Abstract: Systems and methods for identifying and evicting idle sessions include training a machine learning model as a session classifying model to learn rules for classifying active sessions between clients and the cloud-based service. The session classifying model is trained to receive a plurality of parameters pertaining to the document associated with an active session as input and to apply the rules to the plurality of parameters to determine a classification for the active session and to provide an output indicative of the classification for the active session. The session classifying model is then utilized in the cloud-based service to classify the active sessions. The active sessions classified as idle sessions may then be evicted from the cloud-based service.

Abstract: The present disclosure discloses a laser detection method for port machinery equipment including: providing with a laser radar device: selecting a suitable laser radar device and installing on the port machinery, ensuring that an installation position and angle of the device can provide a good detection range and field of view; emitting and receiving laser: emitting a laser beam and receiving reflected light signals by the laser radar device, emitting a pulsed laser beam by the laser radar device, forming a narrow beam of laser by focusing with an optical component. The laser detection method uses a Velodyne® VLP-32C infrared laser, which has high resolution and a large number of detection points, can provide high-precision laser data to more accurately describe a port environment and target objects. Through a PointNet++deep learning mode, global perception and analysis of laser data can be carried out to obtain target object information.