97results about How to "Improve build quality" patented technology

The invention discloses a three-dimensional model construction method and device, a storage medium and computer equipment, and relates to the technical field of financial science and technology and the technical field of digital medical treatment. Comprising the following steps: acquiring a two-dimensional image, and dividing the two-dimensional image into a plurality of panes; predicting a local approximate plane normal in a view angle range corresponding to each pane, determining a three-dimensional modeling starting point, determining a three-dimensional coordinate of the three-dimensional modeling starting point, taking the pane where the three-dimensional modeling starting point is located as a starting point pane, and taking the three-dimensional coordinate of the three-dimensional modeling starting point as a starting point center coordinate of a starting point local approximate plane corresponding to the starting point pane; determining a neighborhood pane adjacent to the starting point pane, and determining a neighborhood center coordinate of a neighborhood local approximate plane corresponding to the neighborhood pane based on the starting point center coordinate, a local approximate plane normal of the starting point pane and a local approximate plane normal of the neighborhood pane; and based on the starting point center coordinate and the neighborhood center coordinate, splicing the starting point local approximate plane and the neighborhood local approximate plane to obtain a three-dimensional model.

This invention relates to a method and system for automated generation of TSN network configurations based on a reflective agent. The system comprises a network state perception and intent reflection module, a YANG model configuration parameter and structure decision module, and a YANG model intelligent generation module. The network state perception and intent reflection module is responsible for structurally perceiving network state and resource information. The YANG model configuration parameter and structure decision module integrates multi-source knowledge and contextual information, intelligently generating deployable TSN scheduling parameters and YANG configuration structures based on business needs. The YANG model intelligent generation module automatically generates the corresponding YANG configuration model based on the optimized results, performs syntax and semantic verification, and then distributes it to the target device, achieving automated deployment of network configurations. This invention significantly improves the intelligence level and deployment automation capability of TSN network configuration by introducing reflective reasoning and feedback optimization techniques.

This invention relates to the field of decorative engineering technology, and discloses a method and system for generating virtual renderings of decorative engineering projects. The method includes: S1, parsing CAD drawings; S2, identifying professional intent; S3, defining and configuring key aesthetic elements; S4, attributing and correcting model parameters; S5, conflict detection; S6, adaptive fusion and correction; S7, material mapping and lighting calculation; and S8, outputting the virtual rendering. This invention solves the problem that the complexity of CAD drawings leads to incomplete or inaccurate geometric structures in 3D models, which in turn affects material mapping and lighting calculation, thus impacting the visual realism of virtual renderings.

This invention discloses a method for generating poses of articulated objects based on physical perception and graph diffusion, relating to the field of computer vision. The method first reconstructs the componentized geometric and physical properties of objects from images using a bi-branch neural implicit network and initializes component connectivity relationships. Subsequently, it refines the component relationship graph through kinematic fitting and temporal consistency checks, and uses a physically enhanced graph diffusion process to infer the prior pose distribution of components on an SE(3) manifold. Finally, using this prior and reconstructed information as conditions, a conditional diffusion model is constructed on the SE(3) manifold, and backsampling is performed through a physically guided two-step backsampling framework to generate a diverse and physically plausible set of pose assumptions for articulated objects. This invention achieves efficient generation of diverse and highly physically plausible poses of articulated objects by tightly coupling physical laws with data-driven generation.

This invention relates to the field of artificial intelligence technology, and particularly to an automated fuzzy appeal processing method and system based on multi-agent intelligence. This automated fuzzy appeal processing method based on multi-agent intelligence obtains the probability distribution of fuzzy information in a user's appeal through a preset size model recognition strategy; determines the information entropy of multiple words in the user's appeal based on the fuzzy information probability distribution, and identifies target fuzzy information sites by identifying words whose information entropy exceeds a preset information entropy threshold and their corresponding positions in the user's appeal; executes a disambiguation strategy on the target fuzzy information sites, and performs long-span coarse-grained task planning for the disambiguated user based on multi-agent intelligence, forming a task heterogeneity graph; constructs task execution meta-paths based on the task heterogeneity graph, and processes user appeals according to the task execution meta-paths. This achieves automated fuzzy appeal processing from fuzzy information recognition, disambiguation, and post-disambiguation task planning to final execution, as well as accurate recognition of fuzzy information.

