Abstract: A method, computer program product and system are provided for preloading debug information based on the presence of incremental source code files. Based on parsed input parameters to a source code debugger, a source code repository and a local storage area are searched for an incremental file. In response to the incremental file being located, a preload indicator in the incremental file, which is a source code file, is set. Based on the preload indicator being set, debug symbol data from the incremental file is merged to a preload symbol list. In response to receiving a command to examine the debug symbol data from the incremental file, the preload symbol list is searched for the requested debug symbol data.

Abstract: A method for making a spatio-temporal combined optimal scheduling strategy of a mobile energy storage (MES) system includes: inputting data of a power system, a traffic system, and an MES system; setting a time interval, and initializing a time interval counter; inputting real-time fault, traffic, and MES data; and performing rolling optimization and solving, and delivering regulation decision instructions of the MES system, till a fault is removed. The core of the present disclosure is to propose a spatio-temporal combined optimal model of the MES system to describe spatio-temporal coupling statuses of an energy storage vehicle, a traffic network, and a power distribution network. The present disclosure provides guidance for an optimal scheduling decision of the MES system by properly regulating a traveling path and charging and discharging power of the MES system, thereby supporting high-reliability operation of the power distribution network.

Abstract: A virtual machine management method and apparatus, a device, and a readable storage medium. The virtual machine management method is applied to a private cloud, and comprises: acquiring a SELinux label, the SELinux label comprising five elements: User, Role, Type, Sensitivity, and Category (S101); setting elements other than Category in the SELinux label as default values (S102); assigning different values to Category according to a preset Category variable combination so as to obtain multiple non-duplicate label groups (S103); and configuring each label group to a virtual machine in the private cloud, so that virtual machines configured with the same label group communicate with each other, and virtual machines configured with different label groups are isolated from each other (S104).

Abstract: Methods, systems, and processor-readable media for adaptive cycle-level traffic signal control are described. An adaptive cycle-level traffic signal controller and control method that operate within a continuous action space. A reinforcement learning algorithm called Proximal Policy Optimization (PPO), which is a type of actor-critic model for reinforcement learning, may be used to generate signal cycle phase durations selected from a continuous range of values. The controller thus does not treat the action space as discrete, but instead produces continuous values as output. The generated phase durations may define a full traffic signal cycle. The inputs to the controller may indicate current and past states of the traffic environment. The average duration of delay of vehicles in the traffic environment may be used to calculate the reward for the reinforcement learning model that drives the behavior of the controller.

Abstract: Methods, systems, and processor-readable media for adaptive cycle-level traffic signal control are described. An adaptive cycle-level traffic signal controller and control method that operate within a continuous action space. A reinforcement learning algorithm called Proximal Policy Optimization (PPO), which is a type of actor-critic model for reinforcement learning, may be used to generate signal cycle phase durations selected from a continuous range of values. The controller thus does not treat the action space as discrete, but instead produces continuous values as output. The generated phase durations may define a full traffic signal cycle. The inputs to the controller may indicate current and past states of the traffic environment. The average duration of delay of vehicles in the traffic environment may be used to calculate the reward for the reinforcement learning model that drives the behavior of the controller.

Abstract: Techniques for sorting search results using user characteristic data are described. These techniques may include receiving a query from a user device. A search may be performed based on the query to obtain multiple results. User responses corresponding to the multiple results may be obtained and then grouped to determine multiple users based on similarities among the multiple users. Based on user responses associated with the multiple users, the multiple results may then be ranked.

Abstract: The present disclosure describes an information matching method and information system.

Abstract: The present disclosure describes an information matching method and information system.