According to one embodiment, a method, computer system, and computer program product for three-dimensional printing is provided. The embodiment may include analyzing data of a user. The data is collected while the user is performing an activity. The embodiment may include deriving a user behavior model (UBM) of the user based on the analysis of the data. The embodiment may include calculating a relative comfort coefficient (RCC) of the user for the activity based on attributes of the UBM. The embodiment may include predicting adjustments to the attributes of the UBM which result in the RCC exceeding a threshold value. The predicted adjustments are derived using a convolutional neural network classifier. The embodiment may include defining one or more parameters of a tangible component of an object utilized by the user when performing the activity based on the predicted adjustments.

Artificial assistant system notification techniques are described that overcome the challenges of conventional search techniques. In one example, a user profile is generated to describe aspects of products or services learned through natural language conversations between a user and an artificial assistant system. These aspects may include price as well as non-price aspects such as color, texture, material, and so forth. To learn the aspects, the artificial assistant system may leverage spoken utterances and text initiated by the user as well as learn the aspects from digital images output as part of the conversation. Once generated, the user profile is then usable by the artificial assistant system to assist in subsequent searches.

Artificial assistant system notification techniques are described that overcome the challenges of conventional search techniques. In one example, a user profile is generated to describe aspects of products or services learned through natural language conversations between a user and an artificial assistant system. These aspects may include price as well as non-price aspects such as color, texture, material, and so forth. To learn the aspects, the artificial assistant system may leverage spoken utterances and text initiated by the user as well as learn the aspects from digital images output as part of the conversation. Once generated, the user profile is then usable by the artificial assistant system to assist in subsequent searches.

An information processing device according to embodiments includes a reception unit that receives sensor data related to a user's action, a storage unit that stores a condition indicated by a threshold based on a psychological burden for information that is associated with the user's action and is to be presented to the user and for presentation of the information associated with the action related to the user or a threshold indicated by a psychological burden function, and a determination unit that determines content and a presentation timing of the information that is associated with the action indicated by the sensor data and is to be presented to the user from information stored in the storage unit when the action indicated by the sensor data received by the reception unit satisfies the condition related to the user and stored in the storage unit.

An information processing device according to embodiments includes a reception unit that receives sensor data related to a user's action, a storage unit that stores a condition indicated by a threshold based on a psychological burden for information that is associated with the user's action and is to be presented to the user and for presentation of the information associated with the action related to the user or a threshold indicated by a psychological burden function, and a determination unit that determines content and a presentation timing of the information that is associated with the action indicated by the sensor data and is to be presented to the user from information stored in the storage unit when the action indicated by the sensor data received by the reception unit satisfies the condition related to the user and stored in the storage unit.

A multi-tenant computer system implements a platform for providing data protection scopes to shared infrastructure services according to a nested tenant model that permits a hierarchy having a plurality of levels. The multi-tenant computer system provisions data protection scopes for cloud products, service products, cloud product tenants, service products operating in the context of cloud products, service products operating in the context of cloud product tenants, and combinations of the foregoing.

A multi-tenant computer system implements a platform for providing data protection scopes to shared infrastructure services according to a nested tenant model that permits a hierarchy having a plurality of levels. The multi-tenant computer system provisions data protection scopes for cloud products, service products, cloud product tenants, service products operating in the context of cloud products, service products operating in the context of cloud product tenants, and combinations of the foregoing.

The present teaching relates to method, system, medium, and implementations for storage management. A hash table is constructed, having an index file having one or more slots, each of which includes one or more buckets. Each bucket stores one or more types of records, including a direct record, an indirect record, and a forwarding record. A direct record stores data directly in a bucket of a slot of the index file. When a storage request is received related to some relevant data, the request is handled based on the constructed hash table.

The present teaching relates to method, system, medium, and implementations for storage management. A hash table is constructed, having an index file having one or more slots, each of which includes one or more buckets. Each bucket stores one or more types of records, including a direct record, an indirect record, and a forwarding record. A direct record stores data directly in a bucket of a slot of the index file. When a storage request is received related to some relevant data, the request is handled based on the constructed hash table.

A method, computer system, and a computer program product for modifying a user interface. Attributes of a source object identified by a user in connection with a user input for storing the source object are determined. Attributes of one or more target storage locations are determined. A target storage location for storing the source object is predicted, along with a confidence value associated with the prediction. The prediction is made using a machine learning model that predicts the predicted target storage location and associated confidence value based on the determined attributes of the source object. A plurality of target storage location usage patterns are determined. The user interface is modified based on the predicted target storage location.