Embodiments of the present application disclose a risk behavior detection method, device and equipment, the method comprises: determining a first scene with a behavior correlation between the target scene is less than a preset correlation threshold, obtaining the first picture data containing the target behavior corresponding to the target scene, the target behavior annotation information corresponding to the target behavior in the first picture data, and the second picture data containing the first behavior corresponding to the first scene, based on the second picture data and the target behavior annotation information, the first sample data is constructed, based on the first picture data, the target behavior annotation information, and the first sample data, a preset visual language model is trained, and a trained visual language model is obtained, the trained visual language model is used for detecting whether a preset risk behavior exists in the video to be detected.

The invention relates to the technical field of image processing, and discloses a landslide surface crack three-dimensional evolution unmanned aerial vehicle image extraction and quantification method and system, and the method comprises the steps: carrying out the bundle adjustment of an ultrahigh overlapping degree aerial image of a landslide surface, and obtaining an image shooting position, an image attitude parameter and a sparse three-dimensional point cloud; constructing a high-precision digital earth surface model; performing digital mosaic on the aerial image with the ultrahigh overlapping degree to obtain an orthoimage; performing semantic segmentation on the orthoimage to obtain a crack binary segmentation map of the orthoimage so as to identify a main crack and a secondary crack; performing three-dimensional geometric parameter analysis on the main crack and the secondary crack to obtain a crack three-dimensional space attribute parameter; carrying out evolution trajectory tracking on the crack three-dimensional space attribute parameters to obtain evolution data so as to construct a visual map of the landslide surface; according to the invention, the efficiency of extracting and quantifying the three-dimensional evolution unmanned aerial vehicle image of the landslide surface crack can be improved.

The invention discloses a document generation method and device, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the following steps: obtaining a document theme which is used for indicating theme content of a to-be-generated first document; obtaining a plurality of sample documents and a plurality of data contents, wherein the plurality of sample documents meet preset document quality requirements; determining at least one sample document from the plurality of sample documents based on the document topic, and determining a first data content from the plurality of data contents based on the document topic; performing format conversion on the first data content to obtain first chart content; analyzing the first chart content through a first natural language model, and outputting to obtain a first text content for describing the first chart content; analyzing the document theme, the at least one sample document, the first chart content and the first text content through the second natural language model, and outputting to obtain a first document. The document generation efficiency and the document quality can be improved.

The application discloses a radar target recognition method and device with azimuth enhancement under physical scattering constraints. The core is that a feature level azimuth expansion module (FAEM) is constructed, sparse view angle features are augmented in a feature space, and effective expansion of azimuth information is realized; meanwhile, a scattering center reconstruction constraint module (SCRCM) is innovatively introduced, physical authenticity and semantic fidelity of generated features are improved; in addition, multi-view perception enhancement modules (MVFM) are used to fuse generated multi-azimuth features, and intra-class compactness constraints are applied to optimize feature space structures, and the recognition ability of the model is further improved. The method realizes optimization from feature generation, physical constraints to semantic enhancement, and effectively improves the target recognition performance under sparse view angles.

This invention relates to the technical field of programming task code generation methods based on multi-agent collaboration and iterative reasoning. Specifically, it discloses a method for generating programming task code based on multi-agent collaboration and iterative reasoning, comprising: obtaining a task description with a primary-secondary functional dependency structure; generating initial code by a generating agent based on a dependency-guided thought chain and performing static structure verification; collecting runtime execution trajectories in an isolated sandbox through dynamic agents; having a diagnostic agent attribute errors to the trajectories, distinguishing between inter-function collaboration errors and intra-function logic errors, and generating structured repair guidance; and combining historical perception feedback and a controlled reset mechanism to guide subsequent iterative repairs and avoid local optima. This invention solves the problems of ambiguous error location, easy code degradation, and low repair efficiency in existing code generation methods for multi-functional dependency tasks, achieving accurate error attribution, preventing code rollback, and improving generation success rate and repair convergence efficiency.

