Abstract: A self-heterodyne phase-sensitive optical time domain reflectometry (?-OTDR) system with a free multi-spatial resolution includes a narrow linewidth laser source, a 1×3 fiber-optic coupler, three acousto-optic modulators (AGMs), a 3×1 fiber-optic coupler, two time-delay fibers, an erbium-doped fiber amplifier (EDFA), a circulator, a photodetector, an electrical amplifier, three filters, a data acquisition card, a pulse signal generator, and a driver module. A plurality of acousto-optic modulators using the same driver are used to couple probe light with different pulse intervals and different frequency shifts and then inject the probe light into a fiber, such that a self-heterodyne detection structure with a multi-spatial resolution is implemented, which suppressed optical background noise such as coherent fading noise, phase noise introduced by a frequency drift of a light source, and pseudo-random noise (PRN).

Abstract: Disclosed are a drive-by-wire chassis cyber-physical system under an intelligent traffic environment and a control method. The system includes: an SoS-level CPS, a system-level CPS, and a unit-level CPS, data transmission is realized between a plurality of unit-level CPSs and one system-level CPS, and data transmission is realized between a plurality of system-level CPSs and one SoS-level CPS. The system integrates a hub motor with a suspension, cancels traditional structures such as an engine and a clutch, and simplifies the structure of a chassis. A motor directly drives a vehicle to run, and different driving, braking or torque is applied to different wheels through four hub motors, so as to meet independent control of the wheels and improve active safety and operational stability.

Abstract: A networked control method for primary frequency regulation of a new energy power station based on a source-grid-load-storage networked cloud decision control system platform comprises: determining, according to historical operating data of a new energy power station, primary frequency regulation predictive values of power generation units of the new energy power station; determining, according to the primary frequency regulation predictive values, optimal control sequences of inverters of the power generation units at different times based on a pre-established inverter active power model, wherein the optimal control sequences comprise multiple control quantities of active power of the inverters; marking the optimal control sequences at the different times with time scales, sending the optimal control sequences to executing devices of the power generation units, receiving the optimal control sequences, and determining whether to store or not store the optimal control sequences; and determining the control qua

Abstract: A multi-view outlier detection algorithm based on the tensor representation is provided. Specifically, the multi-view data are firstly transformed into a set of tensors, and then its low-rank representation is learned. Finally, an outlier function is designed in the case of tensor representation to realize detection.

Abstract: The present disclosure relates to a method and system for detecting a structural defect in additive manufacturing. The method includes: layering a three-dimensional model of an additive manufacturing test piece to obtain a two-dimensional contour of an interface of each layer, and generating a machining path; arranging a non-contact sensor at a fixed measuring point of the additive manufacturing test piece, and acquiring an ultrasonic signal at each machining point when a pulse laser conducts machining point by point along the machining path; forming a visual ultrasonic field based on all the ultrasonic signals, and determining ultrasonic field data; determining, based on the ultrasonic field data, a curve of a peak of an incident wave changing with the machining path; and determining whether a machining defect exists at the machining points based on the curve of the peak of the incident wave changing with the machining path.

Abstract: An interrupt-driven system verification method based on interrupt sequence diagrams includes the steps of: establishing an interrupt-driven system model based on an interrupt sequence diagram, dividing interaction fragments in the obtained interrupt sequence diagram into basic interaction fragments and composite interaction fragments and sequentially converting the basic interaction fragments and the composite interaction fragments into the corresponding automaton models, combining the automaton models into one automaton model, adding the constraints in the interrupt sequence diagram to the converted automaton model, adding the verification attribute information as a constraint to the converted automaton model, describing an automaton as an input format acceptable to the automaton verification tool, and verifying the model with the automaton verification tool.

Abstract: This invention proposes a single-vector-based finite control set model predictive control for two parallel power converters, which adopts a centralized control structure to achieve accurate control of overall performance. It establishes predictive models for line currents and three phase-circulating currents and constructs a novel cost function that uses these currents as performance indices to implement the predictive control algorithm based on the proposed predictive models. The invention proposes dynamic weighting coefficients and adjustment principles to improve system control performance. A finite set output signal matrix containing important characteristic information of all alternative vectors is constructed to avoid redundant calculations in each control horizon, reducing computation time during practical implementation.

Abstract: The disclosure provides a method for detecting and defending a Distributed Denial of Service attack in an SDN environment. The method includes: building data messages acquired as feature messages by a proxy module; sending the feature messages to a pre-built detection model to obtain a detection result; making a decision instruction based on the detection result; and performing control operations by the proxy module based on the decision instruction.

Abstract: The present disclosure discloses an image segmentation method combined with superpixel and multi-scale hierarchical feature recognition. This method is based on a convolutional neural network model taking multi-scale hierarchical features extracted from a Gaussian pyramid of an image as a recognition basis, and then being connected with a multilayer perceptron to achieve the recognition of each pixel in the image, moreover, this method is used tier performing superpixel segmentation on the image and is combined with a method for improving superpxiel in combination with LBP texture features to segment an original image so that an obtained superpixel block is more fitted to edges of targets, then, the original image is merged according to a mean value of a color, and finally, recognition of each target in the image is achieved.

Abstract: A method for preparing a negative pressure film-covering frozen sand mold includes: directly obtaining a mold cavity of a sand mold through numerically controlled machining of a frozen sand blank; covering a surface, brushed with a thermal insulation coating, of the mold cavity of the sand mold with a softened thin film, and covering an outer surface of the sand mold with a back film to seal a sand box; fixing the frozen sand mold in an air extraction sand box with a vacuum chamber, and extracting air through a vacuum pump, so that the thin film tightly adheres to the sand mold through vacuum suction force; and closing the box to obtain an integral sand mold, and pouring a casting at room temperature or low temperature under negative pressure. The method is environment-friendly, and the prepared frozen sand mold has high strength and is convenient for sand cleaning.

