the segments; and presenting the personalized engaging activities to the user via a computing device. A computer readable medium embodies instructions for the method and an apparatus including a processor is operative to facilitate the method.

Abstract: A method includes obtaining a user profile that includes a user's affinities to each of a plurality of micro-tasks; estimating a duration of down-time for the user; estimating task selection factors responsive to the user profile and to the estimated duration of down-time; generating a list of micro-tasks responsive to the task selection factors; ranking the list of micro-tasks according to the user's affinities; partitioning the down-time according to the ranked list of micro-tasks; and presenting one or more of the micro-tasks to the user, according to the partitioning of the down-time, by altering operation of a user device.

Abstract: Automatically managing ameliorative process that controls undesired code use in an application based on predicted valuation and risk vectors. A multidimensional risk vectors may be received in relation to current and future use of undesired code. Amelioration actions may be classifies by using a custom trained machine learning model. An optimal amelioration action may be selected based on at least one optimization objective function. The selected amelioration action may be taken to control undesired code use in application. Examples of an amelioration action may include changing of the characteristics of a user interface and stopping an application or a component of the application from running.

Abstract: A conversation attendant and assistant platform implements a method of receiving by a computer a plurality of messages in a plurality of conversations via one or more messaging applications. The platform tags each message of the plurality of messages with a message cohort and an amelioration action, and assigns a risk to the given message based on the message cohort. The platform also determines a user context of a user of the computer, and, in response to factors including the user context and the risk, assigns a concern level to the given message. The platform accumulates and summarizes the given message along with other messages in a conversation of the given message. In case the concern level exceeds a threshold, the platform selects one or more delivery channels for surfacing a summary of the conversation and surfaces the summary via the one or more delivery channels.

Abstract: A computer-implemented method of controlling a computer system is provided. In particular, the method relates to controlling of a touchscreen of the computer system in order to display contextually relevant user interface objects on a graphical display of the touchscreen. The computer system includes a processor and the touchscreen includes a touch sensor as an input device. The method includes determining, by way of a user context determination module, a user context of at least one user of the computer system, selecting, using an icon selection module, one or more user interface objects which are contextually relevant to the determined context of the user, and displaying, using the graphical display of the touchscreen, the one or more user interface objects selected by the icon selection module. Determining the user's context may include monitoring the user's behavior, mood or cognitive state.

Abstract: A system and method are provided for implementing a credit-worthiness recommendation system based on social capital. Recommenders are nominated by a user of the system, and the recommenders are queried to provide quantified creditworthiness information about the user.