The invention discloses a steel-concrete composite beam cable-stayed bridge girder deflection calculation method considering interface slippage deformation. Comprising the following steps: calculating the slippage of the main beam section of the steel-concrete composite beam cable-stayed bridge, analyzing the deflection of the main beam of the steel-concrete composite beam cable-stayed bridge considering the interface slippage effect, and performing equivalent analysis on the mechanical behavior of the main beam in the steel-concrete composite beam cable-stayed bridge through a multi-span continuous system. According to the method, the deflection of the main beam of the steel-concrete composite beam cable-stayed bridge in the construction and operation stages can be accurately predicted, important technical support is provided for design, construction monitoring and operation maintenance of a bridge, and the construction quality and safety of bridge engineering can be improved.

This invention provides a method, apparatus, device, and readable storage medium for improving audio generation quality, relating to the field of speech conversion and recognition technology. The method includes acquiring low-sampling-rate audio, a target audio sampling rate, and an audio processing model; calculating an initial high-sampling-rate audio based on the low-sampling-rate audio, the target audio sampling rate, and the audio preprocessing mathematical model; calculating the target audio time-domain signal and target audio wavelet coefficients based on the initial high-sampling-rate audio and an audio signal reconstruction mathematical model; and solving the mathematical model based on the target audio time-domain signal, the target audio wavelet coefficients, and a preset fused audio signal mathematical model to obtain the target high-sampling-rate audio. This invention uses discrete wavelet transform to capture multi-scale details of the audio signal and reconstructs high-sampling-rate audio by combining the time-domain and frequency-domain information of the audio signal, further improving the overall generation quality of the audio.

The application discloses a ship body segmentation splicing method based on a laser point cloud device, and comprises the following steps: acquiring X partial point cloud data of a ship body segmentation; splicing the X partial point cloud data by using the spatial overlapping part and the same features of the point cloud data; deleting the point cloud data of a part which is not needed to be compared with a ship body segmentation design model, and reserving the ship body segmentation point cloud; generating a target point by the key position of the ship body segmentation point cloud data, performing coordinate conversion on the coordinates of the target point and the corresponding position of the ship body segmentation design model, converting the coordinate system of the ship body segmentation point cloud data into the same as the theoretical coordinate system of the ship body segmentation design model; outputting the required point cloud format, saving the complete ship body segmentation point cloud data, and realizing the ship body segmentation splicing. The precision and efficiency of the segmentation splicing directly determine the linear smoothness, structural strength, assembly stress, construction period and cost of the final ship body, and is one of the core key processes of ship construction.

The embodiment of the invention relates to a processing method and device for retrieving an enhanced language model based on a variational auto-encoder architecture. The method comprises the following steps: introducing a low-rank enhancer for a basic model to obtain a basic revision model; performing data acquisition on the public question and answer data set to obtain a first data set training basic revision model; constructing a second data set according to the target text library after training is finished, and combining the first data set and the second data set to obtain a third data set; constructing a feature vector library of the target text library; a retriever and a feature aggregation module are introduced into the basic revision model to form a retrieval enhancement language model, and the retrieval enhancement language model is in butt joint with the feature vector library; training a retrieval enhancement language model based on the third data set; and after the training is finished, processing a natural language question and answer task by using a retrieval enhanced language model. The quality of the generated text can be improved.

This invention discloses a collaborative update method for knowledge bases based on multi-source corpora, belonging to the field of knowledge base update technology. The method includes: acquiring incremental text streams from multiple heterogeneous corpora and segmenting them into text segments to be verified according to time windows; extracting the terminology dependency paths of the text segments to be verified and mapping them to candidate update triples for the target knowledge base; collecting existing triples in the knowledge base that have the same head entity as the candidate triples and extracting their tail entity type distribution; determining the conflict level based on the type offset between the tail entity type of the candidate triples and the existing distribution; directly entering the triples into the review queue when the conflict level is below a threshold; recalling a set of supporting texts from the heterogeneous corpora, correcting the relational predicates based on co-occurrence frequency, and then sending them into the review queue; and writing each triple into the main storage area of ​​the knowledge base in timestamp order. This invention achieves adaptive conflict handling in incremental knowledge base updates, effectively balancing update efficiency and knowledge consistency.

