Abstract: The invention provides an AC/DC conversion device for intelligent green-power operation and maintenance in power transmission and transformation projects, including a cabinet, an assembling panel, an inverter, a driving mechanism and a controller. A door is mounted at the front portion of the cabinet in a fixed and sealed manner, and the assembling panel is fixedly mounted on the back wall of the cabinet inside the cabinet. The assembling panel, the inverter, the driving mechanism and the controller are all provided inside the cabinet, which provides desirable dust-proof effects, preventing the case where the inverter, the driving mechanism and the controller are interfered by the dust, so that this device is suitable for outdoor usage. The driving mechanism and the controller work in coordination, so that the inverter can be switched off in time when it burns out and smokes, thereby substantially reducing the risk of fire hazards.

Abstract: The invention provides an AC/DC conversion device for intelligent green-power operation and maintenance in power transmission and transformation projects, including a cabinet, an assembling panel, an inverter, a driving mechanism and a controller. A door is mounted at the front portion of the cabinet in a fixed and sealed manner, and the assembling panel is fixedly mounted on the back wall of the cabinet inside the cabinet. The assembling panel, the inverter, the driving mechanism and the controller are all provided inside the cabinet, which provides desirable dust-proof effects, preventing the case where the inverter, the driving mechanism and the controller are interfered by the dust, so that this device is suitable for outdoor usage. The driving mechanism and the controller work in coordination, so that the inverter can be switched off in time when it burns out and smokes, thereby substantially reducing the risk of fire hazards.

Abstract: A method for controlling peak saving by wind power grid. The method includes: S1: evaluating dispatchability of a cluster virtual wind power unit; S2: developing a method for calculating a dispatchability index of the cluster virtual wind power unit; S3: analyzing a source-load peak-shaving resource strategy; and S4: distributing a control strategy for tie-line peak shaving. The present disclosure has the following beneficial effects: In the present disclosure, real-time dispatchability of wind power participating in real-time power balance is first analyzed, specific evaluation indexes and calculation methods are provided, and calculation examples are given for verification. Then, an optimized real-time dispatch strategy is provided based on demand-side response resources, and DC and AC tie-lines are coordinated for operation. The peak shaving control method for emergent source-grid coordination when a sending-end power grid is faulty can ensure normal operation.

Abstract: An Activation Map Analysis (AMA) system attaches to an existing deep neural network (host network) as an observer that analyzes the internal activities of the host network to provide additional information, e.g., metrics for resilience, interpretability, and adversarial defense, to the end-user. The AMA system is developed using deep k-nearest neighbor (DkNN) coupled with principal component analysis (PCA) for data dimensionality reduction or Hyperdimensional Computing (HDC) to encode activation map data of the host for data reduction.

Abstract: A system of modular components can be used with existing sensor suites to fuse data and determine the operating environment (surface contacts/tracks) for an autonomous marine vehicle and feed an autonomy decision engine to improve the vessel arbitration process in deciding which way to turn, how fast to go, obstacle avoidance, and mission monitoring. The system includes the ability to obey the set of navigation rules published by the International Maritime Organization, generally referred to as COLREGS (collision regulations).

Abstract: A system of modular components can be used with existing sensor suites to fuse data and determine the operating environment (surface contacts/tracks) for an autonomous marine vehicle and feed an autonomy decision engine to improve the vessel arbitration process in deciding which way to turn, how fast to go, obstacle avoidance, and mission monitoring. The system includes the ability to obey the set of navigation rules published by the International Maritime Organization, generally referred to as COLREGS (collision regulations).

Abstract: A system of modular components can be used with existing sensor suites to fuse data and determine the operating environment (surface contacts/tracks) for an autonomous marine vehicle and feed an autonomy decision engine to improve the vessel arbitration process in deciding which way to turn, how fast to go, obstacle avoidance, and mission monitoring. The system includes the ability to obey the set of navigation rules published by the International Maritime Organization, generally referred to as COLREGS (collision regulations).

Abstract: Seismic pattern recognition using an attributed relational graph matching-based fingerprint classification and identification method for identifying features of possible hydrocarbons significance in a seismic data volume (10). The seismic data are reduced to line representations (11), which are represented in a graph structure (12), having edges and vertices. Various attributes such as polarity are associated (14) with the edges and vertices, thereby creating an attributed relational graph, which is then searched for matches (16) with a selected pattern (15) considered to have hydrocarbon significance (18).

Abstract: The present invention relates to systems and methods for characterizing targets, e.g., trucks, pallets, trains, cars, and the like, using digital target imaging. Accordingly, embodiments of the present invention provide, at base: a) image segmentation and filtering to identify surrounding white space, interior walls, floor, and ceiling of the container; morphology routines to identify and classify objects found inside the container; and decision routines to report status of container as empty or non-empty with a confidence factor from 1-100.