Abstract: A global active noise control method for a rotorcraft, including: acquiring the acoustic pressure signal at a measuring point of the rotorcraft; predicting the holographic and global sound field of noise of the rotor; reconstructing the reverse sound field of the noise of the rotor; and performing adaptive sound field adjustment based on the optimal phase search.

Abstract: A method for assessing microbial drug resistance multi-level risks of antibiotic residues in water environments, belonging to the technical field of water environment assessment, comprises the following steps: S1, environment monitoring; S2, preliminary screening of antibiotics: S2-1, determination of n-octanol/water partition coefficient, and S2-2, determination of antibiotic environment concentration; S3, assessment of microbial drug resistance; and S4, high-level assessment. The assessment method of the present disclosure conducts a step-by-step assessment of target antibiotics or target antibiotic derivatives in water environment with risks.

Abstract: The present disclosure discloses a multi-task joint computing unloading and resource allocation method based on D2D (Device-to-Device) communication. For solving the problems that computing resources of a local terminal cannot complete all computing tasks on time when there are multiple computing tasks with delay requirements on a local terminal, the method introduces a computing unloading mechanism to reduce the delay and the overhead of the local terminal itself. The method is based on a D2D communication technology. In the scenario where mobile terminals are densely distributed, the local terminal can unload the computing tasks at the same time to several surrounding idle terminals for processing. According to the method, a total overhead objective function is established in consideration of the task delay, energy consumption, and unloading fee.

Abstract: The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into t

Abstract: A method for selecting a content forwarding node in a vehicle ad-hoc network on the basis of service type, comprising the following steps: calculating a bandwidth occupation proportion factor according to the type of requested content information and a bandwidth occupation situation of a neighboring vehicle which can perform forwarding in a one-hop transmission range; defining a virtual arrival time of a candidate forwarding vehicle to an initial request vehicle according to the distance between the neighboring vehicle and the initial request vehicle and a driving speed of the neighboring vehicle; calculating a forwarding node impact factor according to the bandwidth occupation proportion factor and the virtual arrival time; and selecting a forwarding node according to the forwarding node impact factor.

Abstract: A semantic segmentation method for aircraft point cloud based on voxelization and three views, including: filtering a collected point cloud followed by centralization to obtain a centralized point cloud; inputting the centralized point cloud into a T-Net rotation matrix network; rotating the centralized point cloud to a front side followed by voxelization to obtain a voxelized point cloud; subjecting the voxelized point cloud to voxel filling to obtain a voxel-filled point cloud; calculating thickness maps of three views of the voxel-filled point cloud, followed by sequentially stitching and inputting to the point cloud semantic segmentation network to train the point cloud semantic segmentation network; inputting the collected point cloud into the trained point cloud semantic segmentation network; and predicting a result semantic segmentation of a 3D point cloud of the aircraft.

Abstract: A method for preparing an electrochemiluminescent nanoprobe according to an embodiment includes: adding a metal complex ion to an inorganic oxide nanoparticle to provide a metal-doped inorganic oxide nanoparticle; and binding a secondary antibody to the metal-doped inorganic oxide nanoparticle to provide a metal-doped inorganic oxide nanoparticle modified with the secondary antibody. The secondary antibody is configured to identify a specific antibody against nucleic acid-specific site modification.

Abstract: A multi-timescale voltage regulation method based on source-grid-load-storage multi-terminal collaboration of a power distribution network is disclosed, which comprises: establishing, based on a Petri network, a multi-mode switching control model based on voltage security event trigger to realize effective control of a global voltage; establishing multi-objective optimization taking into account a source-storage-load regulation cost and a network transmission loss to realize collaborative and dynamic control of controllable resources of a source terminal, a load terminal and a storage terminal in each operating mode; and establishing a source-storage-load multi-terminal collaboration-based distributed voltage control model based on voltage security event trigger over a short timescale by taking into account the problems of voltage magnitude being out of limit and voltage leap, and solving online an optimal control sequence of the source terminal, the load terminal and the storage terminal in a receding horizo

Abstract: A three-dimensional (3D) spectrum situation completion method and device based on a generative adversarial network includes performing graying and coloring preprocessing based on incomplete 3D spectrum situations from historical or empirical spectrum data obtained by a UAV through sampling a target region, obtaining three-channel incomplete 3D spectrum situation maps displayed in colors, forming a training set based on the incomplete 3D spectrum situation maps; training the generative adversarial network based on the training set and obtaining a trained generator network in the generative adversarial network, performing graying and coloring preprocessing based on a measured incomplete 3D spectrum situation obtained by the UAV through sampling a specified measurement region, obtaining a three-channel measured incomplete 3D spectrum situation map displayed in colors, and using the measured incomplete 3D spectrum situation map as input data to the generator network to obtain a three-channel measured complete 3D

Abstract: This application discloses a semantic learning-based down-sampling method of point cloud data of an aircraft, including: (S1) constructing a multi-input encoder based on feature learning according to point cloud semantic learning principle; inputting the point cloud data of the aircraft and feature point data into the multi-input encoder for feature fusion followed by decoding using a decoder the multi-input feature fused data to obtain to-be-measured data; (S2) constructing and training a point cloud feature weight calculation network based on semantic learning to acquire a feature weight of each point in the to-be-measured data; and (S3) performing spatial weighted sampling on the feature weight of each point in the to-be-measured data followed by down-sampling based on Gaussian distribution-based spatial sampling principle.