The application discloses a kind of T profile intersection panel double-angle transition operation methods, and the method specifically includes the following steps: S1, web in T profile is respectively welded and fixed with bulkhead and outer plate, and the circular radius R of arc angle transition is measured;S2, the panel of T profile on bulkhead is installed on the web on bulkhead, and the panel width B is measured;S3, the panel of T profile on outer plate is installed on the web on outer plate, and the angle A of panel and web on outer plate is measured;S4, make dome long circle bottom platform device, according to the circular radius R cutting dome long circle bottom platform, obtain the transition panel of arc angle transition;S5, the transition panel is installed on the web;S6, the transition panel is cut to panel excess after installation is completed, and the installation of bulkhead and outer plate transition panel is completed.The application is cut by making dome long circle bottom platform to realize the manufacture and installation of transition panel, improve the installation efficiency of transition panel and construction quality.

The invention discloses an efficient and automatic construction method for Tibetan and Chinese bilingual parallel corpora, and relates to the technical field of Tibetan and Chinese bilingual parallel corpora construction.The Tibetan and Chinese bilingual parallel corpora construction comprises a base model unit, a localization processing unit and a Tibetan stability strengthening module, the base model unit is a Qwen2.5 series pre-training model as a technical base, and the localization processing unit is a local processing unit; the training model comprises a 70B parameter main generation model and a 7B parameter lightweight intention judgment model, and the 70B model is responsible for receiving an input text and generating Tibetan-Chinese bilingual parallel sentence pairs. A base model unit, a localization processing unit and a Tibetan stability strengthening module communicate with one another through shared memory communication, the Tibetan stability strengthening module further comprises a double-model cooperation mechanism, and the working process of the double-model cooperation mechanism comprises the steps that input Chinese sentences are preprocessed through a word segmentation module, 7B model execution intention triad analysis is carried out, and the Chinese sentences are classified into Chinese sentences; and semantic control codes are generated, so that the output stability of the Tibetan and Chinese bilingual parallel corpora is improved through a double-model collaborative architecture.

This application provides a method for controlling the upward tilt of the side deck sections of a ship, belonging to the field of shipbuilding technology. The method includes: simulating the anti-deformation state of the side section assembly using design software to calculate the upward tilt at the deck docking position; based on the calculation results, implementing a tapered anti-deformation design that decreases from near to far center at the lower end of the transverse bulkhead during the side section design stage; controlling the deck inclination to meet design requirements during the section construction stage; and controlling the outward anti-deformation of the side section sections and positioning the height according to positive tolerances during the assembly stage. This method, by incorporating pre-compensation during the design stage, effectively offsets the upward tilt of the deck caused by ensuring the beam during the assembly stage, simultaneously solving the height misalignment problem between the side section bulkheads and the compartment sections, achieving a balance between beam control and internal structural precision, and improving the quality of shipbuilding.

This application discloses a method, apparatus, and computer program product for constructing negative samples. The method includes: firstly, performing token-level cross-modal alignment processing on the target image and its associated target question text to overcome the semantic coarseness problem caused by relying on global similarity or heuristic rules in existing methods. Then, based on the obtained alignment result, masking processing is performed on image patches corresponding to key visual regions in the target image to obtain a masked image patch token sequence, thereby generating a masked target image. Next, the incorrect response content generated by VLM based on the masked target image for the target question text can be used to construct high-quality negative samples with semantic interpretability. This avoids the problem of arbitrary selection of occlusion regions without semantic basis in existing methods, and also ensures that the generated negative samples can truly reach key nodes on the VLM inference chain, rather than simply random destruction or perturbation, thus improving the construction quality.

The invention discloses an improved WaveGAN radar radiation source sequence signal augmentation method based on physical constraints, and relates to the technical field of radar radiation source signal processing, and the method comprises the steps: carrying out the preprocessing of an original radar time domain signal, and constructing a one-dimensional radar signal sequence data set; an improved WaveGAN model is constructed, a generator of the improved WaveGAN model adopts a deep deconvolution neural network containing a pyramid type multi-scale convolution kernel and introduces a self-attention mechanism, and a discriminator adopts a convolution neural network containing an inverted pyramid type multi-scale convolution kernel and introduces a self-attention mechanism; inputting a data set into the model for adversarial training, wherein a total loss function of a generator is formed by weighting adversarial loss and mean square error loss of constraint signal physical characteristics; and synthesizing a radar radiation source signal sequence for data augmentation by using the trained generator. According to the method, the quality of the generated signal is remarkably improved.

