Abstract: A plate making system includes a writing device, an exposure device, a developing device, a plate cutting device, a first transfer device, a second transfer device and a third transfer device in an integrated manner. The plate making system also includes a control device that controls a series of plate making processes for a flexographic printing original plate performed by the writing device, the exposure device, the developing device and the plate cutting device.

Abstract: A plate making system comprises a writing device, an exposure device, a developing device, a plate cutting device, a first transfer device, a second transfer device and a third transfer device in an integrated manner. The plate making system also comprises a control device that controls a series of plate making processes for a flexographic printing original plate performed by the writing device, the exposure device, the developing device and the plate cutting device.

Abstract: A plate making system comprises a writing device, an exposure device, a developing device, a plate cutting device, a first transfer device, a second transfer device and a third transfer device in an integrated manner. The plate making system also comprises a control device that controls a series of plate making processes for a flexographic printing original plate performed by the writing device, the exposure device, the developing device and the plate cutting device.

Abstract: A service system provides users with access to online services. As part of providing the services to users, the service system stores data for users in a data storage system. When the service system receives a request from an administrator of the system for user data stored in the data storage system, the service system identifies the data requested by the administrator. The service system also determines policies that apply to the data. The determined policies indicate transformations that are to be performed on the data to protect the privacy of the users. The service system transforms the user data as indicated by the policies and provides the transformed user data to the administrator.

Abstract: A user provides a description of a neural network to a visualization tool. The visualization tool displays a user interface that includes a visual of the neural network based on the description. If the user interacts with a node or connection, for example by placing a cursor on the node/connection in the user interface, the user interface displays information associated with the node/connection. If the user selects a node of a layer, the neural network is applied to an input that corresponds to the selection and the user interface displays the propagation of the input through the neural network. Additionally, the user interface displays results from applying the neural network to the input.

Abstract: A service system provides users with access to online services. As part of providing the services to users, the service system stores data for users in a data storage system. When the service system receives a request from an administrator of the system for user data stored in the data storage system, the service system identifies the data requested by the administrator. The service system also determines policies that apply to the data. The determined policies indicate transformations that are to be performed on the data to protect the privacy of the users. The service system transforms the user data as indicated by the policies and provides the transformed user data to the administrator.

Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses machine learning techniques to predict likelihood of success for a potential transaction object. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data as training dataset for a predictor model. The online system extracts features describing potential transaction objects and provides these as input to the predictor model for predicting the likelihood of success of a given potential transaction. The online system may use predictions of likelihood of success of potential transactions to identify a set of potential transactions that should be acted upon to maximize the benefit the enterprise within a time interval, for example, by the end of the current month.

Abstract: A user provides a description of a neural network to a visualization tool. The visualization tool displays a user interface that includes a visual of the neural network based on the description. If the user interacts with a node or connection, for example by placing a cursor on the node/connection in the user interface, the user interface displays information associated with the node/connection. If the user selects a node of a layer, the neural network is applied to an input that corresponds to the selection and the user interface displays the propagation of the input through the neural network. Additionally, the user interface displays results from applying the neural network to the input.