Abstract: A storage and display assembly for a shaving razor system. The assembly has a case with a top portion coupled to a bottom portion. The case is made from one or more metals. An insert is received in the bottom portion of the case. The insert has one or more cavities configured to receive one or more components of the shaving razor system. A hang tag is coupled to the case. A securement cover is associated with the case. The securement cover includes at least one of product indicia or product imagery. The top portion of the case has one or more first gripping features, and the bottom portion of the case has one or more second gripping features. The first and second gripping features are configured to assist with separating the top portion from the bottom portion.

Abstract: A storage and display assembly for a shaving razor system. The assembly comprising has a case with a top portion and a bottom portion. The top and bottom portions being coupled together so as to be movable relative to one another between a closed position and an open position. The top and bottom portions, when in the closed position, define an inner cavity sized to receive the shaving razor system. A securement cover associated with the top and bottom portions to maintain the top and bottom portions in the to be moved to the open position. The securement cover comprises at least one of product indicia closed position. The securement cover being removable from the case to allow the top and bottom portions or product imagery.

Abstract: A system includes a virtual reality system configured to enable a user to interact with a virtual environment, a plurality of biofeedback sensors configured to monitor a user, and a computer system including a virtual reality module configured to generate at least a view of the virtual environment, a biofeedback module configured to fuse output of the plurality of biofeedback sensors with a plurality of events within the virtual environment, a training module configured to generate a model of user behavior, wherein the training module executed by the computer system enables the computer system to make a prediction of a user response of the user based on a corpus of biofeedback data, and an alert module configured to generate at least one alert to the user via the virtual reality system based on the user response predicted by the computer system.

Abstract: A storage and display assembly with a base defining a cavity configured to receive a product. A lid is mounted to the base covering the cavity. A hang tag is mounted to the base. The hang tag has a first position with a first end of the hang tag engaging an inner surface of the lid securing the lid to the base and a second position with the first end of the hang tag is disengaged from the inner surface of the lid.

Abstract: Whether to train a new neural network model can be determined based on similarity estimates between a sample data set and a plurality of source data sets associated with a plurality of prior-trained neural network models. A cluster among the plurality of prior-trained neural network models can be determined. A set of training data based on the cluster can be determined. The new neural network model can be trained based on the set of training data.

Abstract: Techniques that facilitate layered stochastics anonymization of data are provided. In one example, a system includes a machine learning component and an evaluation component. The machine learning component performs a machine learning process for first data associated with one or more features to generate second data indicative of one or more example datasets within a degree of similarity to the first data. The first data and the second data comprise a corresponding data format. The evaluation component evaluates the second data for a particular feature from the one or more features and generates third data indicative of a confidence score for the second data.

Abstract: A system and a method of managing a manufacturing process includes receiving production data relating to the manufacturing process and determining an operational mode associated with the manufacturing process using historical, multivariate senor data. The method may further determine a recommended action to affect production based on the determined operational mode. The operational mode may be based on at least one of: a level of operation in a continuous flow process relating to a joint set of process variables, a representation of a joint dynamic of the set of process variables over a predefined length, and a joint configuration of an uptime/downtime of a plurality of units comprising a process flow.