The utility model discloses a waterproof outer wall concrete structure, and relates to the technical field of walls. The wall comprises a wall base layer, an isolation layer is fixedly connected to the outer surface of the wall base layer, and an outer layer is fixedly connected to the outer surface of the isolation layer; the isolating layer comprises a base material layer, the inner surface of the base material layer is fixedly connected with a reinforcing layer, the outer surface of the base material layer is fixedly connected with an anti-corrosion layer, and the outer surface of the anti-corrosion layer is fixedly connected with a protective layer. Through layer-by-layer protection of the isolation layer, the waterproof mortar layer, the waterproof coating layer and the waterproof breathable film layer, the waterproof performance of the outer wall is greatly improved, rainwater permeation is effectively blocked, the isolation layer effectively blocks alkaline substances seeping out of a wall body base layer, the waterproof mortar layer is protected, and it is ensured that a waterproof system is effective for a long time; the isolation layer can buffer tiny deformation of the wall base layer, damage to the waterproof mortar layer caused by base layer change is avoided, and the integrity of the waterproof structure is maintained.

The invention discloses a feature enhancement fusion-based fundus fluorescence angiography collaborative generation method, which comprises the steps of constructing and training an improved cyclic generative adversarial network model, and comprises a multi-scale fusion generator, a residual network generator, a first discriminator and a second discriminator, a multi-scale fusion generator, a residual network generator and a first discriminator are sequentially connected to form a main generation network, then the residual network generator, the multi-scale fusion generator and a second discriminator are sequentially connected to form an auxiliary generation network, and the main generation network and the auxiliary generation network are trained. Completing the training of the multi-scale fusion generator in the process of generating and reconstructing the fundus fluorescent angiography image; and converting the to-be-detected color fundus structure image into a fundus fluorescent angiography image by using the trained multi-scale fusion generator.

The invention relates to the technical field of medical treatment, in particular to a medical record extraction method based on a large language model. The method comprises the following steps: performing fine-grained classification and context verification on candidate terms through a BERT-Md model, and outputting a fact support; guiding the first call of the large language model through the first composite prompt, and synthesizing a context example specific to a case; and guiding the second calling of the large language model through the second composite prompt to generate a target clinical abstract. The invention provides a large language model-based medical record extraction method, which comprises the following steps of: extracting and classifying key clinical elements from an original medical record through a BERT-Md model, and inputting the extracted key words into a large language model to generate a context example conforming to clinical logic; and ensuring that the generated abstract contains eight necessary modules through a constraint decoding technology, automatically marking an abnormal test value reference range, and outputting a clinical abstract with a standard format and standard information density.

This invention discloses a backdoor attack method, system, and medium based on multi-object semantic coexistence in text-to-image diffusion models. This method utilizes the perspective of multi-object semantic coexistence in text-to-image diffusion models to develop MOBA backdoor attack schemes. First, by constructing a trigger alignment dataset and optimizing backdoor implantation and semantic preservation in parallel, the attack success rate and visual concealment are effectively improved, reducing the impact of semantic corruption on attack effectiveness. Second, during model training, an attention-based decoupling backdoor enhancement mechanism is adopted. By decoupling the attention regions of different objects, the semantic integrity of the input prompt is maintained while the backdoor is activated and the attention distribution is reasonably adjusted to reduce the impact of generation bias on attack concealment. The method of this invention ensures both visual concealment and model performance under benign input while achieving efficient backdoor attacks.

The application discloses a kind of machine learning training topology generator and the method for generating topological discriminator model, comprising the following steps: with matrix pair form characterizing real topological data, and pre-processing;Topology generator is constructed, and topological pseudo-matrix pair data is generated;Topological discriminator is constructed to identify the source of topological data;The topological generator and the topological discriminator are based on the adversarial training of generative adversarial network;Low-voltage area topological matrix pair data is generated, and is converted into visual topological graph.The application realizes the coevolution of topological generator and topological discriminator by constructing topological generator and topological discriminator and through the adversarial training of both, and then enables topological generator to automatically generate a large number of topological data in accordance with real station area statistical distribution and engineering rationality from simple input, with the technical effects of high generation quality, high automation efficiency, guaranteeing physical rationality, solving data scarcity problem and strong flexibility and adaptability.

