SPATIAL STRUCTURE ANALYSIS AND REGENERATION DECISION-MAKING METHOD FOR RESIDENTIAL HISTORIC AREA

    公开(公告)号:US20240354459A1

    公开(公告)日:2024-10-24

    申请号:US18702812

    申请日:2023-11-20

    IPC分类号: G06F30/13

    CPC分类号: G06F30/13

    摘要: The method includes the following steps: first establishing urban street and urban plot elements, delineating publicly used parts of public and private property areas as streets, and delineating boundaries of privately owned land as plots; after defining urban streets and urban plots, obtaining accessibility levels of the street elements through depth, connectivity, and low connection rate, where the accessibility level of an urban plot includes an external value and an internal value, the external value is obtained through the levels of urban streets connected to the plot, and the internal value is obtained through the delineation of interlocking structure, basic structure, cul-de-sac structure, and embedding structure types of the urban plot and the urban streets; and based on calculation results of the accessibility levels of the urban streets and urban plots, making judgments from four aspects: upper level planning, commercial system, community system, and historic resources.

    Information security-oriented reconfigurable system chip compiler and automatic compilation method

    公开(公告)号:US12124593B2

    公开(公告)日:2024-10-22

    申请号:US17992132

    申请日:2022-11-22

    IPC分类号: G06F21/60 G06F8/41 G06F9/445

    CPC分类号: G06F21/602

    摘要: The present disclosure discloses an information security application-oriented reconfigurable system chip compiler and an automatic compilation method. The method includes the following steps: firstly, inputting a source program of a cryptographic algorithm; then, executing a software compilation function syntax check of the source program, and when the check result is passed, performing compilation mapping using a compiler; next, executing the cryptographic algorithm by simulation running using a simulator, and generating a configuration code by a simulator array; and finally, guiding a hardware behavior operation using a binary configuration code file generated by the simulator. The reconfigurable system chip compiler includes a source program input module, a software compilation function verification module, a compilation mapping module, a simulation execution module, a configuration code generation module, and a hardware debugging module.

    Foldable rail-mounted crane stop device

    公开(公告)号:US12110216B2

    公开(公告)日:2024-10-08

    申请号:US17368801

    申请日:2021-07-06

    IPC分类号: B66C9/18 B61K7/04 B66C7/16

    CPC分类号: B66C9/18 B61K7/04 B66C7/16

    摘要: A foldable rail-mounted crane stop device includes an actuating device, a slidably fixing device and a braking device. The actuating device is mounted on a crane rail for bearing the pressure of a crane wheel and thereby actuating the braking device, the slidably fixing device is mounted at an end of the crane rail, and the braking device is connected with the slidably fixing device for braking the crane wheel. The device provided by the present invention is used for crane braking at the end of a rail.

    MICROGRID SPATIAL-TEMPORAL PERCEPTION ENERGY MANAGEMENT METHOD BASED ON SAFE DEEP REINFORCEMENT LEARNING

    公开(公告)号:US20240330396A1

    公开(公告)日:2024-10-03

    申请号:US18550287

    申请日:2023-03-14

    IPC分类号: G06F17/11

    CPC分类号: G06F17/11

    摘要: A microgrid spatial-temporal perception energy management method based on safe deep reinforcement learning includes: transforming an energy management problem of a microgrid (MG) into a constrained Markov decision process (CMDP), where an agent is an energy management agent of the MG; and solving the CMDP by using a safe deep reinforcement learning method, including: 1) building a feature extraction network combining an edge conditioned convolutional (ECC) network and a long short-term memory (LSTM) network to extract spatial and temporal features in a spatial-temporal operating status of the MG; and 2) endowing the agent with abilities to learn policy value and security simultaneously by using an interior-point policy optimization (IPO) algorithm. The microgrid spatial-temporal perception energy management method based on safe deep reinforcement learning enhances perception on the spatial-temporal operating status of the MG, safeguards the secure operation of the distribution network, and achieves superior energy management policy cost efficiency.

    COMBINED STRUCTURE FOR THIN FILM SPUTTERING HIGH-PRECISION SIX-DIMENSIONAL FORCE SENSOR

    公开(公告)号:US20240328873A1

    公开(公告)日:2024-10-03

    申请号:US18655303

    申请日:2024-05-05

    IPC分类号: G01L1/22

    摘要: A combined structure for thin film sputtering high-precision six-dimensional force sensor includes a cross beam, a double U-shaped beam, a base, a top cover, a bottom cover and thin film strain gauges. Strain gauges are sputtered on the main beam to form six sets of Wheatstone bridges, with three sets on the cross beam and three sets on the double U-shaped beam. The measurement method of the six-dimensional force sensor is that: an input force/moment of a certain dimension acts on the center of the cross beam and the center of the double U-shaped beam, so that the sensor is deformed and resistance values of strain gauges at corresponding positions change, thereby changing output voltages of corresponding bridges.

    Place recognition method based on knowledge graph inference

    公开(公告)号:US12099806B2

    公开(公告)日:2024-09-24

    申请号:US17701137

    申请日:2022-03-22

    摘要: The present disclosure discloses a place recognition method based on knowledge graph inference; and provides, on the basis of giving a knowledge graph construction method in the place field, a recognition method of general places that is based on knowledge graph inference and can integrate various heterogeneous environmental information, including the following steps: (1) extracting main clues such as the main items that make up the place, the produced events, and the spatial structure from various heterogeneous information, and describing these clues in natural language text; (2) screening the foregoing descriptions by using natural language processing methods, to form place description entities; (3) constructing a knowledge graph in the place field according to the occurrence frequencies of the description entities in an actual environment; and (4) implementing inference and classification based on the knowledge graph by using a Deep Neural Network (DNN), to give a final recognition result. The present disclosure improves the place recognition accuracy by means of knowledge graph inference, and greatly improves semantic interpretability in the place recognition process.