The invention discloses a medical question and answer method and device, related equipment and a computer program product, and the method comprises the steps: retrieving a clinical reasoning path in a medical hierarchical knowledge graph based on a clinical query of a user, and firstly determining an initial medical entity related to the clinical query in the graph as a current medical entity; a current state vector representing a current retrieval scene is constructed based on an embedded vector of a clinical query of a user, an embedded vector of a current medical entity and an embedded vector of a configured global medical knowledge set. The next-hop medical entity is determined in the medical hierarchical knowledge graph based on the current state vector through the pre-trained strategy network, and the clinical reasoning path is added until the end condition is reached, so that the logic preciseness and the path effectiveness of the clinical reasoning path can be improved, and the path quality is improved. A clinical reasoning path is used as knowledge enhancement information to assist a large model to generate answers of clinical queries, and the generation quality of question and answer results of a medical scene is improved.

This invention relates to a dynamic retrieval enhancement generation method based on critical path entropy increase trends and document selection. Addressing the issues of retrieval response lag and false triggering caused by single-point threshold triggering in existing technologies, as well as noise interference and resource waste caused by direct splicing of Top-K retrieval documents, this invention creatively proposes a critical path entropy increase trend triggering mechanism. It optimizes single-point entropy monitoring of all tokens to critical path token entropy increase trend monitoring, achieving on-demand retrieval triggering by dynamically determining uncertainty increments, thereby suppressing false triggering caused by noise fluctuations in non-critical locations and alleviating retrieval response lag. Furthermore, this invention proposes a document selection model based on direct preference optimization of DPO, optimizing the coarse-grained injection of Top-K documents into a fine-grained filtering and injection mechanism. By filtering out irrelevant and redundant documents, it reduces the invalid occupation of the context window, thereby solving the problems of reduced generation quality and wasted computational resources caused by noise interference.

The invention discloses a multi-mode intelligent plasma activated water device and method, and belongs to the technical field of plasma activated water preparation. The equipment comprises an air supply unit, a plasma generation unit, a gas-liquid mass transfer unit and an intelligent control unit, the plasma generation unit comprises a plurality of surface dielectric barrier discharge plates which are arranged in parallel; and the intelligent control unit is configured to be switched to operate in two working states of a low-power ozone mode and a high-power nitrogen oxide mode. In the low-power ozone mode, the discharge plates alternately supply power and automatically switch when detecting that the temperature reaches a preset threshold value; and in a high-power nitrogen oxide mode, the discharge plate synchronously and continuously works. The multi-purpose machine is achieved through mode switching, overheating is effectively prevented and the service life is prolonged through alternate power supply in a low-power mode, efficient treatment is achieved in a high-power mode, the differentiated requirements of different scenes for activated water components are met, and the multi-purpose machine has the advantages of being flexible in operation, high in stability and high in intelligent degree.

The utility model relates to the technical field of fabricated buildings, in particular to an external wall panel stripping and hoisting tool which comprises a truss beam and a hoisting beam, the truss beam comprises an upper main beam and two lower main beams, the two lower main beams are arranged in parallel, the upper main beam is arranged above the lower main beams, the upper main beam is arranged at the central position between the two lower main beams, and the hoisting beam is arranged above the upper main beam. A truss beam lifting lug is arranged at the top of the upper main beam, fixing seats are correspondingly arranged on the outer sides of the two lower main beams respectively, the hoisting beam comprises a hoisting main beam, the hoisting main beam is fixedly connected to the fixing seats, and more than two hoisting beam lifting lugs are arranged at the bottom of the hoisting main beam. The external wall panel stripping and hoisting tool can meet the hoisting requirements of different large external wall panels, the applicability of the hoisting tool in assembly type civil buildings and assembly type industrial buildings is improved, and application and popularization of steel structure and concrete prefabricated part building systems can be accelerated.

Embodiments of the present disclosure provide a text information generation method and device, electronic equipment and storage medium. The method comprises: obtaining a target video, and extracting a video feature of the target video, the video feature being used to represent content in at least one content dimension of the target video; generating a target prompt according to the video feature, the target prompt being used to represent a generation rule of text information for the target video; and generating the text information for the target video based on the target prompt. By extracting the video feature of the target video, generating the target prompt, and using the target prompt in combination with the capability of a language model to generate the text information for the target video, the method realizes fast and efficient generation of the text information, while ensuring that the content of the generated text information matches the video content of the target video, and improves the generation efficiency and content quality of the text information corresponding to the target video.